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Elemental composition of different types of wood
Nuclear Instruments and Methods in Physics Research B 109/110 (1996) 328-331
B
N
Beam Interactions with Materials & Atoms
ELSEVIER
Elemental composition of different types of wood M. Esch*, D. Hofmann, G. Krebs, C. Thierfelder, R. Wiinsch, R. Maier, M. Kuzel, M. Schosnig, K.O. Groeneveld Institut fiir Kernphysik der Joh. W. Goethe-Universitiit Frankfurt am Main, August Euler Strafle 6, 60486 Frankfurt am Main, Germany
Abstract For the use of wood as an environmental sensor the average or normal elemental composition of wood has to be known (here with Z > 12). Since we find with PIXE that the elemental composition depends on the species, environmental influences can only be deduced indirectly from deviations from average elemental concentrations, which have to be known for each examined species. The average elemental composition was calculated from the concentrations of more than 10 samples from almost as many sites for beech and oak. Other species were also analysed but not from more than three different sites. Significant correlations between certain elemental concentrations were found (in particular between Ca and Mn), also studied was the influence of the growing site on the elemental concentrations.
1. Introduction The death of trees, the "Waldsterben" in Germany is a strong motivation for the search of its cause and the study of the dynamics behind the physiological activities that lead eventually to the death of a tree. Although the "Waldsterben" has been studied extensively since the early eighties in Germany, it seems now that there is still no coherent theory on basic tree physiology. The aim of this work was to investigate the relations between elemental concentrations in wood. The use of the PIXE method for wood analysis has been reported earlier [1-5]. The dependence of the elemental composition of wood on the growing site and the species was studied. To exclude strong site-related effects we examined wood coming mostly from an area of 20 times 15 km 2, with no heavy industry, in a recreation area for the population of the Rhein-Main region. The soil composition depends not significantly on the site in this area. Wood which grew under "equivalent" conditions on comparable soil was analysed by PIXE. The remaining growth influencing factors are mostly: - t h e background air-pollution, - the amount of sunlight which each site receives (certainly not equal among the sites), - the quantity of precipitation (which also is not equal for the sample sites). Pernest~l et al. [4] mentioned unspecified " . . . very local factors, individual for each tree site, which influence * Corresponding author.
the result of the trace element analysis". In the present work we did not investigate the composition of the soil or the amount of sunshine or precipitation at each sampling site, so no additional factors could be stated. Our aim was to study correlations between the elemental concentrations as detailed as possible; we, therefore, preserved the ring-structure of the wood, and discarded sample preparation methods as cryogenic pulverisation, microwave digestion or high temperature dry ashing [3] and similar destructive approaches.
2. Experimental procedure 1) Wood samples were collected from 15 sites in the Taunus mountains north-west of Frankfurt am Main, an area which is partly under environmental protection law, has relatively low population density and no strong polluting industry. The sampling area m e a s u r e s 20 to 15 km 2 and is densely wooded by pine, oak, beech and several more seldom tree-species. Samples were collected from wind broken trees and branches, which broke so recently that a change in elemental concentrations caused by decomposition was not expected. 2) The wood was prepared with hard metal tools as "thick target samples" in a size of 60 mm length, 20 mm width and 2 mm thickness. We found that hardwood has a much more stable structure and is easier to cut than wood of pine-like trees. No contamination by sawing nd cutting was observed. Surface charging-up by the incident proton beam was prevented by vacuum evaporation of ca. 50 nm
0168-583X/96/$15.00 Copyright © 1996 Elsevier Science B.V. All rights reserved S S D I 0168-583X(95)00930-2
329
M. Esch et al. / Nucl. Instr. and Meth. in Phys. Res. B 109/110 (1996) 328-331
Table 1 Median elemental concentration values (in ppm) for the most commonly found elements for four species Number of spectra
Species
A1
Si
P
S
C1
K
Ca
Cr
Ti
Mn
Fe
207 143 52 36
beech oak birch sweet chestnut
2.460 3.683
650 875 589 670
204 125 161 63
209 240 170 194
28 26 20 22
1.009 570 187 49
721 350 540 245
3.7 6.3 6.7 6
3.4 3.9 4.5 3.4
279 134 104 113
64 12 8.8 8.2
4.215
of high purity carbon [6]. Because the samples were dried in several stages (the last stage before analysis was then drying during the vacuum evaporation process), the experiment chamber had been evacuated for about 15 to 25 minutes, before the first X-ray spectra were taken. No deformation of the wood under vacuum was observed. 3) A modified version of the described [7] PIXE setup was used. All samples were irradiated with protons of 2 MeV from a 2.5 M V Van de Graaff accelerator, collimated by a quadrupole doublet [8] to a rectangular cross section of 0.5 to 2.0 mm 2. The proton beam was kept nondestructive, at currents between 3 and 7 nA. The accumulated charge on the targets was 2 IxC ( + 2 % ) . The reproducibility of the results, within the relative errors quoted below, has been observed. The Si(Li)-detector (10 m m 2, AE = 168 eV at 5.898 keV, 12 Ixm Be window, 12 = 4.8 X 10 4 sr) was positioned at 135 °, with an additional 36 ~ m Hostaphan absorber. The spectra, taken from 2 to 35 spots separated by 1 - 2 mm, were registered using a PC-based MCA-card (AccuSpec, Nuclear Data Inc.), and analysed by means of the PIXYKLM program, using the absolute yield method, which requires no internal standards [9].
