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Investigation of the Discrimination between Aluminium Held within Vegetation and That Contributed by Soil Contamination Using ICP–AES and EPMA
JOBNAME: MIC 53#3 96 PAGE: 1 SESS: 61 OUTPUT: Tue Jun 18 13:18:29 1996 /xypage/worksmart/tsp000/69777e/1
MICROCHEMICAL JOURNAL ARTICLE NO. 0049
53, 337–348 (1996)
Investigation of the Discrimination between Aluminium Held within Vegetation and That Contributed by Soil Contamination Using ICP–AES and EPMA DEMING DONG Department of Environmental Science, Jilin University, 75 Jiefang Road, Changchun, People’s Republic of China 130023 The difficulties in the accurate determination of aluminium in plant materials have been known for a long time. A major problem is caused by aluminium contamination from soil/dust particles adhering to the vegetation. In this methodological approach, a combination of two analytical techniques [electron probe micro analysis (EPMA) and inductively coupled plasma–atomic emission spectrometry (ICP–AES)] was employed to investigate the aluminium held within vegetation and that contributed by soil/dust contamination. Aluminium concentrations in NIST (formally NBS) Certified Reference Material tomato leaves (SRM 1573) and citrus leaves (SRM 1572) and NIES Certified Reference Material tea leaves (NIES No.7) were determined by ICP–AES after acid digestion. The normal “total” acid attack (nitric and perchloric acids) gave a very low recovery of aluminium in tomato leaves (41.9%) compared with the provisional value quoted by NIST. The aluminium concentrations measured for the citrus leaves and tea leaves were much closer to the certified values. The contribution of aluminium from Al-rich soil/dust particles in these reference materials was estimated semiquantitatively by computer-controlled EPMA. The aluminium held in these particles corresponded in approximate concentration to the shortfall between the acid soluble component determined in this study and the certified value. Analysis by EPMA can provide, therefore, a method of estimating aluminium contributed by soil contamination to plant materials. The limitation of the Standard Reference Materials for the validation of methods for the determination of aluminium in vegetation are demonstrated. © 1996 Academic Press, Inc.
INTRODUCTION The difficulties in the accurate determination of aluminium in plant materials have been discussed over the past several years. A major problem is caused by aluminium contamination from soil/dust particles adhering to the vegetation (6,2,7). Fortmann and Johnson (3,4) and Coe and Lindbery (1) used scanning electron microscopy (SEM) to characterize individual particles and to determine the particle size distributions on foliage of plants. In this study, a combination of two analytical techniques [electron probe micro analysis (EPMA) and inductively coupled plasma–atomic emission spectrometry (ICP–AES)] was employed to investigate the aluminium held within vegetation and that contributed by soil/dust contamination. Some of the results have been published (8). MATERIALS AND METHODS National Institute of Standards and Technology, U.S.A. (NIST) Certified Reference Material tomato leaves (SRM 1573) and citrus leaves (SRM 1572), and National Institute for Environmental Studies, Japan (NIES) Certified Reference Material tea leaves (NIES No.7) were used in this methodological approach. Some of the soybean leaves and beans grown in the greenhouse pot trials were also examined using this method to verify if there were any soil/dust contamination to the samples. The reference materials and the soybean 337 0026-265X/96 $18.00 Copyright © 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.
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samples were dried overnight in an oven at 85°C prior to use. Dried samples were weighed (2 g) into clean Teflon tubes, with 20 ml fuming nitric acid (95% w/w). The tubes were placed into a heating block for 10 h at 150°C. After the bulk of the sample was dissolved, 3.0 ml perchloric acid (60% w/w) was added. The tubes were heated for another 18 h at 150°C, taken to dryness at 190°C, and leached by adding hydrochloric acid at 70°C. For the purposes of comparition, certain samples were treated with hydrofluoric acid (5 ml, 40% w/w) and further nitric (2 ml, 70% w/w) and perchloric acids (1 ml) prior to leaching with hydrochloric acid (10, 8). The ICP–AES instrumentation used was an ARL-34000C, 1-M vacuum spectrometer with PDP 11/04 computer. The wavelength used was 308.2 nm. The relevant instrumental conditions for the determination of Al by ICP–AES has been described by Ramsey and Thompson (9). In order to examine and analyse individual particles by EPMA, the dry leaf material was mounted onto a clean glass slide and vacuum coated with carbon. The EPMA utilized a JEOL 733 superprobe electron microscope with attached Link Analytical AN10000 data handling system. During the scanning electron microscopy (SEM), secondary electron images and backscattered electron images were taken for each sample. This allowed any mineral material to be recognized visually. Seventy-five fields (0.262 mm2 each), which were spaced at equal intervals, and a large number of mineral particles were examined in backscattered electron mode with the detector set to discriminate against material of low atomic number (i.e., the leaf mass). The mineral particles were then analysed semiquantitatively using energy dispersive spectroscopy (EDS) and classified according to their aluminium concentrations. The area occupied by the particles were measured automatically using the link analytical feature detection and classification program called Digiscan (11, 5). Finally, the aluminium concentrations contributed from soil/dust contamination to the total aluminium concentrations in the plant materials were estimated semiquantitatively. RESULTS AND DISCUSSION 1. Concentrations of Aluminium in Vegetation Samples The normal “total” nitric and perchloric acid attack gave a very low recovery of aluminium in tomato leaves (41.9%) compared with the provisional value quoted by NIST. Similar low results have been reported by Pierson and Evenson (7). The aluminium concentrations measured for the citrus leaves and tea leaves were much closer to the certified values (Table 1). The recovery of aluminium was 68.4 and 91.6%, respectively. When hydrofluoric acid was added to the digestion mixture, the aluminium concentrations found were close to the certified values in both cases. This validates the accuracy of the ICP–AES determination and shows that neither the digestion method nor instrumental bias was the cause of the low recovery of aluminium when decomposed without hydrofluoric acid. Only for one sample of the soybean leaves was there a big difference found in the aluminium concentrations obtained between the digestion of nitric/perchloric acid with and without hydrofluoric acid. For the other soybean leaves and beans there were not significant difference found between the two procedures of acid digestion. The results are given in Table 2.
