trace element inter-relationships for the humber rivers: inferences for hydrological and chemical...

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ELSEVIER The Science of the Total Environment 194!195 (1997) 321-343

Trace element inter-relationships for the Humber rivers: inferences for hydrological and chemical controls

Colin Neal, Alice J. Robson, Hazel A. Jeffery, Martin L. Harrow, Margaret Neal, Christopher J. Smith, Helen P. Jarvie

Institute oj Hq‘drolo~~, Ma&an Building, Crott,marsll G/ford, Wallingfiwd, OXON, OX10 8BB UK

Abstract

Data on a wide range of trace elements, determined by multi-element procedures based on inductively coupled plasma emission and mass spectrometry, are presented for the major rivers entering the Humber estuary. The average trace element chemistry varies significantly across the region with a clear divide between the southern and northern rivers. This pattern is related to lead-zinc-barium mineralisation and flood plain sediment contamination from historic mining activity, and to historic and current industry and urbanisation to the south. For the industrial/urban rivers, most dissolved components dilute with flow; this pattern is most clearly seen for those components with little acid available particulate (AAP) fractions. In the ruralimineralised areas, dissolved components show more variable flow patterns. AAP fractions and dissolved components with significant associated AAP fractions usually increase with flow in all rivers. The different trace elements show multi-linear relationships with one another. These are much tighter than the links between dissolved and AAP components of the same element. Two main groups of closely associated elements emerge, but these groups are different on northern and southern rivers. The first group corresponds to elements which dilute with flow and this group includes significantly more trace elements to the south where industrial and urban inputs dominate. For this group, within-river chemical processes do not seem to be operative as linear relationships with each of the trace elements of the group and chloride are observed: chloride is chemically conserved within river systems and is predominantly found in the point source effluent discharges. The second group corresponds to those determinands which increase with increasing flow for both dissolved and AAP fractions and they have a high AAP fraction: relationships show much more scatter for this group. Links between dissolved and particulate fractions for this second group are weak and are not well described by empirical partition coefficient relationships which are commonly used in environmental modelling studies. Rather, AAP fractions are much more closely linked with suspended solid concentrations than the dissolved component. The reasons for the contrasting behaviour between the two groups probably reflects the inability of 0.45 /Lrn filtration (47 mm diameter cellulose nitrate Whatman sterile filters in this case) to remove all colloidal sized materials. Thus, for this second group, at high flows, when suspended sediments are at their highest, there is the greatest potential for acid available enriched micro-particulates to pass through the filters. This feature provides a fundamental schism for environmental research for this second and wide ranging group: process based water suspended-sediment interaction modelling requires a clear separation between truly dissolved and truly particulate fractions; water industry based environmental sampling and management strategies, as well as legislative water consent controls, are based on a 0.45 !tM separation.

0048-9697:97:‘S17.00 C 1997 Elsevier Science B.V. All rights reserved

PII SOO48-9697(96)05373-9

322 C. Neal et al. / The Science of’ the Total Environment 194/195 (1997) 321-343

The results point to the importance of contributing sources and hydrological controls in determining dissolved and AAP concentrations in the Humber rivers. The role of within-river chemical controls is much less clear-cut and may well be of second order importance. 0 1997 Elsevier Science B.V.

Keywords: LOIS; Humber; Water quality; Trace elements; Trace metals; Trent; Ouse; Partition coefficients; Particu- lates; Suspended sediments

1. Introduction

In this paper, trace element information is presented for the main rivers entering the Humber estuary using data collected under the Land Ocean Interaction Study (LOIS) Rivers And Coasts Study for the Riverine (RACS(R)) component of the monitoring programme (Leeks et al., 1997). The paper characterises the dominant features of trace element river chemistry to gain insights into dominant sources, key underlying within-river hydrochemical processes and hydrological controls at a level that (a) is relevant to environmental management and (b) acts as a base for water quality management and chemical flux modelling and more detailed and process linked special topic initiatives which are being undertaken within LOIS. The work is of particular importance as the Humber provides a major flux of trace elements to the North Sea from British rivers (Robson and Neal, 1997a; Jarvie et al., 1997a). Thus, metal concentrations draining into the Humber, which are well above normal back- ground levels for unpolluted UK river systems (Robson and Neal, 1997a,b), are of environmental and economic concern, since critical loadings need to be assessed and regulated for (De Vries and Bakker, 1996; Forstner and Wittman, 1981; Mal- let et al., 1992; McNeely et al., 1979).

