Solid phase associations, oceanic fluxes and the anthropogenic perturbation of transition metals in world river particulates

Solid phase associations, oceanic fluxes and the anthropogenic perturbation of transition metals in world river particulates

Marine Chemistry 72 Ž2000. 17–31 www.elsevier.nlrlocatermarchem Solid phase associations, oceanic fluxes and the anthropogenic perturbation of transi...

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Marine Chemistry 72 Ž2000. 17–31 www.elsevier.nlrlocatermarchem

Solid phase associations, oceanic fluxes and the anthropogenic perturbation of transition metals in world river particulates Simon W. Poulton, Robert Raiswell ) Department of Earth Sciences, Leeds UniÕersity, Leeds LS2 9JT, UK Received 18 October 1999; received in revised form 23 May 2000; accepted 26 May 2000

Abstract The solid phase associations of particulate Mn, Cu, Ni, Co, Cr and Zn in eight world rivers Žrepresenting 19% of the global sediment flux. have been determined in order to estimate the fluxes and sources of particulate transition metals in different phases on a global scale. A sequential extraction procedure measured the metals progressively dissolved by dithionite, concentrated HCl, and HF–HClO4 –HNO 3 reflecting decreasing availability in surface environments. The combined evaluation of phase associations, enrichment factors and theoretical and observed flux ratios highlight the differing sources for these elements in river particulates. Zn appears to be significantly affected by pollutant inputs on a global scale, with total fluxes that may have doubled relative to natural background concentrations. By contrast, riverine particulate Mn and Cu appear to be relatively unaffected by anthropogenic perturbations. The Cu contents of river particulates are high relative to the average Cu contents of surficial sediments, and in general, this probably arises due to geochemical fractionation in the soil column or differential weathering processes. However localised pollution may produce exceedingly high Cu levels associated with organic or sulphide phases. Cr and Ni show no clear evidence of significant pollutant contributions, but Co has somewhat enhanced enrichment factors and flux ratios which may be indicative of anthropogenic additions. q 2000 Elsevier Science B.V. All rights reserved. Keywords: River particulates; Transition metals; Phase associations

1. Introduction Globally integrated studies of the trace element contents of river particulates can provide valuable insights into continental-scale weathering processes, oceanic sediment sources and sinks, and the anthropogenic perturbation of trace element cycles. Martin and Meybeck Ž1979. provided the first comprehen)

Corresponding author. Fax: q44-1132-335-259. E-mail addresses: [email protected] ŽS.W. Poulton., [email protected] ŽR. Raiswell..

sive survey of river particulate composition, covering more than 40 major, minor and trace elements in 22 rivers representing approximately 15% of the global river particulate supply. Other studies have supplied additional data relating to the total element concentrations of major world rivers Že.g. Eisma et al., 1978; Presley et al., 1980; Emeis, 1985; Trefrey et al., 1986; Zhang, 1988; Huang and Zhang, 1990; Huang et al., 1992., and the average elemental compositions of world river particulates are now relatively well-known ŽMartin and Gordeev, 1982; Martin and Meybeck, 1979; Martin and Whitfield, 1983..

0304-4203r00r$ - see front matter q 2000 Elsevier Science B.V. All rights reserved. PII: S 0 3 0 4 - 4 2 0 3 Ž 0 0 . 0 0 0 6 0 - 8

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S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

Hence attention is now being directed towards obtaining information on the phase associations of trace elements, because trace elements held in lattice positions in crystalline minerals are believed to be less bioavailable Žand less likely to be extracted into the aqueous phase. than those which are held in nonlattice sites Ži.e. adsorbed, or associated with mineral coatings, carbonates and organic material.. Furthermore, trace elements added by anthropogenic processes mainly occur in nonlattice sites ŽSalomons and Forstner, 1980, 1984.. Unfortunately, it is difficult to compare trace element phase association data from the literature because individual studies on different rivers have used a variety of extraction techniques, making it difficult to establish any general patterns of behaviour. It is the purpose of this study to produce internally consistent data for the phase associations of Mn, Co, Cu, Zn, Ni and Cr in particulate matter harvested from a suite of major world rivers. These metals have been chosen because observations based on total concentrations in river particulates suggest that their principal sources differ on a global scale ŽMartin and Meybeck, 1979; Martin and Whitfield,1983.. However, further insight into the sources of these elements in sediments supplied to the oceans may be obtained by consideration of their phase associations. Thus the data presented here will be used to examine the relative importance of weathering processes and anthropogenic activities on the trace element cycles of Mn, Co, Cu, Zn, Ni and Cr on a global scale.

2. Sampling and analytical methodology Sediments were collected from the rivers Amazon, Huanghe, Changjiang, Magdalena, Colorado, Nile, Brahmaputra and Burdekin ŽFig. 1., which represent geographically diverse regions with average climatological characteristics that vary considerably between individual drainage basins ŽTable 1.. This data-set includes four of the five most important world rivers, in terms of annual sediment load, and represents approximately 19% of the total riverine sediment flux to the oceans ŽMilliman and Syvitski, 1992.. Temporal variations in river suspended sediment compositions may be particularly large for trace elements, and in all cases rivers were sampled on only one occasion by colleagues with access to suitable sampling localities. Samples were collected from the midpoint of the main channel at approximately 1 m depth, at various times from 1996 to 1997 ŽTable 2.. This approach does not constrain seasonal and spatial variability Žwhich would require multiple sampling events.. However, trace-element variations between rivers tend to be far higher than those found for repeat analyses of sediment from a single river ŽKonovalov and Ivanova, 1970; Martin and Meybeck, 1979.. Thus single sampling episodes can provide a first approximation of the trace element concentrations of suspended particulates. In order to minimise the effects of unrepresentative sample collection, sufficient volumes of water were sampled to allow the collection and subsequent anal-

Fig. 1. Localities of rivers surveyed and sampling points Žleft to right on rivers Colorado, Magdalena, Amazon, Nile, Brahmaputra, Huanghe, Changjiang and Burdekin..