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DETERMINATION OF ALUMINIUM IN PLANT MATERIALS TABLE 1 Concentrations of Aluminium in Leaf Materials Using Two Different Acid Decompositions Prior to Determination by ICP–AES (mg g−1) Sample Tomato leaf SRM 1573 Certified Value 1200a Nitric and perchloric acid digestion n 22 Mean 502.7 s 20.8 Recovery (%) 41.9 Nitric, perchloric, and hydrofluoric acid digestion n 13 Mean 1220.7 s 53.3 Recovery (%) 101.7 a
Citrus leaf SRM 1572
Tea leaf CRM 7
92 ± 15
775 ± 20
22 62.9 3.4 68.4
10 710.2 20.1 91.6
13 80.6 4.2 87.6
7 742.4 19.5 95.8
Provisional value.
2. Aluminium Contamination from Soil/Dust Particles Adhering to the Standard Reference Materials Scanning electron microscopy (SEM) was used to identify the nonleaf particles in samples (Figs. 1–3). Electron probe micro analysis (EPMA) was then carried out in two stages. Initial semiquantitative aluminium analysis of all the nonleaf particles in a fixed area revealed that there was a fraction that contained significantly high concentrations (>2.7% Al or >5% Al2O3). For the tomato leaves, 121 Al-rich particles were identified (6.7% of the total particles), and for the citrus leaves and the tea leaves there were 38 (12.0%) and 451 (76.8%) Al-rich particles, respectively. However, there was a marked difference in the distributions of aluminium concentrations of the Al-rich particles for these reference materials (Fig. 4). The proportions of the particles with high aluminium concentrations for the tomato leaves and citrus leaves were much higher than that for the tea leaves where 83% of particles were less than 10% Al2O3. The area of each Al-rich particle ranged from 1 to 20 mm2 for the tomato leaves and the citrus leaves, but that was less than 2 mm2 for the 99% of Al-rich particles on the tea leaves (Fig. 5). This resulted in the total area occupied by the Al-rich TABLE 2 Concentrationsa of Aluminium in Selected Soybean Leaves and Beans Using Two Different Acid Decompositions Prior to Determination by ICP–AES (mg g−1) Sample
Digested by HNO3 + HClO4 Digested by HNO3 + HClO4 + HF Difference a
Leaf-3
Leaf-26
Leaf-33
Bean-7
Bean-28
548.0 574.0 26.0
25.0 27.5 2.5
70.8 75.0 4.2
2.0 3.3 1.3
2.5 2.0 −0.5
The data in this table have a precision of < ± 10%, tested by the method of Thompson and Howarth.
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FIG. 1. Aluminium-rich particles in one field of view for a sample of NIST tomato leaves (SRM 1573). (a) A suspect nonleaf particle found on the tomato leaves by secondary electron image (SEI). (b) A backscattered electron image (BEI) confirms that the nonleaf particle consists of mineral material. (c) An aluminium map identifies this as an Al-rich particle. (d) Energy dispersive spectrometry (EDS) reveals multielement analysis which indicates that the particle is probably a feldspar.
particles being smaller for the tea leaves than that for either the tomato leaves or the citrus leaves. The total area of all the Al-rich particles was calculated as a percentage of the total area of the sample. This area was 0.155% for the tomato leaves, 0.027% for the citrus leaves, and 0.020% for the tea leaves (Table 3). In the second stage of the EPMA, 10 Al-rich particles from each sample were identified by multielement energy dispersive analysis (e.g., Fig. 1d). For the tomato leaves, all 10 particles approximated to a feldspar composition, presumably from soil contamination, with approximately 65% SiO2, 20% Al2O3 and variable amounts of Na2O (<8%), K2O (<15%) or Ca (<8%). For the citrus leaves and the tea leaves, the particles that were Al-rich were also rich predominantly in Ca (<8%) and K2O (75%) rather than SiO2 (9%) and Al2O3 (10%) (8% for the tea leaves), and were therefore probably not predominantly of aluminosilicate composition (Figs. 2d and 3d). The proportion by area (S1/S2) occupied by the high aluminium particles was used as an estimate of their proportion by volume (v1/v2). This approximation was considered justified for this semiquantitative application. The mass fraction (m1/m2) contributed by the particles was then estimated from the density (p) using the equation p 4 m/v
(1)
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FIG. 2. Nonleaf particle in one field of view for a sample of NIST citrus leaves (SRM 1572) (a) A suspect nonleaf particle found on the citrus leaves by secondary electron image (SEI). (b) A backscattered electron image (BEI) confirms that the nonleaf particle consists of mineral material. (c) An aluminium map shows that none of the nonleaf particles in this field of view are Al-rich, using energy dispersive spectrometry (EDS) mode. (d) A calcium map shows that the nonleaf particles in this field of view are Ca-rich.