Given the remit for the work, emphasis has been placed on the use of measures that are used within both the water industry and the LOIS programme. In particular, separation between dissolved and particulate fractions has been made on the basis of a filter size cutoff of 0.45 pm. How- ever, fine colloidal material can pass through such filters (cf. Kennedy et al., 1974; Benes and Stein- nes, 1975; Gunn et. al., 1992) and this artificial separation provides an obstacle to describing and modelling riverine chemical reactivity within a

rigorous thermodynamic framework. The implications of this limitation are discussed within the paper.

2. Study area and sampling strategy

Details of the study area and sampling strategy are presented in this volume by Jarvie et al. (1997b) and Leeks et al. (1997) but a brief summary of the salient features are presented here for completeness.

The Humber catchment provides the largest UK freshwater input to the North Sea (average flow of 250 m3 s ~ ‘, NRA, 1993). There are two principal river basins in the area, the Trent and the Yorkshire Ouse (Leeks et al., 1997) and considerable manufacturing industry has been concentrated to the south of the Humber catchment area (Arnett and Justice, 1991). However, in the industrial areas there has been a marked decline over the past 30 years for industries such as coal mining following pit closures. The catchment ex- hibits a wide range of land use types, with large areas of intensively farmed agricultural land in the vales of York and Trent, urbanised and industrial regions in the Midlands and South and West Yorkshire, and open moorland of the Pennines and North York Moors. River water is of variable quality, receiving effluent from mines, industry and urban conurbations, and diffuse inputs from agricultural land. In general, the waters are of fairly high alkalinity and moderate pHs (Jarvie et al., 1997~) although in the upper parts of the region, where the rock types are low in base cations, acidic conditions occur and these areas are susceptible to acidic deposition (Edmunds and Kinniburgh, 1986; UKAWRG, 1988).

Eleven river sites have been sampled under the LOIS programme (Leeks et al., 1997) and they

C. Neal et al. / The Science of’ the Total Emironment 194/195 (1997) 321-343 323

cover the major rivers draining to the Humber estuary (Derwent, Ouse, Aire, Wharfe, Don and Trent) together with selected major tributaries to these rivers (the Upper and Lower Swale, Ure and Nidd and the Calder). The sample points represent a range of environments, geological settings and land-uses and include both predominantly rural and highly industrialised systems. Data from the period September 1993 to September 1995 are presented here.

3. Chemical methodology

Both dissolved and acid available trace element fractions were determined. Here, the acid available fraction represents the dissolved fraction plus that part of the particulate phase which can easily be dissolved under acidic conditions. The dissolved fraction was measured by filtering samples and acidifying the filtrates on the same day of sampling. The acidification, to l%vv concentrated aristar grade nitric acid, ensured that precipitation/adsorp- tion of the trace elements did not occur to a significant degree during storage. The acid available fraction was determined by acidifying an unfiltered sample with concentrated aristar grade nitric acid (1 %vv) and agitating for 24 h, at room temperature, prior to filtration. Samples were then analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES: B, Ba, Fe, Mn, Sr) and mass spectrometry (ICP-MS: Al, As, Co, Cr, Cu, Li, MO, Ni, Pb, Rb, SC, Zn): the lowest quotable values were taken as five times the detection level. In the initial phases of the work, filtration and storage of blank samples were included to test for contamination. For all the chemical determinations, mixed quality control standards were included in the routine analyses. These standards were checked weekly against international quality control references pre- pared by the United States Geological Survey National Water Quality Laboratory (SRM 1643~). Each new batch of calibration standards was always cross-checked with the previous batch and the international control references. If there were significant discrepancies between the old and new calibration standards a complete remake of new standards was carried out. The Institute of Hydrol- ogy’s laboratory takes part in UK and international

inter-laboratory comparisons exercises and a rigorous quality assurance system is maintained. With each batch of samples for ICP-OES and ICP-MS analysis, the Institute of Hydrology’s own quality control standards are included.

For the above analyses, a filter size of 0.45 pm was used (47 mm diameter cellulose nitrate What- man sterile filters). As indicated in the introduction, although not ideal, this filter size has been selected because of its widespread use by the National Rivers Authority and the UK water industry, even though fine colloidal particles can pass through them (Kennedy et al., 1974; Benes and Steinnes, 1975; Gunn et al., 1992). Finer filters are capable of removing these fine particles, but their use leads to both a data compatibility problem and a practical field sampling constraint: the lengthy filtration times involved are simply not compatible with the very long field sampling days required to satisfy the major needs of the programme. For the filtration step, two 50 ml subsamples of water were individ- ually filtered to wash the filters, filtration equipment and sample bottles: the filtrates were then discarded. A third subsample was then filtered and the resultant filtrate was stored for analysis: N.B., this washing step is also of value in relation to the problems of filter efficiency as successive filtration of water leads to a reduction in the micro-particulate fraction passing through the filters, and to a more uniform result (Kennedy et al., 1974). The acid available particulate (AAP) fraction was calculated as the difference between the acid available fraction and the dissolved fraction.