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

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Table 1 Drainage basin characteristics Žafter Milliman and Syvitski, 1992. River

Basin area Ž10 6 km2 .

Annual Sediment Load Ž10 6 tryear.

Percentage of global riverine sediment flux

Classification

Amazon Huanghe Brahmaputra Changjiang Magdalena Nile Colorado ŽUSA. Burdekin

6.1 0.77 0.61 1.9 0.24 3.0 0.63 0.13

1200 1100 540 480 220 120 120 3

6 5.5 2.7 2.4 1.1 0.6 0.6 0.02

Tropical-wet Temperate-dry Tropical-wet Temperate-wet Tropical-wet Tropical-dry Temperate-dry Tropical-sub humid

ysis of several grams of sediment from each river. This approach produces total element data that generally agree well with previous studies Žsee later., and hence our consistency in analytical methodology does allow some useful comparisons to be drawn between different rivers on a global scale. Suspended particulates were pressure-filtered through either 0.40 mm polycarbonate filters or 0.45 mm nitrocellulose filters, then air-dried and removed from the filters using a scalpel. Unfortunately suspended particulates for the Amazon and Nile rivers could not be obtained. Instead, bed sediments were grain-size separated and an appropriate size fraction selected to represent the sediment transported in suspension. Gibbs Ž1967. states that the average particle size in the Amazon varies with the concentration of suspended sediment; however, the mean particle diameter is - 2 mm at the lower concentrations Ž- 30 ppm. characteristic of normal, nonflood conditions. Hence the - 2 mm fraction was chosen for the Amazon. We will show later that our analyses for this fraction, in terms of both the total metal contents and their phase associations, are in good agreement with the suspended sediment analyses of Gibbs Ž1973, 1977.. The - 20 mm fraction was chosen for the Nile because this fraction represents more than 85% of the sediment discharged, and the remaining larger grains mainly represent locally derived biogenic material ŽKrom et al., 1999.. Total trace element concentrations may vary greatly as a function of grain size in river sediments Že.g. Whitney, 1975; Gibbs, 1977; Horowitz and Elrick, 1987., but the present study emphasizes comparative variations in the phase associations of trace elements,

rather than absolute concentrations, and our conclusions should be relatively unaffected by these grain size choices. A variety of sequential extraction procedures have been used to determine the phase associations of metals in sediments Že.g. Chester and Hughes, 1967; Gibbs, 1977; Tessier et al., 1979; Forstner et al., 1981.. These procedures commonly provide a measure of the trace elements associated with five phases Žadsorbed, associated with oxyhydroxides, organic matter or carbonates, or present in residual silicate minerals.. However, organic matter, carbonate and adsorbed phases tend to be relatively insignificant in terms of total transport of transition metals ŽGibbs, 1973, 1977; Zhang et al., 1990; Baruah et al. 1996.. Thus we have adopted a three-stage sequential procedure based on the techniques commonly used to determine the phase associations of iron in sediments Žsee Berner, 1970; Canfield, 1989; Canfield et al., 1992; Raiswell and Canfield, 1998; Raiswell et al., 1994.. Initially the sediments were subjected to a Table 2 Sampling details River

Date sampled Locality

Map reference

Amazon Huanghe Brahmaputra Changjiang Magdalena Nile Colorado Burdekin

July 1996 July 1997 June 1997 July 1997 Jan 1997 April 1996 June 1996 Jan 1996

00802 N, 51802 W X X 37852 N, 118842 E X X 25814 N, 89836 E X X 29844 N, 112824 E X X 07830 N, 73805 W X X 17838 N, 33856 E X X 37856 N, 110822 W X X 19805 S 145841 E

Macapa, Brazil N. China Bangladesh Shishou, China Colombia Atbara, Sudan Arizona, USA N. Queensland, Australia

X

X

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

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buffered sodium dithionite solution ŽpH s 4.8. for 1 h ŽCanfield, 1989; Raiswell et al., 1994.. Subsequently, trace elements were solubilised by a boiling 12 N HCl extraction for 2 min ŽBerner, 1970; Raiswell et al., 1994.. Finally, the remaining trace elements were solubilised using an HF–HClO4 – HNO 3 extraction ŽWalsh, 1980.. Cr, Mn, Co, Ni, Cu, Zn and Fe were analysed by atomic absorption spectroscopy and total Al by ICP-AES on a separate HF–HClO4 –HNO 3 extraction. Data from six replicate extractions ŽTable 3. on an international stream sediment standard ŽSTSD-4. were reproducible to within 0.8–8.8% for the dithionite extraction, 2.4– 9.5% for the hydrochloric-acid-soluble fraction, and 4.2–8.6% for the residual fraction. The sum of the values for the three fractions was within one standard deviation of the certified values ŽTable 3. except for Mn which was unexpectedly low. Sodium dithionite has been shown to dissolve amorphous and crystalline iron oxides Žwith the exception of magnetite; Raiswell et al., 1994., which largely occur in association with the surfaces of solid particles Žsee Whitney, 1975; Gibbs, 1977; Horowitz and Elrick, 1987.. Thus, the dithionite extraction provides a measure of the elements associated with hydroxide coatings, but will additionally remove the generally lower proportions of elements present in exchange sites. The boiling 12 N HCl technique partially attacks some sheet silicate minerals, such as chlorite, nontronite, glauconite and biotite from which 12–40% of their total Fe can be extracted ŽCanfield et al., 1992; Raiswell et al., 1994.. However, this extraction will also remove trace elements associated with hydrolysable organic matter. Froelich Ž1980. showed that dilute acid solubilized 5–15% of the organic C in carbonate-poor sediments, and up to 45% of the