3. Results and discussion Several biological and physical references were studied to confirm the observed concentration values [1,10,11,14]; furthermore a sample was divided and the adjacent surfaces were analysed by PIXE independently both in
Frankfurt and in Debrecen [14]; the calculated concentration values agreed very well within 10%. The absolute values have an absolute error of about 25%, the relative values have errors of 6%. Of greater interest than the absolute concentration values were the relations between the elements. These relations were deduced in two ways: 1) the ratio between elements in individual spectra, 2) the correlation of two elements, using the correlation coefficient, within one sample. The following discussion is divided into three parts, the first concerns the absolute concentration values, the second deals with the relative values and the third presents the found correlations. 1) The typical composition for several species and the more commonly found elements in terms of median values are given for all samples of the listed species in Table 1. The detection limits for our studies depended somewhat on the species, but as a guideline the detection limits, given in Table 2, can be used. The absolute values varied strongly from species to species but to a lesser degree for the same species from site to site. In some samples the values of the major elements (S, P, K, Ca, Mn) remained constant within + 2 5 % , most of the time. Within rings the differences in elemental concentration between early wood and late wood were not so pronounced (5 to 10%) as from ring to ring. This is in contrast to the findings of Lill et al. [13] who found a strong dependence on position of concentrations within single rings. This difference could most likely be explained by the fact of the difference in latitude between the Frankfurt sampling area and the area in Finland from Ref. [13], so that the growing conditions were very
Table 2 Relative error (%) of the absolute concentrations for the detected elements and their average detection limits (ppm). The values vary from species to species and are in a lesser degree dependent on the individual composition of the sample Element A1 Rel. error Det. limit
5-50 200-1500
Si 10-50 50-300
P 5-7 20-70
S 5-7 10-30
C1 5-15 10-20
K
Ca
Cr
Ti
5-7 <10
4-6 <7
10 <1
10 <2.5
As
Ba
Hg
Pb
Element
Rel. error Det. limit
Mn
Fe
Ni
Cu
Zn
4-10 <3
5-15 <4
5-15 <2.5
5-10 <5
5-10 <5
5-40 <4
10-20 <8
10-20 25
20-50 40
IV. BIOMEDICAL SAMPLES
330
M. Esch et al. / Nucl. Instr. and Meth. in Phys. Res. B 109/110 (1996) 3 2 8 - 3 3 1
Table 3 Elemental concentration ratios of several combinations of elements and some species
Beech Oak Birch Sweet chestnut
K/Ca
Ca/Mn
Mn/Fe
Ca/S
K/S
Ca/P
K/P
1.4 1.6 0.35 0.2
2.6 2.6 5.2 2.2
14.7 11.2 3.2 1.3
3.5 1.5 3.2 1.3
4.8 2.4 1.l 0.25
3.5 2.8 3.4 3.9
5.0 4.6 1.2 0.8
Table 4 The more common observed correlations between elements and their relative abundance Correlation
Abundance [%]
K/S
Ca/S
Ca/K
K/Mn
Ca/Mn
Mn/Fe
50
52
63
50
69
48
different (the species difference may also have contributed here). 2) The ratio of elemental concentrations showed a surprisingly strong dependence on the species (Table 3) (up to a factor of 10) and to a lesser degree on the site (below a factor of 3). The ratio was shown to be roughly constant within one sample (mostly within 10%), with no big differences from year to year. Along single rings the ratio was almost conslant, and no significant vertical height-dependence could be observed.