4. Results

Basic patterns of trace element behaviour are examined and are interpreted in terms of their implications for processes and modelling. The approach used has been to study the data set as a whole and from this to identify the salient features. Rainfall inputs of trace elements have not been considered as they are probably of second order importance (cf. Smith et al., 1997) The extensive nature of the dataset (around 120 samples for each of 11 sites and each of 17 determinands) makes the use of graphical displays particularly appropriate. Here, a number of features of the data are investi-

324 C. Neal et al. / The Science of’ the Total Environment 1941195 (1997) 321-343

gated. Regional variations in mean concentrations are interpreted in relation to catchment geography (land use, industry and geology as presented in another paper within this special volume; Jarvie et al., 1997b) to give an overview of the trace element chemistry of the LOIS rivers. The influence of flow on concentration is then investigated by examining the chemical characteristics of base and storm flow waters. Links between the dissolved and AAP fractions of the trace elements are also examined and consideration is given to the issue of whether a distribution coefficient approach is of value to describe the data in a way that will be valuable for the LOIS modelling studies (cf. Schnoor et al., 1987). Finally, the relationships between different trace elements are investigated. The main results are described and implications are discussed in the subsequent section.

1980; Stumm and Morgan, 1970; Garrels and Christ, 1985).

Trace element concentrations show significant variations across the Humber catchment area. The main features relate to three main influences.

4.1. Regional variation in trace element concentrations

The main features of the trace element results are summarised below: basic information on average concentrations and ranges at each of the sites, are provided in Neal et al., 1996.

Of the elements analyzed, Al, As, Ba, Cr, Co, Cu, Fe, Pb, Mn, Ni and Zn are found in both dissolved and particulate form, whereas B, Li, MO, Rb, SC and Sr exist predominantly in dissolved form. This distinction reflects the chemical reactivity of the trace elements. Elements found predominantly in the dissolved phase are probably chemically conserved in solution (i.e. they are relatively unreac- tive), whereas those with a high AAP fraction may, depending upon the particular element, be involved in adsorptiondesorption reactions and solubility controls (cf. Bassett, 1980; Kaback and Runnels,

(i) Lead-zinc mineralisation in the northern catchments (Swale, Nidd and Ouse). In the northern rivers, where current industrial activity is limited, historical lead-zinc mining activity has led to major contamination of stream and flood plain sediments from mineral veining the North Yorkshire orefield by mining spoil (especially in the Swale; Say and Whitton, 1981; Gill, 1991; White, 1989; Macklin, 1992; Macklin et al., 1997; Hudson-Edwards et al., 1997): N.B., a major feature of the north Pennine area of the LOIS area from the Tyne to the Swale, Ouse, Ure, Nidd and Wharf is the occurrence of such mineralisation (Macklin et al., 1997 cf. their Fig. 1). As a result, these rivers are important sources of Pb, Zn and Ba along their length. Within these rivers, materials concentrated within particulate phases are released to solution by weathering processes. The composition and storage of the solid phases changes along the length of the river as a result of sulphide oxidation and the precipitation of hydroxide phases as well as physical dispersion (Macklin et al., 1997; Hudson-Edwards et al., 1997).

(ii) Industrial and domestic ejfluents from the southern catchments (Aire, Calder, Don and Trent). With the high level of industrial activity and urbanisation in the South Yorkshire and Trent regions (cf. Edwards et al., 1997 and Jarvie et al., 1997a,b), effluent discharges from industry and sewage works result in higher concentrations of As, B, Cr, Co, Li, Mn, MO, Ni, Rb and SC in the southern LOIS rivers. For this region, the impacts are not simply confined to present day activities as, for example, discharges from abandoned mines and

Fig. 1. (a) Average dissolved and particulate chemical concentrations for Cr, Mn, Co, Ni, Li and B for the Humber Rivers. Here, illustrations of contrasting north-south separations between the rural and industrial/urban rivers are shown as pie plots for components with differing dissolved and particulate concentration ratios. For these plots, the area of the pie plot denote the total concentration: the dissolved portion is the black area and the particulate portion is the shaded area. Average concentrations are provided in the top right hand comer of each diagram. (b) Average dissolved and particulate chemical concentrations for Pb, Ba, Al, Fe, Sr and Zn for the Humber Rivers. Here, illustrations are shown of (a) historic mining influenced rivers (Pb and Ba), (b) contrasting proportions of dissolved to particulate concentrations (Al, Fe) and (c) no regional contrast (Sr and Zn). Concentrations are shown as pie plots for components with differing dissolved and particulate concentration ratios. For these plots, the area of the pie plot denote the total concentration: the dissolved portion is the black area and the particulate portion is the shaded area. Average concentrations are provided in the top right hand corner of each diagram.