organic C in carbonate-rich, organic C-poor sediments. Hence, it was necessary to determine the efficiency of organic C removal by the stronger 12 N HCl extraction used in the present study. This method removed approximately 40% of the organic C from the stream sediment standard STSD-4, and 10–55% of the organic C found in the suspended samples collected from the Brahmaputra, Magdalena, Nile and Burdekin rivers. The HF–HClO4 –HNO 3 extraction solubilises any remaining elements, which may occur within the crystal structure of residual silicate minerals, in refractory mineral phases, or in association with refractory organic matter phases. Oxidisable Cu Žthat bound to organic matter andror present as sulphides. was measured by the method of Tessier et al. Ž1979. on separate subsamples following pretreatment with dithionite to remove elements in exchange sites and associated with Fe–Mn oxides. In brief, the dithionite residue was treated with 0.02 M HNO 3 and 30% H 2 O 2 Žadjusted to pH 2 with HNO 3 . at 858C. The liberated metals were then complexed in a 0.8 M ammonium acetate solution and analysed relative to a range of standards in a similar matrix by AAS. Organic C analyses were carried out on carbonate-free samples Žafter treatment with 10% HCl at room temperature for 24 h., followed by combustion and measurement as CO 2 by gas chromatography on a Carlo Erba 1106 Element Analyser. The same instrumental technique was also used to measure total S. For convenience, the trace element concentrations associated with each operationally defined fraction are termed Adithionite-solubleB ŽD ., Ahydrochloric-acid-solubleB ŽH., or AresidualB ŽR., and are denoted by the appropriate subscript Že.g. Zn D , Zn H , and Zn R for dithionite-soluble, HCl minus dithion-

Table 3 Reproducibility of analyses in extracted fractions and comparison to international stream sediment standard STSD-4 Fraction

Cr

Mn

Co

Ni

Cu

Zn

Dithionite-soluble HCl-soluble Residual Total Certified total

21.6 " 0.8 Ž3.6. 8.9 " 0.9 Ž9.5. 72 " 5 Ž7.1. 103 " 13 Ž13. 93

519 " 4 Ž0.8. 107 " 6 Ž5.9. 324 " 11 Ž3.2. 950 " 64 Ž6.7. 1520

8.7 " 1.9 Ž6.9. 1.8 " 0.5 Ž9.1. 5.6 " 1.6 Ž8.6. 16 " 2 Ž13. 13

7.0 " 0.9 Ž8.8. 12.5 " 0.6 Ž3.5. 15 " 1 Ž6.0. 34 " 4 Ž12. 30

9.6 " 0.6 Ž5.8. 48 " 1 Ž2.4. 15.2 " 0.7 Ž4.4. 73 " 6 Ž8.2. 65

43 " 3 Ž6.6. 36 " 3 Ž9.0. 38 " 2 Ž4.7. 117 " 14 Ž12. 107

Values given as mean " 1 s.d. Žin ppm., figures in brackets represent the relative standard deviation.

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

ite-soluble, and HFrHClO4rHNO 3 minus HCl-soluble Zn respectively.. 3. Results Major and trace element data are reported in Table 4. Concentrations of Cr, Co, and Cu in Amazon river sediments and Cr in Changjiang sediments were considered too close to detection limits to be reliable, and are thus not reported. Our reliance on single sampling events necessitates that our data are validated prior to interpretation. Table 5 therefore compares our total element data with literature analyses of river particulates from the Amazon, Huanghe, Changjiang, Magdalena, Nile and Colorado. Our total Fe and Al data are within 10% of literature data

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except for Fe in the Nile, and Fe and Al in the Colorado, where the differences are closer to 20%. However our Colorado data are within 10–15% of the Fe and Al suspended particulate data reported by Canfield Ž1997.. Trace element data ŽTable 6. are in good agreement with the data from Martin and Meybeck Ž1979. for the Amazon, Magdalena, Nile and Colorado Žonly Cu in the Nile is different by more than two standard deviations.. Agreement with published data for the Huanghe and Changjiang is not as close, but only Cu and Ni in the Changjiang, and Mn in the Huanghe, are outside four standard deviations. These major and trace element data suggest that our samples are broadly representative Žonly Cu shows any consistent differences. and the present data set can be considered to provide a useful preliminary

Table 4 Analytical data for river suspended sediments. All values in parts per million except Fe and Al Žwt.%. Element

Amazon

Huanghe

Brahmaputra

Changjiang

Magdalena

Nile

Colorado

Burdekin

Cr D Cr H Cr R Cr Total Mn D Mn H Mn R Mn Total Co D Co H Co R Co Total Ni D Ni H Ni R Ni Total Cu D Cu H Cu R Oxidisable Cu Cu Total Zn D Zn H Zn R Zn Total Fe D Fe H Fe R Fe Total Al Total Organic C

ND ND ND ND 778 113 133 1024 ND ND ND ND 51 68 7 126 ND ND ND ND ND 145 241 48 434 2.6 0.38 2.61 5.59 12.11 3.1

1 9 59 69 346 137 153 636 3 5 8 16 4 22 31 57 2 23 10 4 35 25 38 25 88 0.96 1.51 1.2 3.59 7.53 1.3

8 56 68 132 359 274 287 920 11 10 16 37 63 42 46 151 590 5061 826 4632 6477 20411 2474 99 22984 0.67 2.17 0.27 3.06 7.7 0.83

ND ND ND ND 644 200 153 997 18 10 10 38 16 32 16 64 9 117 24 ND 150 59 60 32 151 1.86 1.72 1.34 4.92 6.97 0.78

38 17 67 142 800 235 103 1138 9 10 7 26 1 20 56 77 64 402 136 168 602 436 179 30 645 3 0.96 0.98 4.94 10.84 2.5

42 13 80 135 631 328 466 1425 13 10 17 40 10 35 61 106 7 50 27 8 84 13 49 35 97 2.4 2.71 4.09 9.2 8.72 0.72

8 36 30 74 398 87 93 578 10 3 10 23 1 12 19 32 7 34 20 7 61 77 48 28 153 1.1 1.33 0.55 2.98 6.95 2.1

34 22 78 134 580 69 108 757 10 3 12 25 21 18 55 94 5 33 19 2 56 27 40 58 124 3.25 0.44 2.33 6.02 11.7 1.49

ND s At or below detection limit.