and hence m1/m2 4 v1/v2 2 p1/p2.
(2)
The densities of the SRMs were estimated approximately (±10%) by weighing compacted powders, which were 0.70 g cm-3 for the tomato leaves and the citrus leaves, and 0.75 g cm-3 for the tea leaves. The density of the particles was assumed to be approximately that of feldspar, which was 2.60 g cm-3. The aluminium concentrations contributed by soil/dust particles were then calculated by application of the equation [Al] (mg g−1) 4
s (Al–rich particles) × 2.60 2 C, s (total) × p (leaves)
(3)
where C is the mean aluminium concentration of the Al-rich particles. There was a broad agreement found between the estimated aluminium contributed by the soil particles on the tomato leaves (600 mg g-1) and the shortfall between the certified aluminium value and that found in the acid decomposition (697 mg g-1) (by nitric and perchloric acid). Although the former estimate is only semiquantitative it does suggest that
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FIG. 3. Nonleaf particle in one field of view for a sample of NIES tea leaves (CRM 7). (a) A suspect nonleaf particle found on the tea leaves by secondary electron image (SEI). (b) A backscattered electron image (BEI) confirms that the nonleaf particle consists of mineral material. (c) An aluminium map shows that none of the nonleaf particles in this field of view are Al-rich, using energy dispersive spectrometry (EDS) mode. (d) A calcium map shows that the nonleaf particles in this field of view are Ca-rich.
soil contamination is responsible for the “missing” aluminium and that this aluminium was not solubilized extensively by the mixture of nitric and perchloric acids. In the cases of the citrus leaves and the tea leaves, a relatively small amounts of aluminium were estimated to be contributed by the particles (60 and 30 mg g-1, respectively). Comparisons of these with the differences in aluminium concentrations found between two acid attack procedures (17.7 and 32.2 mg g-1, respectively), suggest that the citrus leaves and the tea leaves were less contaminated by soil/dust particles than were the tomato leaves. The comparative significance of the aluminium contributed by soil/dust particles adhering to the leaf surface is given in Table 4. 3. Examination of Soil/Dust Particles on the Surface of Soybean Plant Materials A number of nonleaf particles were also found on selected sample of both the soybean leaves (Fig. 6) and the beans. The same procedures that have been used to classify the particles in the SRMs were employed for the soybean plant materials. The classified characteristics of the particles are given in Table 5, and the results of semiquantitative analysis of Al-rich particles by EMPA are listed in Table 6.
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FIG. 4. A comparison of the distribution of Al-rich particles with different percentages of Al2O3. (a) NIST tomato leaves, (b) NIST citrus leaves, and (c) NIES tea leaves.
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FIG. 5. Distributions of particle sizes (by area) of Al-rich particles for the SRMs. (a) NIST tomato leaves, (b) NIST citrus leaves, and (c) NIES tea leaves.