200 , ~r..
150
"~
100
o
I
I
I
4. C o n c l u s i o n
5O 0
500
I
I
1
400
500
600
700
(Co)
80of/ t 600
o
400
!
100
3) Particularly pronounced and found in 69% of all samples was the correlation between Ca and Mn as observed also in Ref. [4]. An overview for the more common correlations is given in Table 4: only correlations that were judged as significant (r > 0.8) were taken into account. Fig. 1 shows two strong correlations between (Ca, Mn) and (Ca, K). The observed correlations should contain information about the physiological state of the tree; it had been proposed to use the M n / C a ratio as an indicator for acidification of the soil [4].
!
It has been demonstrated that PIXE can be well used for wood elemental analysis, with sufficient detection limits, and with non-destructively prepared samples. Typical elemental concentration patterns for different species could be found, and a kind of natural " b a c k g r o u n d " composition for two species was determined, valid at least for the sampled region. Elemental concentrations are shown to be significantly different from year ring to year ring but not within single rings. The detected elements along with the achieved detection limits showed that it should be possible to use trees as indicators for heavy element soil pollution, besides the possibility to examine pollution by lighter elements, especially sulphur [1]. From relation data of the detected elements it appears to be possible to come to new or better models for elemental uptake and physiology for trees, in cooperation with biologists and forest researchers.
300
200
(co) Fig. 1. Concentration values (in weight ppm) c(Mn) versus c(Ca) of birch sample (#53, top) and c(K) versus c(Ca) of oak sample (#19, bottom). Solid line: linear least squares fit to all measured data points. Correlation coefficients are r(birch) = 0.969, r(oak) = 0.998.
Acknowledgements
We appreciate the helpful advice and competent suggestions provided by Gy. Szabr/Debrecen, Ungarn. We also thank M.I. Dinator/Santiago de Chile for her help in discussion and experiments.
M. Esch et al. / Nucl. Instr. and Meth. in Phys. Res. B 109/110 (1996) 328-331
References [1] A.H. Legge, H.C. Kaufmann and J.W. Winchester, Nucl. Instr. and Meth. B 3 (1984) 507. [2] J. Injuk, M. Nagj and V. Valkovic, Anal. Chim. Acta 195 (1987) 299. [3] G.S. Hall, Nucl. Instr. and Meth. B 49 (1990) 60. [4] K. Pemest~l and B. Johnsson, Nucl. Instr. and Meth. B 75 (1993) 326. [5] G.A. Glass and K.H. Hasenstein, Nucl. Instr. and Meth. B 79 (1993) 393. [6] H. Ohashi, Y. Koizumi and K. Kobayashi, Nucl. Instr. and Meth. B 75 (1993) 140. [7] G. Henrici, D. Hofmann, H.W. Georgii and K.O. Groeneveld, J. Aerosol Sci. 12 (1990) 391.
331
[8] D. Hofmann, Nucl. Instr. and Meth. B 30 (1988) 607. [9] Gy. Szab6 and I. Borbtly-Kiss, Nucl. Instr. and Meth. B 75 (1993) 123. [10] P. Rademacher, J. Bauch and J. Puls, Holzforschung Bd. 40 (1986) 331. [11] A. Vogelei and G.M. Rothe, Mitteilungen fiir Wissenschaft und Technik Bd. X, Nr. 6 (1993) 197. [12] I. Borbtly-Kiss and I. Rajta, private communication; I. Borbtly-Kiss, E. Koltay, Gy. Szabo, these Proceedings (PIXE-7), Nucl. Instr. and Meth. B 109/110 (1996) 445. [13] J.O. Lill, private communication. [14] K. Pernest~l, H.K. Li and B. Johnsson, Nucl. Instr. and Meth. B 49 (1990) 261.