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

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Table 5 Comparison of major element literature analyses of suspended river particulate compositions with analyses from the present study Žin wt.%.. Standard deviations based on measurements in Table 3 River

Fe

Amazon

5.59"0.11 5.50 Huanghe 3.59"0.07 3.72 Changjiang 4.92"0.10 5.20 Magdalena 4.94"0.10 5.20 Nile 9.20"0.18 10.80 Colorado 2.98"0.06 2.30

Al

Source

12.11"0.24 11.50 7.53"0.15 7.91 6.97"0.14 ND 10.84"0.21 ND 8.72"0.17 9.80 6.95"0.14 4.30

Present study Martin and Meybeck, 1979 Present study Huang et al., 1992 Present study Huang and Zhang, 1990 Present study Martin and Meybeck, 1979 Present study Martin and Meybeck, 1979 Present study Martin and Meybeck, 1979

N.B. Canfield Ž1997. gives 3.66% Fe and 7.60% Al for the Colorado. No data available for the Brahmaputra and Burdekin.

assessment of the relative importance of different phases in the transport of these transition metals on a global scale. Note that our Fe and Mn data for the Amazon and Nile Žfor which grain-size fractions of bed sediments were analysed. show no evidence of Fe and Mn enrichments resulting from the concentration of authigenic Fe and Mn oxides into bed sediments.

4. Interpretation

4.1. Phase associations Table 4 shows that different rivers may have wide variations in the amounts of each different phase, as measured by the variations in Fe D Ž0.7–3.0%., Fe H Ž0.3–2.2%. and Fe R Ž0.3–4.1%.. There are also significant variations in the relative proportions of each phase, as measured by the proportion of total iron, which each phase contains; dithionite-soluble Ž22– 61%., hydrochloric-acid-soluble Ž7–71%. and residual Ž9–47%.. The total concentrations of trace elements also vary considerably between rivers ŽMn 636–1425, Cu 35–6477, Ni 32–151, Co 16–40, Cr 69–142 and Zn 88–22984 ppm.. This is particularly the case for the Brahmaputra Žand to a lesser extent the Magdalena., which have exceptionally high Cu and Zn contents relative to the other rivers. These totals show no significant correlations Žat the - 0.1% level. with organic C, total Fe or total Al. The highest concentrations of Mn ŽFig. 2. are associated with the dithionite-soluble fraction Ž62 " 14%., and the hydrochloric-acid-soluble and residual Mn fractions are smaller, but approximately equal in importance Ž19 " 7% and 19 " 9% respectively.. The distribution of Mn between the three fractions shows

Table 6 Comparison of trace element literature analyses of suspended river particulate compositions with analyses Žin parts per million. from Table 4. Relevant standard deviations based on measurements in Table 3 River

Cr

Mn

69 " 9 95

1024 " 69 1033 636 " 43 885 997 " 67 1109

Amazon Huanghe Changjiang Magdalena

142 " 18 136

Co

16 " 2 15 38 " 5 19 26 " 3 19

Ni 126 " 15 105 57 " 7 52 64 " 8 124

Nile Colorado

74 " 10 82

578 " 39 430

23 " 3 17

32 " 4 40

Cu

Zn

Source

35 " 3 23 150 " 12 62

434 " 52 426 88 " 11 53 151 " 18 120

84 " 7 39

97 " 12 93

Present study Martin and Meybeck Ž1979. Present study Huang et al. Ž1992. Present study Zhang Ž1995. Present study Martin and Meybeck Ž1979. Present study Martin and Meybeck Ž1979. Present study Martin and Meybeck Ž1979.

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

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Fig. 2. Proportions of dithionite-soluble Žshaded., hydrochloric-acid-soluble Žcross hatched. and residual Žclear. Mn, Cu, Ni, Co, Cr and Zn in the sampled rivers. Total concentrations in parts per million in brackets.

relatively small variations between different rivers. Data for the dithionite-soluble fraction of Mn in Amazon sediments Ž76%. are reasonably consistent with previous measurements Ž60%; Gibbs, 1977., and the mean Mn D value Ž62 " 14%. is close to previous measurements for this fraction in the Yukon Ž52%; Gibbs, 1977. and in 23 river sediments from the USA Ž72 " 12%; Canfield, 1997.. The three Cu fractions display a striking similarity in their relative importance in sediments from all

rivers under study ŽFig. 2.. In all cases, Cu is mainly associated with the hydrochloric-acid-soluble fraction Ž66 " 9%.. The residual fraction is the next largest Cu pool Ž26 " 8%., while the Cu D fraction represents only 9 " 2% of the total Cu content Žsimilar to estimates of 14% and 6% for the Cu D fraction in the Amazon and Yukon respectively; Gibbs, 1977.. The hydrochloric-acid-soluble fraction includes elements associated with sheet silicate minerals, in addition to organically bound trace elements, and distin-

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S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

guishing between these contributions has important implications for assessing the extent of anthropogenic influences in world river particulates Žsee later.. Thus oxidisable Cu was determined for the Huanghe, Brahmaputra, Magdalena, Nile, Colorado and Burdekin rivers Žinsufficient sample was available for the Amazon and Changjiang rivers.. Table 4 demonstrates that for the Huanghe, Nile, Colorado and Burdekin rivers, the majority of HClsoluble Cu is associated with sheet silicate minerals rather than organic matter Žonly 7–20% of HCl-soluble Cu, or 4–13% of total Cu is associated with organic matter, assuming that the HCl extraction removes all the organically bound Cu.. Consistent with this, our Cu H fraction Žand total Cu. show no significant correlations with organic C. Concentrations of up to 250 ppm Cu may be associated with Fe and Mg silicates Žsuch as biotite. from basic rocks ŽZemann and Wedepohl, 1969.. It has also been shown that organically bound Cu accounts for approximately 6% of the total particulate Cu transported by the River Amazon ŽGibbs, 1973, 1977. and 5.5–7% of the total Cu transported by the Changjiang ŽZhang et al., 1990.. Thus for all these rivers it is clear that the relatively high proportions of HCl-soluble Cu arise mainly from an association with sheet silicates Žsee also Gibbs, 1973, 1977. rather than organic matter Ži.e. as a result of natural processes rather than anthropogenic activities; see earlier.. By contrast, oxidisable Cu accounts for ) 40% of the HCl-soluble fraction for the Magdalena, and ) 90% of the HCl-soluble fraction for the Brahmaputra. Significant concentrations of total S Ž1.73%. were found in the Magdalena particulates and the oxidisable Cu may here be associated with sulphide ores andror organic matter. The Magdalena passes through regions of mining activity and the presence of sulphide phases, which are resistant to oxidation, is not unreasonable. Negligible concentrations of total S Ž- 0.08%. were found in the Brahmaputra, and all oxidisable Cu must therefore be organically bound, suggestive of a strong anthropogenic source ŽSalomons and Forstner, 1980, 1984.. The phase associations of Ni display more variability between different rivers than most of the other elements studied ŽFig. 2.. However, with the exception of the Amazon and Brahmaputra, Ni is