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DETERMINATION OF ALUMINIUM IN PLANT MATERIALS TABLE 3 Particles Found on the SRM Samples Sample Tomato leaf NIST 1573 Total particles found Particles with Al2O3 > 5% Percentage by area occupied by total particles Percentage by area occupied by particles with Al2O3 > 5%
1813 121
Citrus leaf NIST 1572 317 38
Tea leaf NIES No. 7 587 451
1.360
0.620
0.033
0.155
0.027
0.020
The results show that small amounts of aluminium (generally <20 mg g-1) were contributed by the particles to the total aluminium in the plant materials, except of the sample named Leaf-3. A large number of Al-rich particles were found in this sample compared with other soybean leaves and beans. The estimated aluminium concentration from the soil/dust particles on this sample (Leaf-3) was 95 mg g-1. However, for other soybean leaves and beans the estimated aluminium concentrations contributed by soil/dust particles were less than 20 mg g-1. The results suggest that soil/dust contamination is responsible for the difference in the aluminium concentrations of the soybean plant materials found between the two types of acid attack listed in Table 2. Compared with particles found on the SRMs, the characteristics of the particles found on the soybean plant materials were very similar to those found on the tea leaves, both in the particle size distributions and in percentage (by mass) of the aluminium concentration TABLE 4 Result of Semiquantitative Analysis of Al-Rich Particles for the SRM Samples Sample Tomato leaf NIST 1573 Percentage by area of Al-rich particles Percentage by mass of Al-rich particles Estimated particle density (g cm−3) Approximate percentage by weight of Al content of Al-rich particles Estimated Al concentration (mg g−1) contributed by Al-rich particles to the total Al in the material Shortfall in Al between acid attack and certified value (mg) g−1)
Citrus leaf NIST 1572
Tea leaf NIES No. 7
0.155
0.027
0.020
0.576
0.100
0.069
0.70
0.70
0.75
10
6
4
600
60
30
697
29
65
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DEMING DONG TABLE 5 Particles Found on Soybean Plant Materials from Pot Trials Sample Leaf-3
Total Particles found Particles with Al2O3 > 5% Particles with Al2O3 > 5% and size within 0.8–1.2 um2 Percentage by area occupied by total particles Percentage by area occupied by particles with Al2O3
Leaf-26
Leaf-33
Bean-7
Bean-28
2318
347
181
346
764
662
94
57
146
212
654
94
57
146
212
0.154
0.026
0.019
0.019
0.059
0.074
0.017
0.014
0.014
0.021
in the Al-rich particles. In both soybean plant materials and the tea leaves, more than 99% of the particles found were very fine particles ranging from 0.8 to 1.2 mm2 (Table 5 and Fig. 5c), and have an approximate aluminium concentration of 3.5–4% in the Al-rich particles. This suggests that the Al-rich particles on both the tea leaves and the soybean plant materials could be from similar sources (1). CONCLUSIONS Low recoveries of aluminium estimated using NIST tomato leaves (SRM 1573) do not imply a negative bias for the analytical method for the determination of Al in vegetation. TABLE 6 Result of Semiquantitative Analysis of Al-Rich Particles on Soybean Plant Materials Sample
Percentage by area of Al-rich particles Estimated particle density (g cm−3) Percentage by mass of Al-rich particles Approximate percentage by weight of Al content of Al-rich particles Estimated Al concentration (mg g−1) contributed by Al-rich particles Difference in Al found between two acid attacks (mg g−1)
Leaf-3
Leaf-26
Leaf-33
Bean-7
Bean-28
0.074
0.017
0.014
0.014
0.021
0.70
0.70
0.70
1.10
1.10
0.275
0.063
0.052
0.033
0.050
3.5
3.5
3.5
3.5
3.5
95
26
20
2.5
15
4.2
10
1.3
15
0.5
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FIG. 6. Nonleaf particle in one field of view for a sample of soybean leaves. (a) A suspect nonleaf particle found on the soybean leaves by secondary electron image (SEI). (b) A backscattered electron image (BEI) confirms that the nonleaf particle consists of mineral material. (c) An aluminium map shows that none of the nonleaf particles in this field of view are Al-rich, using energy dispersive spectrometry (EDS) mode. (d) A calcium map shows that the nonleaf particles in this field of view are Ca-rich.
This is because the acid decomposition of vegetation (using HNO3–HCIO4) is selective in dissolving the aluminium present in the vegetation, but only a small fraction of that present in the soil/dust particles contaminating the surface of the vegetation. A sample decomposition capable of solubilizing all the aluminium in this reference material does so by decomposing both the vegetation and the soil contamination by a mixture of nitric, perchloric, and hydrofluoric acids. Electron probe micro analysis (EPMA) allows the extent of soil contamination of vegetation samples to be estimated. The combination of EPMA and ICP–AES offers the possibility of determining the sources of the aluminium in the vegetation samples, particularly that contributed by the soil/dust particles. In particular, this approach allows the semiquantitative determination of aluminium in soil/dust particles that are present as contamination on the surface of plant materials. This will be equally applicable to the estimation of contamination by both the soil originating in the process of field sampling and the dust from the laboratory environment. REFERENCES 1. Coe, J. M.; Lindberg, S. E. J.A.P.C.A., 1987, 37, 237–243.
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2. Delves, H. T.; Suchak, B.; Fellows, C. S. in Aluminium in Food and the Environment (Massey R.C. and Taylor, D. Eds.), pp. 52–67. Royal Society of Chemistry, London, 1989. 3. Fortmann, R. C.; Johnson, D. L. Environ. Pollut. Ser. B, 1984, 7, 297–316. 4. Fortmann, R. C.; Johnson, D. L. Environ. Pollut. Ser. B, 1984, 8, 1–16. 5. Heasman, I.; Watt, J. Environ. Geochem. Health, 1989, 11(3/4), 157–162. 6. Jones, K. C.; Bennett, B. G. Sci. Total Environ., 1986, 52, 65–82. 7. Pierson, K. B.; Evenson, M. A. Anal. Chem., 1986, 58, 1744–1748. 8. Ramsey, M. H.; Dong, D.; Thornton, I.; Watt, J.; Giddens, R. Environ. Geochem. Health, 1991, 13(2), 114–118. 9. Ramsey, M. H.; Thompson, M. J. Anal. Atomic Spectrom., 1987, 2, 497–502. 10. Thompson, M.; Wood, S. In Atomic Absorption Spectrometry (E. J. Cantle, Ed.), pp. 261–284. Elsevier, Amsterdam, 1982. 11. Watt, J. Microsc. Anal., 1990, 15, 25–28.