C. Nral et ul. : Thr Scirncr qf the Total Enrironmenr 194/195 (1997) 321-343 325

326 C. Neal et al. / The Science of the Total Environment 194/195 (1997) 321-343

Fig. 2. Dissolved and acid available concentrations of trace elements for the Humber rivers. Dissolved concentrations are indicated by the solid bars, acid available concentrations are shown by a diagonally shaded bar. The rivers are ordered from north to south (left to right) and are as follows:- Sl = Upper Swale, S2 = Lower Swale, U = Ure, N = Nidd, 01 = Ouse, W = Wharfe, De = Der- went, A = Aire, C = Calder, D = Don, T = Trent. Units are pg/l.

C. Neal et al. / The Science of’ the Total Encironment 194,/195 (1997) 321-343 321

2.

1.

1.

a.

a.

Fig. 3. Dissolved concentrations of trace elements at low and high flows. Concentrations at base flows (lowest 10% of flows) are shown by the solid bars. Concentrations at storm flows (highest 5% of flows) are shown by the diagonally shaded bars. The sites are ordered and labelled as in Fig. 1. Units are pg!l.

328

Table I

C. Neal et al. ! The Science of’ the Total Environment 1941195 (1997) 321-343

A summary of flow concentration relationships for the Humber rivers

Relationships for Rural/Mineralised catchments

Relationships for Industrial/Ur- ban Rivers

Base > Storm Mixed relationships or Base Base <Storm = Storm

Base > Storm B, Rb, SC, Li, Sr, Cr, As, Co MO, Ni Zn

Mixed relationships or Ba Cu. Mn Pb Base = Storm Base <: Storm Al, Fe

Flow-concentration relationships are characterised for two groups of catchments (1) the rural/mineralized rivers, and (2) the industrial/urban rivers. Concentrations at base flow (Base) and concentrations at storm flow (Storm) are compared. The elements with high AAP ratios are shown in bold (note that Ba only has an AAP component to the north). Elements with higher dissolved concentrations in industrial/urban rivers are underlined. Elements without an AAP fraction or with industrial sources tend to dilute with flow (i.e. Base>Storm).

spoil wastes probably contribute Fe and other metals to the rivers draining this area.

(iii) Widespread sediment sources. Al, Fe and Mn are associated with silicate, oxide and hydroxide phases of many sediments, as well as sulphides in the case of Fe (Krauskopf, 1967; Degens, 1965). These elements show a much less clear cut separation between industrial/urban, historically contam- inated and rural regions.

The above features broadly apply to both the dissolved and AAP fractions and result in a marked separation between the northern and southern rivers of the Humber region as shown in Fig. la,bFig. 2. For Fig. la,b, regional plots for representative chemicals are presented, based on the methods developed by Robson and Neal (1997a,b), but using pie charts to distinguish dissolved and acid available particulate fractions. In Fig. 2, the mean dissolved and acid available total concentrations are plotted as a bar diagram for all the trace elements with concentrations usually above the detection levels: the rivers are presented on the x-axis, from north to south. For example, the highest concentration for lead and barium occur to the left of the graphs, indicating the region of highest historic mining activity, while highest chromium concentrations occur to the right of the graphs, indicating the regions of highest industrial activity. For some determinands, there is no clear separation across the graph and for these cases (such as Zn) the distribution derives from a mixture of the above factors.

4.2. Relationships with flow

Many trace elements show strong concentration variations with flow although these vary according to the determinand and the river. Changes associated with flow need assessing as they can highlight important hydrological controls and can indicate likely sources-e.g. whether surface-water, groundwater or point sources dominate. For all the elements considered here, the dominant source probably comes from within the catchment rather than from the atmosphere.

For determinands with a significant particulate component, the AAP fraction almost always in- creases with increasing flow. This increase links in with the raised turbidity and suspended load at high flows although there is considerable scatter in the relationships between the AAP fraction, flow and suspended solids (see also next section).