predominately associated with the residual fraction Žthe average for all rivers is 45 " 23%.. The hydrochloric-acid-soluble Ni fraction represents 36 " 12% of the total Ni content, while 19 " 16% is associated with the Ni D fraction. Gibbs Ž1977. demonstrated that the Amazon and Yukon sediments contained 48% and 52% dithionite-soluble Ni respectively. The Amazon data are consistent with the value measured here Ž40%., although this is atypical of the mean river value Ž19 " 16%.. The phase associations of Cr also display a relatively high degree of variability between rivers ŽFig. 2.. As with Ni, the Cr R fraction is generally the most important phase Ž60 " 15%., while the Cr D and Cr H fractions contain 17 " 13% and 24 " 17% of the total Cr content respectively. Consistent with this, Gibbs Ž1977. gave estimates for the Cr D fraction of Amazon and Yukon rivers of 7% and 11% respectively. Of all the trace elements studied, the phase associations of Zn show the greatest variability between different rivers ŽFig. 2.. The relative proportions of Zn associated with the dithionite-soluble, hydrochloric-acid-soluble, and residual fractions are 43 " 25%, 37 " 14%, and 21 " 15% respectively. Co has similar phase associations in all the rivers, but no single fraction dominates ŽFig. 2.. The relative proportions of cobalt associated with each fraction are 35 " 10%, 25 " 9%, and 40 " 9% for Co D , Co H , and Co R respectively. The Co D contents of these rivers are again consistent with estimates of 36% and 25% for the Amazon and Yukon rivers respectively ŽGibbs, 1977.. Similarities in phase associations are to some extent supported by the correlation coefficients ŽTable 7., where values exceeding 0.84 are significant at the - 0.1% level. The only significant correlations within the dithionite fraction are FerMn and CurZn, within the HCl-soluble fraction between CorMn, and within the residual fraction for CorMn, CrrNi and CurZn. Cu and Zn show a strong covariance in both the hydrochloric-acid-soluble and residual fractions suggesting that the modes of occurrence of these elements may be strongly related in river particulates. However, the phase associations of Zn are more variable than those of Cu ŽFig. 2., which is consistently dominated by the hydrochloric-acidsoluble fraction with only a small dithionite-soluble

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31 Table 7 Correlation coefficients for hydrochloric-acid-soluble and residual trace element relationships. The Brahmaputra exerts a strong control on some of the relationships, and values in parenthesis indicate the coefficient obtained when this river is discounted Cu

Co

HCl soluble Zn 0.99 0.37 Cu 0.39 Co Cr Ni Fe Residual Zn 0.89 Cu Co Cr Ni Fe

0.62 0.47

Cr

Ni

Fe

Mn

0.84 Ž0.09. 0.84 Ž0.13. 0.11

0.31 0.66 Ž0.04. 0.78 0.37

0.34 0.35 0.61 0.16 y0.06

0.40 0.40 0.91 0.07 0.12 0.80

0.32 0.14 0.45

0.22 0.19 0.42 0.93

y0.20 y0.45 0.47 0.62 0.25

0.24 0.27 0.84 0.51 0.47 0.35

fraction. The correlation between Cr R and Ni R Ž R s 0.95. suggests that these elements are associated with similar resistant silicate phases. The phase associations of Mn in river particulates have previously been studied in relation to chemical weathering processes by Canfield Ž1997.. Increased rates of chemical weathering Žas denoted by increased runoff and precipitation rates. result in higher concentrations of total Mn Ždue to the loss of the more soluble elements such as Na, Ca, Mg, K and SiO 2 .. In addition, a greater proportion of the Mn is present in the form of insoluble oxides at higher rates of weathering Ždue to secondary precipitation following initial release from a variety of minerals during weathering; Canfield, 1997.. Iron behaves in a similar manner during chemical weathering ŽCanfield, 1997. and thus, perhaps unsurprisingly, the speciation of Mn and Fe shows some similarities in the river sediments studied here ŽFig. 3.. The Mn D fraction displays a strong covariance with the Fe D fraction Ž R s 0.84; Fig. 3., as do the Mn H and Fe H fractions Ž R s 0.80; Fig. 3., although the residual Mn and Fe fractions display a rather poor relationship Ž R s 0.55.. On average, 62% of the total Mn contents of these river sediments is associated with oxide phases, compared to an oxide association of only 39% for Fe Žimplying that Mn may be more readily released from silicate minerals during weath-

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ering.. This observation is supported by the relatively poor relationship between Mn R and Fe R fractions, suggesting that Mn and Fe may tend to be associated with different minerals in the parent rocks. By contrast, the remaining transition metals display only poor relationships with the equivalent Fe fractions. Overall Fig. 2 shows that there is a reasonable degree of consistency in trace element behaviour, in that an individual trace element is often mainly associated with a single fraction ŽMn in the dithionite-soluble fraction, Cu in the HCl-soluble fraction, and Ni and Cr in the residual fraction.. Co is present to a significant Žand fairly uniform. degree in all three fractions, whereas Zn is variably partitioned between the three fractions. Relatively unpolluted rivers tend to transport transition metals in association with crystalline phases Že.g. Gibbs, 1973, 1977; Huang et al., 1988; Zhang et al., 1990., which can be solubilised as part of our residual and HCl-soluble fractions. By contrast, more polluted rivers have

Fig. 3. Relationships between dithionite-soluble Mn and Fe, and hydrochloric-acid-soluble Mn and Fe in the sampled rivers.