MICROCHEMICAL JOURNAL ARTICLE NO. 0049
53, 337–348 (1996)
Investigation of the Discrimination between Aluminium Held within Vegetation and That Contributed by Soil Contamination Using ICP–AES and EPMA DEMING DONG Department of Environmental Science, Jilin University, 75 Jiefang Road, Changchun, People’s Republic of China 130023 The difficulties in the accurate determination of aluminium in plant materials have been known for a long time. A major problem is caused by aluminium contamination from soil/dust particles adhering to the vegetation. In this methodological approach, a combination of two analytical techniques [electron probe micro analysis (EPMA) and inductively coupled plasma–atomic emission spectrometry (ICP–AES)] was employed to investigate the aluminium held within vegetation and that contributed by soil/dust contamination. Aluminium concentrations in NIST (formally NBS) Certified Reference Material tomato leaves (SRM 1573) and citrus leaves (SRM 1572) and NIES Certified Reference Material tea leaves (NIES No.7) were determined by ICP–AES after acid digestion. The normal “total” acid attack (nitric and perchloric acids) gave a very low recovery of aluminium in tomato leaves (41.9%) compared with the provisional value quoted by NIST. The aluminium concentrations measured for the citrus leaves and tea leaves were much closer to the certified values. The contribution of aluminium from Al-rich soil/dust particles in these reference materials was estimated semiquantitatively by computer-controlled EPMA. The aluminium held in these particles corresponded in approximate concentration to the shortfall between the acid soluble component determined in this study and the certified value. Analysis by EPMA can provide, therefore, a method of estimating aluminium contributed by soil contamination to plant materials. The limitation of the Standard Reference Materials for the validation of methods for the determination of aluminium in vegetation are demonstrated. © 1996 Academic Press, Inc.
INTRODUCTION The difficulties in the accurate determination of aluminium in plant materials have been discussed over the past several years. A major problem is caused by aluminium contamination from soil/dust particles adhering to the vegetation (6,2,7). Fortmann and Johnson (3,4) and Coe and Lindbery (1) used scanning electron microscopy (SEM) to characterize individual particles and to determine the particle size distributions on foliage of plants. In this study, a combination of two analytical techniques [electron probe micro analysis (EPMA) and inductively coupled plasma–atomic emission spectrometry (ICP–AES)] was employed to investigate the aluminium held within vegetation and that contributed by soil/dust contamination. Some of the results have been published (8). MATERIALS AND METHODS National Institute of Standards and Technology, U.S.A. (NIST) Certified Reference Material tomato leaves (SRM 1573) and citrus leaves (SRM 1572), and National Institute for Environmental Studies, Japan (NIES) Certified Reference Material tea leaves (NIES No.7) were used in this methodological approach. Some of the soybean leaves and beans grown in the greenhouse pot trials were also examined using this method to verify if there were any soil/dust contamination to the samples. The reference materials and the soybean 337 0026-265X/96 $18.00 Copyright © 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.
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samples were dried overnight in an oven at 85°C prior to use. Dried samples were weighed (2 g) into clean Teflon tubes, with 20 ml fuming nitric acid (95% w/w). The tubes were placed into a heating block for 10 h at 150°C. After the bulk of the sample was dissolved, 3.0 ml perchloric acid (60% w/w) was added. The tubes were heated for another 18 h at 150°C, taken to dryness at 190°C, and leached by adding hydrochloric acid at 70°C. For the purposes of comparition, certain samples were treated with hydrofluoric acid (5 ml, 40% w/w) and further nitric (2 ml, 70% w/w) and perchloric acids (1 ml) prior to leaching with hydrochloric acid (10, 8). The ICP–AES instrumentation used was an ARL-34000C, 1-M vacuum spectrometer with PDP 11/04 computer. The wavelength used was 308.2 nm. The relevant instrumental conditions for the determination of Al by ICP–AES has been described by Ramsey and Thompson (9). In order to examine and analyse individual particles by EPMA, the dry leaf material was mounted onto a clean glass slide and vacuum coated with carbon. The EPMA utilized a JEOL 733 superprobe electron microscope with attached Link Analytical AN10000 data handling system. During the scanning electron microscopy (SEM), secondary electron images and backscattered electron images were taken for each sample. This allowed any mineral material to be recognized visually. Seventy-five fields (0.262 mm2 each), which were spaced at equal intervals, and a large number of mineral particles were examined in backscattered electron mode with the detector set to discriminate against material of low atomic number (i.e., the leaf mass). The mineral particles were then analysed semiquantitatively using energy dispersive spectroscopy (EDS) and classified according to their aluminium concentrations. The area occupied by the particles were measured automatically using the link analytical feature detection and classification program called Digiscan (11, 5). Finally, the aluminium concentrations contributed from soil/dust contamination to the total aluminium concentrations in the plant materials were estimated semiquantitatively. RESULTS AND DISCUSSION 1. Concentrations of Aluminium in Vegetation Samples The normal “total” nitric and perchloric acid attack gave a very low recovery of aluminium in tomato leaves (41.9%) compared with the provisional value quoted by NIST. Similar low results have been reported by Pierson and Evenson (7). The aluminium concentrations measured for the citrus leaves and tea leaves were much closer to the certified values (Table 1). The recovery of aluminium was 68.4 and 91.6%, respectively. When hydrofluoric acid was added to the digestion mixture, the aluminium concentrations found were close to the certified values in both cases. This validates the accuracy of the ICP–AES determination and shows that neither the digestion method nor instrumental bias was the cause of the low recovery of aluminium when decomposed without hydrofluoric acid. Only for one sample of the soybean leaves was there a big difference found in the aluminium concentrations obtained between the digestion of nitric/perchloric acid with and without hydrofluoric acid. For the other soybean leaves and beans there were not significant difference found between the two procedures of acid digestion. The results are given in Table 2.