For the dissolved fraction, relationships with flow are more diverse. Fig. 3 illustrates this, showing the average dissolved concentration at low and high flows for each site and each trace element. The main features of the concentration-flow relationships are summarised in Table 1. From this, the behaviour in the industrial and urban southern rivers can be compared with the characteristics of the mineralised northern rivers. The results suggest that there are strong links between flow-based changes and the source and form of the element. There are probably two opposing relationships that lead to the patterns observed. Firstly, there is a dilution effect whereby

C. Neal et al. / The Science of’ the Total Environment 1941’195 (1997) 321-343 329

point and diffuse discharges are diluted with increasing flow as the contribution of rainfall in- creases in the rivers. Secondly, there is concentration effect with increasing flow. This can be associated with two factors (a) micro-particulate materials passing through the filters at higher flows when the suspended sediments are at their highest and (b) the transfer of more acidic soil water enriched in mobilised trace elements (the hy- drolysable trace metals in particular) at high flows: cf. Neal et al., 1992. Thus, for the dissolved fraction: (1)

(2)

(3)

(4)

A dilution relationship with flow is more likely if the element has little or no AAP fraction (e.g. B, Rb, SC, Li, Sr on all rivers). i.e. the increased flux of rainfall and near surface runoff from the land during storm events dilutes the point and diffuse sources of the elements. An increase with flow is more likely if the element has a significant associated AAP fraction and the main source is linked to sediments rather than industrial sources (e.g. Al, Fe on all rivers). i.e. the micro-particulate materials passing through the filters are relatively important at high river discharges and point source inputs, which would dilute with increasing flow, are sufficiently low not to confuse the issue. A dilution relationship with flow is more likely where the major source is of industrial/ urban origin (e.g. for Li, Rb, Cr, As, Co, MO, Ni on the southern rivers): i.e. this results from a combination of (a) the increased flux of rainfall and near surface runoff from the land during storm events diluting the point and diffuse sources of the elements and (b) the point and diffuse source contributions being sufficiently high to mask other inputs at high river discharges. An increase with flow is more common when the main source is mineralogical/diffuse rather than industrial (e.g. MO, Ni, Pb, Al, Fe on the northern rivers): i.e. the micro-particulate materials passing through the filters and the mobilised trace elements transferred to the rivers at high discharges predominates over the point and diffuse source contributions.

The above factors result in a number of trace

elements showing contrasting behaviours on the northern and southern rivers (Table 1; e.g. MO, Ni). Not all of the trace elements show straightforward changes with flow. A number show mixed behaviours (see Table 1) either with storm flow and base flow concentrations being similar at most sites, or with variable behaviour for northern and/or southern rivers. Elements with a mixed behaviour, as expected, are mainly those with a significant AAP fraction (e.g. Cr, As, Co, Mn on the cleaner northern rivers).

4.3. Relationships between dissolved and AAP JLactions

The various trace elements show very different partitioning between dissolved and particulate

Table 2 Correlation coefficients for AAP fractions of aluminium and nickel with dissolved (Diss) and acid available (dissolved plus acid available particulate) concentrations, flow, suspended solids (SS) and dissolved times suspended solids (Diss.SS)

Diss AA DissSS Flow SS

Aluminium Aire 0.2 1.0 0.8 0.8 0.8 Calder 0.3 1.0 0.7 0.9 0.9 Don 0.5 1.0 0.8 0.7 0.6 Derwent -0.3 0.6 0.2 0.4 -0.3 Nidd -0.1 0.5 0.6 0.6 0.2 Ouse 0.2 0.9 0.8 0.9 0.8 Upper Swale 0.2 I.0 I.0 I .o 1.0 Lower Swale -0.0 0.8 0.6 0.9 0.3 Trent -0.4 0.1 -0.0 -0.1 -0.6 Ure 0.5 0.9 0.6 0.8 0.8 Wharf 0.3 0.9 0.5 0.8 0.9

Nickel Aire -0.3 0.9 0.8 0.9 0.8 Calder -0.2 I.0 0.7 0.9 0.8 Don -0.6 0.3 0.8 0.7 0.5 Derwent 0.2 0.9 0.4 0.7 0.4 Nidd -0.2 0.7 0.6 0.7 0.6 Ouse -0.1 0.9 0.8 0.9 0.6 Upper Swale 0.1 I.0 I.0 I .o 0.9 Lower Swale 0.1 I.0 0.8 0.9 0.7 Trent -0.5 0.1 0.5 0.1 -0.0 Ure 0.2 0.9 0.7 0.9 0.7 Wharf 0.3 I.0 0.5 0.8 0.9

Values above 0.2 are significant at the 95% level (assuming a normal distribution).

330 C. Neal et al. / The Science of’ the Total Environment 194/195 (1997) 321~343

phases. It is important that this partitioning is characterised since different transport mechanisms act on the two fractions; the particulate fraction is associated with suspended sediment transport whereas the dissolved fraction moves with the main water body. A common modelling approach is to use an empirical equilibrium-like expression relating dissolved and particulate fractions to suspended solid concentrations via a partition coefficient (Schnoor et al., 1987).