IV. BIOMEDICAL SAMPLES
B
N
Beam Interactions with Materials & Atoms
ELSEVIER
Elemental composition of different types of wood M. Esch*, D. Hofmann, G. Krebs, C. Thierfelder, R. Wiinsch, R. Maier, M. Kuzel, M. Schosnig, K.O. Groeneveld Institut fiir Kernphysik der Joh. W. Goethe-Universitiit Frankfurt am Main, August Euler Strafle 6, 60486 Frankfurt am Main, Germany
Abstract For the use of wood as an environmental sensor the average or normal elemental composition of wood has to be known (here with Z > 12). Since we find with PIXE that the elemental composition depends on the species, environmental influences can only be deduced indirectly from deviations from average elemental concentrations, which have to be known for each examined species. The average elemental composition was calculated from the concentrations of more than 10 samples from almost as many sites for beech and oak. Other species were also analysed but not from more than three different sites. Significant correlations between certain elemental concentrations were found (in particular between Ca and Mn), also studied was the influence of the growing site on the elemental concentrations.
1. Introduction The death of trees, the "Waldsterben" in Germany is a strong motivation for the search of its cause and the study of the dynamics behind the physiological activities that lead eventually to the death of a tree. Although the "Waldsterben" has been studied extensively since the early eighties in Germany, it seems now that there is still no coherent theory on basic tree physiology. The aim of this work was to investigate the relations between elemental concentrations in wood. The use of the PIXE method for wood analysis has been reported earlier [1-5]. The dependence of the elemental composition of wood on the growing site and the species was studied. To exclude strong site-related effects we examined wood coming mostly from an area of 20 times 15 km 2, with no heavy industry, in a recreation area for the population of the Rhein-Main region. The soil composition depends not significantly on the site in this area. Wood which grew under "equivalent" conditions on comparable soil was analysed by PIXE. The remaining growth influencing factors are mostly: - t h e background air-pollution, - the amount of sunlight which each site receives (certainly not equal among the sites), - the quantity of precipitation (which also is not equal for the sample sites). Pernest~l et al. [4] mentioned unspecified " . . . very local factors, individual for each tree site, which influence * Corresponding author.
the result of the trace element analysis". In the present work we did not investigate the composition of the soil or the amount of sunshine or precipitation at each sampling site, so no additional factors could be stated. Our aim was to study correlations between the elemental concentrations as detailed as possible; we, therefore, preserved the ring-structure of the wood, and discarded sample preparation methods as cryogenic pulverisation, microwave digestion or high temperature dry ashing [3] and similar destructive approaches.
2. Experimental procedure 1) Wood samples were collected from 15 sites in the Taunus mountains north-west of Frankfurt am Main, an area which is partly under environmental protection law, has relatively low population density and no strong polluting industry. The sampling area m e a s u r e s 20 to 15 km 2 and is densely wooded by pine, oak, beech and several more seldom tree-species. Samples were collected from wind broken trees and branches, which broke so recently that a change in elemental concentrations caused by decomposition was not expected. 2) The wood was prepared with hard metal tools as "thick target samples" in a size of 60 mm length, 20 mm width and 2 mm thickness. We found that hardwood has a much more stable structure and is easier to cut than wood of pine-like trees. No contamination by sawing nd cutting was observed. Surface charging-up by the incident proton beam was prevented by vacuum evaporation of ca. 50 nm
0168-583X/96/$15.00 Copyright © 1996 Elsevier Science B.V. All rights reserved S S D I 0168-583X(95)00930-2
329
M. Esch et al. / Nucl. Instr. and Meth. in Phys. Res. B 109/110 (1996) 328-331
Table 1 Median elemental concentration values (in ppm) for the most commonly found elements for four species Number of spectra
Species
A1
Si
P
S
C1
K
Ca
Cr
Ti
Mn
Fe
207 143 52 36
beech oak birch sweet chestnut
2.460 3.683
650 875 589 670
204 125 161 63
209 240 170 194
28 26 20 22
1.009 570 187 49
721 350 540 245
3.7 6.3 6.7 6
3.4 3.9 4.5 3.4
279 134 104 113
64 12 8.8 8.2
4.215
of high purity carbon [6]. Because the samples were dried in several stages (the last stage before analysis was then drying during the vacuum evaporation process), the experiment chamber had been evacuated for about 15 to 25 minutes, before the first X-ray spectra were taken. No deformation of the wood under vacuum was observed. 3) A modified version of the described [7] PIXE setup was used. All samples were irradiated with protons of 2 MeV from a 2.5 M V Van de Graaff accelerator, collimated by a quadrupole doublet [8] to a rectangular cross section of 0.5 to 2.0 mm 2. The proton beam was kept nondestructive, at currents between 3 and 7 nA. The accumulated charge on the targets was 2 IxC ( + 2 % ) . The reproducibility of the results, within the relative errors quoted below, has been observed. The Si(Li)-detector (10 m m 2, AE = 168 eV at 5.898 keV, 12 Ixm Be window, 12 = 4.8 X 10 4 sr) was positioned at 135 °, with an additional 36 ~ m Hostaphan absorber. The spectra, taken from 2 to 35 spots separated by 1 - 2 mm, were registered using a PC-based MCA-card (AccuSpec, Nuclear Data Inc.), and analysed by means of the PIXYKLM program, using the absolute yield method, which requires no internal standards [9].