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S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

elevated particulate transition metal concentrations, which tend to be associated with nonlattice phases ŽSalomons and Forstner, 1984.. Thus, when viewed in isolation, our phase association data suggests that pollutant influences are potentially important for Mn and Zn Žand possibly Co., which have relatively high proportions associated with the dithionite-soluble fraction, and for Cu in the Brahmaputra and Magdalena Žwhich have high Cu contents in association with sulphides andror organics.. However these data need to be evaluated in terms of the natural abundances of transition metals before anthropogenic and weathering influences can be adequately distinguished. 4.2. Variations in enrichment factors between riÕers River sediments have the potential to provide valuable information relating to the modification of global trace element cycles as a direct result of anthropogenic activity. Theoretically, the impact of pollution on individual rivers may be assessed using enrichment factors ŽEF. for individual elements: EF s Ž w x x pm r w Al x pm . r Ž w x x frr w Al x fr .

Ž 1.

where wxx pm rwAlx pm is the ratio of an element to Al in river sediment, and wxx fr rwAlx fr is the ratio of an element to Al in fresh rock. Aluminium is generally considered to behave conservatively during weathering, and thus an EF of - 1 represents solubilisation relative to Al. However, an EF of ) 1 may indicate either a pollutant input or geochemical fractionation in the soil profile, which results in the enrichment of the element in the top soil layer that supplies the river particulate load. Differential erosion processes may also result in a relatively high enrichment factor ŽMartin and Whitfield, 1983., because a large proportion of suspended matter transported by the world’s rivers originates in mountainous regions, where elements such as Cu and Zn are generally more abundant ŽWilson and Laznicka, 1972; Gibbs, 1977.. However, the calculation of enrichment factors can provide a useful indication of unusual inputs to drainage basins. Unfortunately the wxx fr rwAlx fr ratio of large drainage basins is often difficult to assess, due to lithological variations over the drainage areas. Normalisation with respect to soils can be attempted Žsee

Windom et al., 1989; Zhang, 1995., but this is also difficult due to a lack of data for average soil compositions in the watersheds under study. However, this approach is possible for the suspended sediments transported by the Huanghe, which are largely derived from well-characterized loess deposits ŽGong and Xiong, 1980; Zhang et al.,1990.. Enrichment factors for the Huanghe based on the loess analyses ŽTable 8. are reported in Table 9, which also includes trace element enrichment factors for the remaining rivers derived by normalising their wxx pm rwAlx pm ratios to estimates for the global average composition of soils ŽTable 8.. For comparison, enrichment factors calculated relative to world average soils are also included for the Huanghe. EF values for the Huanghe based on loess suggest the differential loss of Mn, Cr and Co accompanied by gains in Ni and Cu. These changes may be attributable to weathering processes but may also arise because 10% of the river particulates are derived from sediment sources other than loess ŽGong and Xiong, 1980.. EF values for the Huanghe based on average soil composition are comparable with those based on loess with the exception of Co Žfor which the soil content is less than half that of loess; Table 8.. The Huanghe is generally considered to be one of the least polluted of the major world river systems Žsee Zhang, 1988, 1995; Zhang et al., 1990., and this is reflected in EF values close to unity for this river Žrelative to both loess and the average composition of world soils; Table 9.. Although calculated relative to the average global composition of soils, consideration of EF values in conjunction with the phase association data may also

Table 8 Elemental compositions of loess ŽZhang et al., 1990. and estimates for the average composition of soils ŽMartin and Whitfield, 1983.. Al in wt.%, other elements in parts per million Element

Loess

Soils

Al Cr Mn Co Ni Cu Zn

6.5 74 760 17 33 23 66

7.10 70 1000 8 50 30 90

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31 Table 9 Enrichment factors for rivers under study Žsee text for details.. Enrichment factors for the Huanghe are reported relative to loess and world average soil compositions. Mean values exclude EF values based on loess River Amazon Huanghe Žloess. Huanghe Žsoil. Brahmaputra Changjiang Magdalena Nile Colorado Burdekin Mean Standard deviation

Cr 1.63 0.81 0.93 1.76 ND 1.33 1.57 1.08 1.16 1.35 0.31

Mn a

0.60 0.72 0.60 0.86 1.02 0.75 1.16 0.59 0.46 0.76 0.24

Co 3.00 0.81 1.89 4.31 4.84 2.13 4.07 2.94 1.90 3.14 1.15

Ni a

Cu

1.48 5.20 1.49 1.31 1.08 1.10 2.81 201 1.30 5.09 1.01 13.1 1.73 2.28 0.65 2.08 1.14 1.13 1.40 28.9 0.65 69.7

Zn a

2.83 1.15 0.92 238 1.71 4.69 0.88 1.74 0.84 31.5 83.5

a

Indicates total river particulate concentrations from Gibbs Ž1977. for values not measured in the present study.

provide an assessment of the anthropogenic enrichment of trace elements in the sampled particulates. The EF value for Zn in the Brahmaputra is exceptionally high Ž238., while values considerably greater than 1 are also apparent for the Amazon, Changjiang, Magdalena and Colorado ŽTable 9.. These rivers also transport a significant proportion of their total Zn in association with the dithionite phase Ž30–90%; Fig. 2.. These observations suggest that the Zn contents of these rivers have been significantly affected by anthropogenic activities Žsee Salomons and Forstner, 1980, 1984.. By contrast, EF values - 1 and low proportions in association with the dithionite phase ŽFig. 2. suggest that Zn has not been significantly modified by anthropogenic processes in the Huanghe, Nile and Burdekin rivers. With the exception of the Huanghe, EF values for Co are significantly greater than 1 ŽTable 9. and a relatively large proportion of the total Co is transported in association with the dithionite phase Ž30– 50%; Fig. 2., suggestive of a significant anthropogenic Co input to the rivers under study. By contrast, EF values for Mn are low Žless than or approximately equal to 1., indicating no significant enrichment of Mn in these particulates Žas highlighted earlier, the relatively high proportions of Mn found in association with the dithionite phase are likely to arise due to weathering processes rather than being suggestive of anthropogenic enrichments..