Dissolved Cone x Kp

= (Particulate Cone/Suspended Solids) (1) where K, is the partition coefficient. Note that K, is not a true equilibrium coefficient, but is a river dependent empirical term which depends on factors such as pH and temperature and is affected by suspended solid concentrations (Gunn et al., 1992; Ambrose et al., 1991). The approach is straightforward and easily implemented within a modelling framework, but opinions vary as to its usefulness and validity (Bourg, 1987; Gunn et al., 1992; De Vries and Bakker, 1996).

In this section, the primary aims are (a) to summarise the nature of the observed links between the AAP fraction and the dissolved fraction, suspended solids and flow, and (b) to consider whether the partition relationship (Eq. (1)) provides an adequate description of the observations. To achieve this, inter-relationships between AAP fractions and other variables are examined and used to evaluate empirical links between them. These links are compared with the partition coefficient approach to see whether there are other similar or better descriptors. The properties of the estimated partition coefficients are also examined; K, estimates are calculated for each of the samples and temporal and regional variability is examined. Note that in applying Eq. (1) here, it is assumed that the AAP fraction equates to particulate concentration.

Fig. 4 shows typical inter-relationships for Al and Ni including (a) AAP and dissolved, (b) AAP and total, (c) AAP and how, (d) AAP and suspended solids. AAP fractions tend to show positive corre- lations with suspended solids, the acid available fraction and flow but with varying degrees of scatter. For nickel, the AAP fraction is most closely

related to suspended solids; the scatter seen for relationships with flow and total concentration is greater. For aluminium, the AAP relationships with suspended solids and flow are very similar to nickel. However, the link with total concentration is very much tighter because only a small proportion of aluminium is in dissolved form.

Fig. 5 presents the relationships between (1) AAP and (dissolved x suspended solids), and (2) dissolved and (AAP/suspended solids) for a selection of metals (Al, Pb, Mn, Ni). If a partition coefficient approach is a valid description of the river system then both of these plots should be linear. The plots showing the first set of relationships illustrate the degree to which Eq. (1) could be used to predict AAP concentrations from dissolved and suspended solid concentrations. The second set of plots is used to illustrate the link with dissolved concentrations. Comparing the two sets of plots, there is an approximate linear relationship for AAP with (dissolved x suspended solids), but hardly any relationship for dissolved with the ratio of AAP to suspended solids. This difference arises because most of the variation in AAP concentrations relates to suspended solid concentrations; the role of dissolved concentrations is minimal. Thus, although Eq. (1) gives a reasonable description of AAP concentrations there is very little indication that any empirical equilibrium really holds.

It is debateable whether or not Eq. (1) provides any improvement over the use of simple regression relationships such as one to link AAP fractions and suspended solids or flows. Correlation coefficients were calculated for the above relationships. On an average, AAP and suspended solids had a similar or higher correlation than AAP and (dissolved x suspended solids) (Table 2). For determinands with very little dissolved fraction the correlation between total and AAP was also high. Note that correlation coefficients can be sensitive to outlier points and so some caution must be used in interpreting them.

Estimates of the partition coefficients were calculated for each of the trace elements (Table 3). At each site there is considerable scatter (typically the maximum value is around 20 times the mean). There are also significant differences between site aver- ages, even for sites on similar types of river (the

C. Neal et al. / The Science of the Totul Erwironrnrnt 194;195 (1997) 321-343 331

Dissolved Dissolved

al

Total

a 9 000

500 l4!!cLl

500 . P*

0 5;; 0 1000 1500 2000 2500

100 260 360 460 Flow

d 260 460 600 0 260 460 660 Suspended Solids Suspended Solids

Aire

?I;

60

Total

0 0 20 40 60 80

I l Ni I

”

l . *

160 200 360 460 Flow

Derwent

Fig. 4. Relationships between AAP fractions and (a) dissolved, (b) total, (c) flow, (d) suspended solids for aluminium and nickel. A I:1 line is marked for graphs (b). The different colours depict the different rivers; colours are as shown in the text at the base. Units are jig/l except for Row (m’/s).


0 5000 15000 25000 Dissolved x SS

0 50 100 150 AAPISS

250

0 0 500 1000 1500 2000

Dissolved x SS

l Mn .

lOc.IOO 20600 30600 Dissolved x SS

3oT-;“i 0 500 1000 1500

Dissolved x SS

15- : Pb

z 1 lo- .

.

0 2 4 6 AAPISS

.

0 0 5 10 15 20 25

AAPISS

14.’ - l Ni

1 . .

.

. .

. .

* .