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DETERMINATION OF ALUMINIUM IN PLANT MATERIALS TABLE 1 Concentrations of Aluminium in Leaf Materials Using Two Different Acid Decompositions Prior to Determination by ICP–AES (mg g−1) Sample Tomato leaf SRM 1573 Certified Value 1200a Nitric and perchloric acid digestion n 22 Mean 502.7 s 20.8 Recovery (%) 41.9 Nitric, perchloric, and hydrofluoric acid digestion n 13 Mean 1220.7 s 53.3 Recovery (%) 101.7 a
Citrus leaf SRM 1572
Tea leaf CRM 7
92 ± 15
775 ± 20
22 62.9 3.4 68.4
10 710.2 20.1 91.6
13 80.6 4.2 87.6
7 742.4 19.5 95.8
Provisional value.
2. Aluminium Contamination from Soil/Dust Particles Adhering to the Standard Reference Materials Scanning electron microscopy (SEM) was used to identify the nonleaf particles in samples (Figs. 1–3). Electron probe micro analysis (EPMA) was then carried out in two stages. Initial semiquantitative aluminium analysis of all the nonleaf particles in a fixed area revealed that there was a fraction that contained significantly high concentrations (>2.7% Al or >5% Al2O3). For the tomato leaves, 121 Al-rich particles were identified (6.7% of the total particles), and for the citrus leaves and the tea leaves there were 38 (12.0%) and 451 (76.8%) Al-rich particles, respectively. However, there was a marked difference in the distributions of aluminium concentrations of the Al-rich particles for these reference materials (Fig. 4). The proportions of the particles with high aluminium concentrations for the tomato leaves and citrus leaves were much higher than that for the tea leaves where 83% of particles were less than 10% Al2O3. The area of each Al-rich particle ranged from 1 to 20 mm2 for the tomato leaves and the citrus leaves, but that was less than 2 mm2 for the 99% of Al-rich particles on the tea leaves (Fig. 5). This resulted in the total area occupied by the Al-rich TABLE 2 Concentrationsa of Aluminium in Selected Soybean Leaves and Beans Using Two Different Acid Decompositions Prior to Determination by ICP–AES (mg g−1) Sample
Digested by HNO3 + HClO4 Digested by HNO3 + HClO4 + HF Difference a
Leaf-3
Leaf-26
Leaf-33
Bean-7
Bean-28
548.0 574.0 26.0
25.0 27.5 2.5
70.8 75.0 4.2
2.0 3.3 1.3
2.5 2.0 −0.5
The data in this table have a precision of < ± 10%, tested by the method of Thompson and Howarth.
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FIG. 1. Aluminium-rich particles in one field of view for a sample of NIST tomato leaves (SRM 1573). (a) A suspect nonleaf particle found on the tomato leaves by secondary electron image (SEI). (b) A backscattered electron image (BEI) confirms that the nonleaf particle consists of mineral material. (c) An aluminium map identifies this as an Al-rich particle. (d) Energy dispersive spectrometry (EDS) reveals multielement analysis which indicates that the particle is probably a feldspar.
particles being smaller for the tea leaves than that for either the tomato leaves or the citrus leaves. The total area of all the Al-rich particles was calculated as a percentage of the total area of the sample. This area was 0.155% for the tomato leaves, 0.027% for the citrus leaves, and 0.020% for the tea leaves (Table 3). In the second stage of the EPMA, 10 Al-rich particles from each sample were identified by multielement energy dispersive analysis (e.g., Fig. 1d). For the tomato leaves, all 10 particles approximated to a feldspar composition, presumably from soil contamination, with approximately 65% SiO2, 20% Al2O3 and variable amounts of Na2O (<8%), K2O (<15%) or Ca (<8%). For the citrus leaves and the tea leaves, the particles that were Al-rich were also rich predominantly in Ca (<8%) and K2O (75%) rather than SiO2 (9%) and Al2O3 (10%) (8% for the tea leaves), and were therefore probably not predominantly of aluminosilicate composition (Figs. 2d and 3d). The proportion by area (S1/S2) occupied by the high aluminium particles was used as an estimate of their proportion by volume (v1/v2). This approximation was considered justified for this semiquantitative application. The mass fraction (m1/m2) contributed by the particles was then estimated from the density (p) using the equation p 4 m/v
(1)
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FIG. 2. Nonleaf particle in one field of view for a sample of NIST citrus leaves (SRM 1572) (a) A suspect nonleaf particle found on the citrus leaves by secondary electron image (SEI). (b) A backscattered electron image (BEI) confirms that the nonleaf particle consists of mineral material. (c) An aluminium map shows that none of the nonleaf particles in this field of view are Al-rich, using energy dispersive spectrometry (EDS) mode. (d) A calcium map shows that the nonleaf particles in this field of view are Ca-rich.
and hence m1/m2 4 v1/v2 2 p1/p2.