3. Results and discussion Several biological and physical references were studied to confirm the observed concentration values [1,10,11,14]; furthermore a sample was divided and the adjacent surfaces were analysed by PIXE independently both in
Frankfurt and in Debrecen [14]; the calculated concentration values agreed very well within 10%. The absolute values have an absolute error of about 25%, the relative values have errors of 6%. Of greater interest than the absolute concentration values were the relations between the elements. These relations were deduced in two ways: 1) the ratio between elements in individual spectra, 2) the correlation of two elements, using the correlation coefficient, within one sample. The following discussion is divided into three parts, the first concerns the absolute concentration values, the second deals with the relative values and the third presents the found correlations. 1) The typical composition for several species and the more commonly found elements in terms of median values are given for all samples of the listed species in Table 1. The detection limits for our studies depended somewhat on the species, but as a guideline the detection limits, given in Table 2, can be used. The absolute values varied strongly from species to species but to a lesser degree for the same species from site to site. In some samples the values of the major elements (S, P, K, Ca, Mn) remained constant within + 2 5 % , most of the time. Within rings the differences in elemental concentration between early wood and late wood were not so pronounced (5 to 10%) as from ring to ring. This is in contrast to the findings of Lill et al. [13] who found a strong dependence on position of concentrations within single rings. This difference could most likely be explained by the fact of the difference in latitude between the Frankfurt sampling area and the area in Finland from Ref. [13], so that the growing conditions were very
Table 2 Relative error (%) of the absolute concentrations for the detected elements and their average detection limits (ppm). The values vary from species to species and are in a lesser degree dependent on the individual composition of the sample Element A1 Rel. error Det. limit
5-50 200-1500
Si 10-50 50-300
P 5-7 20-70
S 5-7 10-30
C1 5-15 10-20
K
Ca
Cr
Ti
5-7 <10
4-6 <7
10 <1
10 <2.5
As
Ba
Hg
Pb
Element
Rel. error Det. limit
Mn
Fe
Ni
Cu
Zn
4-10 <3
5-15 <4
5-15 <2.5
5-10 <5
5-10 <5
5-40 <4
10-20 <8
10-20 25
20-50 40
IV. BIOMEDICAL SAMPLES
330
M. Esch et al. / Nucl. Instr. and Meth. in Phys. Res. B 109/110 (1996) 3 2 8 - 3 3 1
Table 3 Elemental concentration ratios of several combinations of elements and some species
Beech Oak Birch Sweet chestnut
K/Ca
Ca/Mn
Mn/Fe
Ca/S
K/S
Ca/P
K/P
1.4 1.6 0.35 0.2
2.6 2.6 5.2 2.2
14.7 11.2 3.2 1.3
3.5 1.5 3.2 1.3
4.8 2.4 1.l 0.25
3.5 2.8 3.4 3.9
5.0 4.6 1.2 0.8
Table 4 The more common observed correlations between elements and their relative abundance Correlation
Abundance [%]
K/S
Ca/S
Ca/K
K/Mn
Ca/Mn
Mn/Fe
50
52
63
50
69
48
different (the species difference may also have contributed here). 2) The ratio of elemental concentrations showed a surprisingly strong dependence on the species (Table 3) (up to a factor of 10) and to a lesser degree on the site (below a factor of 3). The ratio was shown to be roughly constant within one sample (mostly within 10%), with no big differences from year to year. Along single rings the ratio was almost conslant, and no significant vertical height-dependence could be observed.