27

Enrichment factors for Ni and Cr tend to be close to unity ŽTable 9., and the generally low proportions of these elements in association with the dithionite phase ŽFig. 2. suggest little anthropogenic modification of these elements in the river particulates under study. Enrichment factors for Cu are high for the majority of the river particulates under study ŽTable 9., and this is particularly the case for the Brahmaputra and Magdalena rivers. Although all the rivers have low proportions of Cu in association with the dithionite phase, the Brahmaputra and Magdalena rivers transport a significant proportion of their total Cu in association with sulphides andror organic matter, suggestive of a large anthropogenic Cu addition to these rivers. The low proportions of Cu present in the dithionite and organic phases for the remaining rivers suggest little anthropogenic modification. Rather, the fact that the majority of the Cu is transported in association with HCl-soluble silicate minerals Žsee earlier. suggests that processes other than anthropogenic activities are likely to account for the elevated EF values. Next we attempt to assess the impact of pollution on a global rather than regional scale by considering observed and theoretical transition metal fluxes to the oceans. 4.3. Oceanic fluxes and global Õariations in the supply and phase associations of trace elements The majority of the river systems under study represent major world rivers draining large continental areas ŽTable 1.. In many cases, a wide variety of lithologies are being eroded, and thus the average chemical composition of sediments from these basins may be considered to approach that of the continental average. An obvious exception to this is the Huanghe, where 90% of the sediment load is derived from loess deposits ŽGong and Xiong, 1980.. However, despite obvious lithological and climatological differences, many of the transition elements display a close degree of similarity in their phase association characteristics. This suggests that the present data-set, although limited by the single event sampling scheme, can provide a preliminary estimate of the average proportions of different trace element fractions in river particulates on a global scale. The

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

28

Table 10 Discharge-weighted proportions and concentrations Žppm. of trace elements in river particulates supplied to the oceans Žsediment fluxes from Milliman and Syvitski, 1992.. Total concentrations are based on the data of Martin and Meybeck, 1979; Huang and Zhang, 1990; Huang et al., 1992; Zhang, 1988; Presley et al., 1980; Trefry et al., 1986; Yeats and Bewers, 1982 Fraction

Cr

Mn

Co

Ni

Cu

Zn

Dithionite-soluble Ž% total. Hydrochloric-acid-soluble Ž% total. Residual Ž% total. Total concentrations

7 " 0.3 22 " 2.1 71 " 5.0 116

61 " 0.5 19 " 1.1 20 " 0.6 922

30 " 2.1 29 " 2.6 41 " 3.5 23

24 " 2.1 43 " 1.5 33 " 2.0 77

7 " 0.4 67 " 1.6 26 " 1.1 110

35 " 2.3 46 " 4.1 19 " 0.9 217

proportions of the different trace element fractions present in the eight rivers under study are weighted for their relative sediment discharge, and estimates for the average phase associations of trace elements in world river particulates are reported in Table 10. Flux ratios allow the relative influences of pollution and natural sources Žand also fractionations resulting from weathering and biochemical processes. in the river systems to be evaluated on a global basis Že.g. Martin and Meybeck, 1979.. The flux ratio ŽFR. relates the observed flux for an element in river systems, to the theoretical flux: Theoretical flux s w x x s Mpm w Al x pm r w Al x s Ž 2. Observed flux s Ž w x x sol Q . q Ž w x x pm Mpm .

Ž 3.

Thus, FR s Ž Ž w x x sol Q . q Ž w x x pm Mpm . . r

Ž wxx s Mpm wAlx pm r wAlx s .

Ž 4.

where wxxs s average content of element x in average world soil ŽTable 8., wAlx pm s average Al content of river particulates Ž9.4%; Martin and Meybeck, 1979., wAlxs s average Al content of world soils Ž7.1%; Martin and Whitfield, 1983., Mpm s annual discharge of river particulates to the ocean Ž20 billion tons; Milliman and Syvitski, 1992., wxxsol s average dissolved content of element x in rivers ŽMartin and Whitfield, 1983; GESAMP, 1989., Q s annual river water discharge to the ocean Ž38.5 = 10 3 km3ryear; Baumgartner and Reichel, 1975.. The inclusion of dissolved fluxes in these calculations allows the effects of variations in the relative solubilities of different trace elements to be taken into account. Flux ratios ŽTable 11. are calculated relative to the discharge-weighted total transition metal concentrations of world river particulates derived in Table 10. These total concentrations represent revised estimates based on the data of Martin and Meybeck Ž1979., incorporating more recent data

relating to several major world rivers Žparticularly the major Chinese rivers. which were previously unrepresented. This assessment is intended to provide the best approximation of the average total element compositions of world river particulates currently possible, and as such does not include the analyses of single sediment samples from the present study. The flux ratios reported in Table 11 are generally consistent with previous estimates ŽMartin and Meybeck, 1979; Martin and Whitfield, 1983., suggesting that observed fluxes of Cu and Zn are considerably higher than theoretical fluxes, while observed fluxes of Cr and Ni are only slightly greater than theoretical fluxes. The flux ratio for Mn Ž0.71. is close to unity, but the flux ratio for Co Ž2.19. is considerably higher than previous estimates Ž1.15; Martin and Meybeck, 1979.. The flux ratio for Mn is consistent with our phase association data in suggesting that Mn is largely unaffected by pollutant inputs on a global scale, but the high Co flux ratio represents a major discrepancy between the present estimates and previous studies ŽMartin and Meybeck, 1979; Martin and Whitfield, 1983.. However, it should be noted that Martin and Meybeck Ž1979. calculated flux ratios relative to the