I -

0.0 0.5 1.0 1.5 2.0 2.5 3.0 AAP I SS

Fig. 5. Partition coefficient equilibrium relationships for the Aire and Ouse. Pairs of graphs are presented for Al, Pb, Mn and Ni. The left column of graphs shows AAP fractions plotted against (dissolved fraction x suspended solids (SS)). The right hand column shows dissolved concentrations against the ratio of AAP to suspended solids. Both sets of graphs should show linear relationships if an empirical equilibrium holds. Units are mg/l for SS and pg/l for the trace element fractions. Samples from the Aire are shown in black, those from the Ouse are grey.

C. Neal et al. / The Science of’the Total Environmrnt 194/195 (1997) 321-343

0 20 40 60 80100 2 4 6 810 50 150 250 I .

~

Ni (dis)

Ba (dis) L-J Whatfe

Fig. 6. A matrix of scatter plots showing a range of trace element inter-relationships for the northern rivers. Dissolved concentrations of each of the trace elements are plotted against all the other elements. The different colours denote the different river sites (see text at base). Units are pg/l.

C. Neal et al. / The Science of‘ the Total Environment 194/195 (1997) 321-343 333

Table 3 Mean values of partition coefficients (m’ kg.‘) for the LOIS sampling sites

Aire Calder Don Derwent Nidd Ouse Upper Swale Lower Swale Trent Ure Wharf

Al As Ba Cr Co Cu Fe Pb Mn Ni Zn SS

197 16.0 31 83 12 46 283 356 50 34 38 21 318 14.8 32 78 6 72 271 389 8 48 93 26 293 14.9 22 94 21 33 829 628 367 20 61 36

92 23.6 4 82 34 14 774 617 85 78 149 19 43 9.3 15 37 46 104 120 383 133 41 180 16 56 19.5 13 58 44 23 213 401 289 50 174 29 89 3.5 11 127 61 121 170 323 204 72 300 23 53 9.2 14 48 33 30 218 339 106 51 251 45

112 2.9 8 44 21 28 399 350 170 9 42 28 73 20.2 7 97 54 27 198 566 349 75 590 15 85 1.5 8 105 82 57 180 460 232 79 451 16

Concentrations of suspended solids (SS) are also given (mg/l)

range of values was about three times the overall average), as is observed for other regions (Ambrose et al., 1991; Delos et al., 1984; Gunn et al., 1992; De Vries and Bakker, 1996)

To conclude, the data shows only weak relationships both between dissolved and AAP fractions and between these fractions and measures such as suspended solids and flow. The common partition coefficient approach is not necessarily a better description of the observed variability than many of the other variables.

4.4. Relutionships between trace elements

An examination of the relationships between the different trace elements can identify groups of closely associated determinands and provide insights into common sources and/or chemical processes. The large number of determinands and sites means that it is only possible to summarise the main characteristics of the data. The data has been examined using matrices of scatter plots such as are illustrated in Fig. 6. Within these diagrams, data for different sampling points are plotted using different colours. For each graph, the y-axis determinand is given by that listed in one of the boxes on the same row, while the x-axis determinand is given by that listed in the same column. The numbers provided in the determinand box corresponds to the range of concentrations plotted. The plots are simply visual presentations of what would normally be represented as a series of standard correlation

matrices (one for each river site). These plots are preferred to the use of correlation coefficients as (a) they provide a much more comprehensive understanding of the data and of the differences between the sampling sites, (b) they are less influenced by outlier values and (c) they show direct comparison of chemical trends and ranges of scatter for the different rivers. To simplify matters, dissolved and AAP fractions are considered separately.

4.4.1. Dissolved components A complex range of relationships are observed

between the dissolved trace element fractions (Fig. 6). Four main classifications of the scatter plots are used to help characterise these relationships. These are necessarily a simplification of the true picture, but they are nevertheless useful. Fig. 7 provides an illustration of each of the types which are described below.

Type 1 A single straight line increasing relationship. In this case, the same relationship is seen at all river sites.

Type 2 A series of increasing relationships, often linear or near-linear. This is similar to type 1 behaviour, but the gradients of the relationships are dependent on the location.

Type 3 Decreasing relationships between determinands, usually fairly non-linear

C. Neal et al. I The Science of’thr Total Enaironment 194/195 (1997) 321-343

00800900P00Z 0 08 09 OP OZ 0 091 OS 0

88888O lObCQCU--

0 (ifin) “04

oooogo L33887

(NW ~04

336 C. Neal et al. 1 The Science of the Total Enkwment 194/195 (1997) 321-343

omoo 6000 tom3 0 10002000 0 10203040

,1

c

ab

f-l . .