200 , ~r..
150
"~
100
o
I
I
I
4. C o n c l u s i o n
5O 0
500
I
I
1
400
500
600
700
(Co)
80of/ t 600
o
400
!
100
3) Particularly pronounced and found in 69% of all samples was the correlation between Ca and Mn as observed also in Ref. [4]. An overview for the more common correlations is given in Table 4: only correlations that were judged as significant (r > 0.8) were taken into account. Fig. 1 shows two strong correlations between (Ca, Mn) and (Ca, K). The observed correlations should contain information about the physiological state of the tree; it had been proposed to use the M n / C a ratio as an indicator for acidification of the soil [4].
!
It has been demonstrated that PIXE can be well used for wood elemental analysis, with sufficient detection limits, and with non-destructively prepared samples. Typical elemental concentration patterns for different species could be found, and a kind of natural " b a c k g r o u n d " composition for two species was determined, valid at least for the sampled region. Elemental concentrations are shown to be significantly different from year ring to year ring but not within single rings. The detected elements along with the achieved detection limits showed that it should be possible to use trees as indicators for heavy element soil pollution, besides the possibility to examine pollution by lighter elements, especially sulphur [1]. From relation data of the detected elements it appears to be possible to come to new or better models for elemental uptake and physiology for trees, in cooperation with biologists and forest researchers.
300
200
(co) Fig. 1. Concentration values (in weight ppm) c(Mn) versus c(Ca) of birch sample (#53, top) and c(K) versus c(Ca) of oak sample (#19, bottom). Solid line: linear least squares fit to all measured data points. Correlation coefficients are r(birch) = 0.969, r(oak) = 0.998.
Acknowledgements
We appreciate the helpful advice and competent suggestions provided by Gy. Szabr/Debrecen, Ungarn. We also thank M.I. Dinator/Santiago de Chile for her help in discussion and experiments.
M. Esch et al. / Nucl. Instr. and Meth. in Phys. Res. B 109/110 (1996) 328-331
References [1] A.H. Legge, H.C. Kaufmann and J.W. Winchester, Nucl. Instr. and Meth. B 3 (1984) 507. [2] J. Injuk, M. Nagj and V. Valkovic, Anal. Chim. Acta 195 (1987) 299. [3] G.S. Hall, Nucl. Instr. and Meth. B 49 (1990) 60. [4] K. Pemest~l and B. Johnsson, Nucl. Instr. and Meth. B 75 (1993) 326. [5] G.A. Glass and K.H. Hasenstein, Nucl. Instr. and Meth. B 79 (1993) 393. [6] H. Ohashi, Y. Koizumi and K. Kobayashi, Nucl. Instr. and Meth. B 75 (1993) 140. [7] G. Henrici, D. Hofmann, H.W. Georgii and K.O. Groeneveld, J. Aerosol Sci. 12 (1990) 391.
331
[8] D. Hofmann, Nucl. Instr. and Meth. B 30 (1988) 607. [9] Gy. Szab6 and I. Borbtly-Kiss, Nucl. Instr. and Meth. B 75 (1993) 123. [10] P. Rademacher, J. Bauch and J. Puls, Holzforschung Bd. 40 (1986) 331. [11] A. Vogelei and G.M. Rothe, Mitteilungen fiir Wissenschaft und Technik Bd. X, Nr. 6 (1993) 197. [12] I. Borbtly-Kiss and I. Rajta, private communication; I. Borbtly-Kiss, E. Koltay, Gy. Szabo, these Proceedings (PIXE-7), Nucl. Instr. and Meth. B 109/110 (1996) 445. [13] J.O. Lill, private communication. [14] K. Pernest~l, H.K. Li and B. Johnsson, Nucl. Instr. and Meth. B 49 (1990) 261.
IV. BIOMEDICAL SAMPLES