(2)
The densities of the SRMs were estimated approximately (±10%) by weighing compacted powders, which were 0.70 g cm-3 for the tomato leaves and the citrus leaves, and 0.75 g cm-3 for the tea leaves. The density of the particles was assumed to be approximately that of feldspar, which was 2.60 g cm-3. The aluminium concentrations contributed by soil/dust particles were then calculated by application of the equation [Al] (mg g−1) 4
s (Al–rich particles) × 2.60 2 C, s (total) × p (leaves)
(3)
where C is the mean aluminium concentration of the Al-rich particles. There was a broad agreement found between the estimated aluminium contributed by the soil particles on the tomato leaves (600 mg g-1) and the shortfall between the certified aluminium value and that found in the acid decomposition (697 mg g-1) (by nitric and perchloric acid). Although the former estimate is only semiquantitative it does suggest that
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FIG. 3. Nonleaf particle in one field of view for a sample of NIES tea leaves (CRM 7). (a) A suspect nonleaf particle found on the tea leaves by secondary electron image (SEI). (b) A backscattered electron image (BEI) confirms that the nonleaf particle consists of mineral material. (c) An aluminium map shows that none of the nonleaf particles in this field of view are Al-rich, using energy dispersive spectrometry (EDS) mode. (d) A calcium map shows that the nonleaf particles in this field of view are Ca-rich.
soil contamination is responsible for the “missing” aluminium and that this aluminium was not solubilized extensively by the mixture of nitric and perchloric acids. In the cases of the citrus leaves and the tea leaves, a relatively small amounts of aluminium were estimated to be contributed by the particles (60 and 30 mg g-1, respectively). Comparisons of these with the differences in aluminium concentrations found between two acid attack procedures (17.7 and 32.2 mg g-1, respectively), suggest that the citrus leaves and the tea leaves were less contaminated by soil/dust particles than were the tomato leaves. The comparative significance of the aluminium contributed by soil/dust particles adhering to the leaf surface is given in Table 4. 3. Examination of Soil/Dust Particles on the Surface of Soybean Plant Materials A number of nonleaf particles were also found on selected sample of both the soybean leaves (Fig. 6) and the beans. The same procedures that have been used to classify the particles in the SRMs were employed for the soybean plant materials. The classified characteristics of the particles are given in Table 5, and the results of semiquantitative analysis of Al-rich particles by EMPA are listed in Table 6.
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FIG. 4. A comparison of the distribution of Al-rich particles with different percentages of Al2O3. (a) NIST tomato leaves, (b) NIST citrus leaves, and (c) NIES tea leaves.
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FIG. 5. Distributions of particle sizes (by area) of Al-rich particles for the SRMs. (a) NIST tomato leaves, (b) NIST citrus leaves, and (c) NIES tea leaves.
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DETERMINATION OF ALUMINIUM IN PLANT MATERIALS TABLE 3 Particles Found on the SRM Samples Sample Tomato leaf NIST 1573 Total particles found Particles with Al2O3 > 5% Percentage by area occupied by total particles Percentage by area occupied by particles with Al2O3 > 5%
1813 121
Citrus leaf NIST 1572 317 38
Tea leaf NIES No. 7 587 451
1.360
0.620
0.033
0.155
0.027
0.020
The results show that small amounts of aluminium (generally <20 mg g-1) were contributed by the particles to the total aluminium in the plant materials, except of the sample named Leaf-3. A large number of Al-rich particles were found in this sample compared with other soybean leaves and beans. The estimated aluminium concentration from the soil/dust particles on this sample (Leaf-3) was 95 mg g-1. However, for other soybean leaves and beans the estimated aluminium concentrations contributed by soil/dust particles were less than 20 mg g-1. The results suggest that soil/dust contamination is responsible for the difference in the aluminium concentrations of the soybean plant materials found between the two types of acid attack listed in Table 2. Compared with particles found on the SRMs, the characteristics of the particles found on the soybean plant materials were very similar to those found on the tea leaves, both in the particle size distributions and in percentage (by mass) of the aluminium concentration TABLE 4 Result of Semiquantitative Analysis of Al-Rich Particles for the SRM Samples Sample Tomato leaf NIST 1573 Percentage by area of Al-rich particles Percentage by mass of Al-rich particles Estimated particle density (g cm−3) Approximate percentage by weight of Al content of Al-rich particles Estimated Al concentration (mg g−1) contributed by Al-rich particles to the total Al in the material Shortfall in Al between acid attack and certified value (mg) g−1)