Table 11 Comparison of observed and theoretical transition metal fluxes in world river systems Ž10 12 gryear.. Dissolved data from Martin and Whitfield Ž1983. except ) GESAMP Ž1989. Cr River particulate load River dissolved load Total load Theoretical load Flux ratio

Mn

Co

Ni

Cu

Zn

2.32 18.44 0.46 1.54 2.20 4.34 0.04 0.32 0.004 0.02 0.06 0.02 ) 2.36 18.76 0.46 1.56 2.26 4.36 1.85 26.5 0.21 1.32 0.79 2.38 1.28 0.71 2.19 1.18 2.86 1.83

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

average composition of surficial fresh rock ŽCo s 13 ppm., rather than to the average composition of world soils ŽCo s 8 ppm; Martin and Whitfield, 1983.. A small change in the estimate for Co in either soils or surficial rocks has a significant effect on the resulting flux ratio, due to the low concentrations of Co in surface sediments. Calculation of the Co flux ratio relative to surficial fresh rock gives a value of 1.35 Žusing the estimate of 23 ppm Co in world river particulates; Table 10.. Thus, it is likely that the very high FR value given in Table 11 arises partly due to an underestimation of the average concentration of Co in world soils. However, the data still suggest that Co may have been significantly affected by pollutant inputs in river particulates on a global scale Žperhaps by as much as 35%.. This conclusion is consistent with the relatively large dithionite-soluble fraction Ž30%; Table 10., suggestive of an anthropogenic contribution Žsee Salomons and Forstner, 1980, 1984.. The flux ratio for Zn Ž1.83; Table 11. also suggests a potentially significant anthropogenic source for this element in world river particulates. The highly variable phase associations of Zn in the river sediments under study, together with the large proportions found in association with the dithionitesoluble fraction ŽFig. 2. support the conclusion that pollution may be the primary source of the elevated present-day Zn concentrations of river particulates. Interestingly, an apparent imbalance exists between oceanic fluxes of Zn and subsequent removal in deep-sea clays, which has been attributed to possible anthropogenic Zn mobilisation, since any additional input may not yet be recorded in deep-sea clays Žsee Yeats and Bewers, 1982; Windom, 1990; Martin and Windom, 1991.. Martin and Windom Ž1991. estimate an additional Zn input of approximately 95% to the marine environment relative to the deposited sediments, a figure which is consistent with the present estimate for the anthropogenic enrichment of Zn in world river particulates Ž83%; Table 11.. The FR values for Cr and Ni ŽTable 11. are consistent with the low proportions of these elements transported in association with the dithionite-soluble phase, suggesting that riverine particulate Cr and Ni can only have been slightly affected by pollutant inputs on a global scale. However, the major sources of Cu in river particulates are apparently more com-

29

plex than the other transition metals under study. Clearly, based on the phase association data and the EF values presented earlier, the major source of Cu in the rivers under study varies between anthropogenic enhancements and differential weathering or geochemical fractionation processes. However, in the present study only the Brahmaputra and Magdalena particulates appear to have been significantly affected by anthropogenic Cu enrichments. These rivers have very high total Cu contents ŽBrahmaputra 6477 ppm, Magdalena, 602 ppm; Table 4., relative to both the remaining rivers of the present study ŽTable 4. and to the average total Cu content of world river particulates Ž110 ppm; Table 10.. The Amazon, Huanghe, Changjiang, Nile and Colorado rivers, which are relatively unaffected by pollutant Cu enrichments Žsee earlier., are very important in terms of the calculation of the discharge-weighted concentration of Cu in world river particulates Žaccounting for 15% of the total sediment flux to the oceans.. Thus, it appears likely that the estimate for the average concentration of Cu in world river particulates Ž110 ppm. is largely based on river systems which are relatively unaffected by pollutant Cu inputs Žnote that total analyses from the present study were not used in this calculation.. Despite this fact, the FR for Cu is very high Ž2.86. suggesting that differential weathering or geochemical fractionation processes are also important in terms of the global Cu flux. This inference is further supported by the observation ŽMartin and Windom, 1991. that the Cu contents of marine sediments equate well with the observed flux of Cu to the marine environment Žin contrast to the anthropogenically modified flux of Zn; see earlier..

5. Conclusions The mean phase association data, EF values and flux ratios suggest that the behaviour of Cu and Zn are clearly distinctive. The high dithionite-soluble Zn levels further point to the predominance of pollutant inputs to river systems, whereas the high Cu content of world river particulates relative to the average composition of the rocks being eroded, does not appear to be due to a significant pollutant source on a global scale Žalthough Cu levels may be locally

30

S.W. Poulton, R. Raiswellr Marine Chemistry 72 (2000) 17–31

enhanced by mining and other anthropogenic activities.. Rather, the high hydrochloric-acid-soluble Cu contents indicate that geochemical fractionation in the soil column or differential erosion processes may account for the elevated Cu contents. The other four elements display rather similar characteristics, which may range in pollutant contributions from Mn Žlow. to Co ŽHigh.. Mn Žlow EF and FR values. appears to have been the least affected by anthropogenic perturbations, with the high dithionite-soluble Mn contents appearing to arise solely due to weathering processes. By contrast, Co Žsomewhat enhanced EF and FR values. appears to be the most affected by pollutant contributions, consistent with fairly high dithionite-soluble metal levels. We can find no evidence for significant pollutant contributions for Cr and Ni ŽEF and FR values close to unity.. We conclude that an improved insight into the processes affecting transition metal sources and fluxes in world river particulates can be gained by considering speciation characteristics along with EF and FR values and phase associations.

Acknowledgements We are grateful to Robert Aller, Ji-Long Rao, Robert Berner, Jim Best, Mike Krom and Jan Alexander for generously donating sediment samples. This work was supported by NERC grant GT4r94r178rG to SWP.

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