Citrus leaf NIST 1572
Tea leaf NIES No. 7
0.155
0.027
0.020
0.576
0.100
0.069
0.70
0.70
0.75
10
6
4
600
60
30
697
29
65
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DEMING DONG TABLE 5 Particles Found on Soybean Plant Materials from Pot Trials Sample Leaf-3
Total Particles found Particles with Al2O3 > 5% Particles with Al2O3 > 5% and size within 0.8–1.2 um2 Percentage by area occupied by total particles Percentage by area occupied by particles with Al2O3
Leaf-26
Leaf-33
Bean-7
Bean-28
2318
347
181
346
764
662
94
57
146
212
654
94
57
146
212
0.154
0.026
0.019
0.019
0.059
0.074
0.017
0.014
0.014
0.021
in the Al-rich particles. In both soybean plant materials and the tea leaves, more than 99% of the particles found were very fine particles ranging from 0.8 to 1.2 mm2 (Table 5 and Fig. 5c), and have an approximate aluminium concentration of 3.5–4% in the Al-rich particles. This suggests that the Al-rich particles on both the tea leaves and the soybean plant materials could be from similar sources (1). CONCLUSIONS Low recoveries of aluminium estimated using NIST tomato leaves (SRM 1573) do not imply a negative bias for the analytical method for the determination of Al in vegetation. TABLE 6 Result of Semiquantitative Analysis of Al-Rich Particles on Soybean Plant Materials Sample
Percentage by area of Al-rich particles Estimated particle density (g cm−3) Percentage by mass of Al-rich particles Approximate percentage by weight of Al content of Al-rich particles Estimated Al concentration (mg g−1) contributed by Al-rich particles Difference in Al found between two acid attacks (mg g−1)
Leaf-3
Leaf-26
Leaf-33
Bean-7
Bean-28
0.074
0.017
0.014
0.014
0.021
0.70
0.70
0.70
1.10
1.10
0.275
0.063
0.052
0.033
0.050
3.5
3.5
3.5
3.5
3.5
95
26
20
2.5
15
4.2
10
1.3
15
0.5
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FIG. 6. Nonleaf particle in one field of view for a sample of soybean leaves. (a) A suspect nonleaf particle found on the soybean leaves by secondary electron image (SEI). (b) A backscattered electron image (BEI) confirms that the nonleaf particle consists of mineral material. (c) An aluminium map shows that none of the nonleaf particles in this field of view are Al-rich, using energy dispersive spectrometry (EDS) mode. (d) A calcium map shows that the nonleaf particles in this field of view are Ca-rich.
This is because the acid decomposition of vegetation (using HNO3–HCIO4) is selective in dissolving the aluminium present in the vegetation, but only a small fraction of that present in the soil/dust particles contaminating the surface of the vegetation. A sample decomposition capable of solubilizing all the aluminium in this reference material does so by decomposing both the vegetation and the soil contamination by a mixture of nitric, perchloric, and hydrofluoric acids. Electron probe micro analysis (EPMA) allows the extent of soil contamination of vegetation samples to be estimated. The combination of EPMA and ICP–AES offers the possibility of determining the sources of the aluminium in the vegetation samples, particularly that contributed by the soil/dust particles. In particular, this approach allows the semiquantitative determination of aluminium in soil/dust particles that are present as contamination on the surface of plant materials. This will be equally applicable to the estimation of contamination by both the soil originating in the process of field sampling and the dust from the laboratory environment. REFERENCES 1. Coe, J. M.; Lindberg, S. E. J.A.P.C.A., 1987, 37, 237–243.
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2. Delves, H. T.; Suchak, B.; Fellows, C. S. in Aluminium in Food and the Environment (Massey R.C. and Taylor, D. Eds.), pp. 52–67. Royal Society of Chemistry, London, 1989. 3. Fortmann, R. C.; Johnson, D. L. Environ. Pollut. Ser. B, 1984, 7, 297–316. 4. Fortmann, R. C.; Johnson, D. L. Environ. Pollut. Ser. B, 1984, 8, 1–16. 5. Heasman, I.; Watt, J. Environ. Geochem. Health, 1989, 11(3/4), 157–162. 6. Jones, K. C.; Bennett, B. G. Sci. Total Environ., 1986, 52, 65–82. 7. Pierson, K. B.; Evenson, M. A. Anal. Chem., 1986, 58, 1744–1748. 8. Ramsey, M. H.; Dong, D.; Thornton, I.; Watt, J.; Giddens, R. Environ. Geochem. Health, 1991, 13(2), 114–118. 9. Ramsey, M. H.; Thompson, M. J. Anal. Atomic Spectrom., 1987, 2, 497–502. 10. Thompson, M.; Wood, S. In Atomic Absorption Spectrometry (E. J. Cantle, Ed.), pp. 261–284. Elsevier, Amsterdam, 1982. 11. Watt, J. Microsc. Anal., 1990, 15, 25–28.