-500 500 15002500 -1 12345

Aire Caider Don &per SW&? ‘b. Trent

Derwent Nidd Wharfe

Fig. 9. Scatter plots showing trace element inter-relationships for AAP fractions. Many show a type I behaviour, i.e. the same linear relationship on all rivers. Units are pg/l.

C. Neal et al. I The Science of’ the Total Enaironment l94/195 (1997) 321-343 331

(inverse/exponential) in appearance.

Type 4 A random scatter.

A typical trace element might show type 2 relationships with one group of elements, type 3 relationships with another set of elements, and no relationship (type 4) with the rest. Examination of the data indicates in this study that different groupings of elements occur in the northern and southern systems.

For the southern rivers (a) Fe-Pb show a type 1 relationship with each other; (b) Sr-B-Li-Rb-Mo-As-Ni-Cr-Mn show a type 2 relationship with each other (Fig. 8); (c) Al and Zn show no clear links with any other element. For the northern rivers (a) Fe-Ni show a type 1 relationship with each other (Fig. 6); (b) Sr-Ba-Li-Rb-B show type 2 relationships with each other (Fig. 8); (c) Zn, MO, As, Cr and Mn show no clear links with any other element (Fig. 6). For both northern and southern rivers, type 3

relationships are observed between some members of groups (a) and (b) (e.g. Fig. 6).

Note that the above lists do not categorise all of the inter-relationships. Although type 1 and type 2 behaviours are clear in many cases, many of the other links are indistinct and much more difficult to characterise (Fig. 6). Often there is considerable scatter and data fall between two of the types of behaviour. For example, on the northern rivers Al-Pb-Cr-Ni-Mn probably have a type 1 relationship with one another and with Fe-Ni, but this is obscured by a high level of scatter.

Despite the apparent complexity, the above groupings suggest a simple underlying structure. To a first approximation, elements which increase with flow demonstrate type 1 relationships with one another, although often with considerable scatter. Elements which dilute with increasing flow tend to show type 2 relationships with one another; these are often relatively tight relationships. Elements with mixed flow relationships

tend to have the most scattered links and to show few associations.

4.4.2. Acid available particulate components For the AAP fraction, data can only be provided

when there is sufficient difference between the dissolved and the acid available fraction for analytical errors to become insignificant: the AAP fraction is calculated as the difference of two laboratory measurements, and in some cases when the dissolved and the acid available fraction are of similar size there can be a significant proportion of nega- tive AAP values. Because of this limitation, only AAP fractions for Al, Fe, Mn, Co, Ni, Ba, Pb and Cr are examined (Fig. 9).

As expected, most of the above show a type 1 behaviour in keeping with the increasing flow-relationship which is seen for the AAP fractions. The tightest links are for Al, Fe, Mn, Co, and Ni. For Ba and Pb, there is a split between the northern and southern rivers (i.e. two straight lines), reflecting different source types. For Cr, relationships are more scattered and samples from the Swale and Ouse system are distinguished by their low concentrations relative to the other sites.

5. Implications

A number of factors contribute to produce the observed trace element relationships. These include:- (1) Hydrological controls: i.e. changes associated

with flow; (2) Source input variations: e.g. regional and tem-

poral differences in composition and volume; (3) Chemical controls: e.g. equilibrium or kinetic

reactions involving precipitation or sediment- solution interactions;

(4) Analytical errors: e.g. associated with the artificial cut off between dissolved and AAP phases.

In the following three subsections, the considerable structure contained in the trace element data is interpreted in relation to these factors. Their relative importance and the implications for rep- resentation of dominant processes and develop- ment of the modelling programme are considered.


5.1. The role of hydrological controls.

The LOIS results point to the importance of hydrological processes in determining both dissolved and AAP trace element concentrations in the Humber rivers. These processes play a critical role in determining the dynamic variations in trace element concentrations. For example, the dilution relationships observed for most dissolved components on the industrial/urban southern rivers are consistent with dilution of point source inputs from industry and sewage works. Also, the rise in particulate concentrations with flow, links in with increased levels of suspended solids at high flows. Furthermore, the linear relationships described above suggest that hydrological fluctuations have similar effects on a number of species. In particular, two main groups can be identified within which very similar flow related behaviours are observed. These are (a) the dissolved trace elements which dilute with flow and (b) the AAP fractions.

For the dissolved trace elements which dilute with flow, the river systems are behaving as if they derive from a mixture of two water types (or endmembers; see Fig. 8). The two endmembers include one corresponding to typical storm flow waters and another representing base flow chemistry. The latter may be thought of as a composite of the point source inputs, net release from bed sediments and ground water sources. The spread of gradients in the inter-relationships seen for many of the dissolved elements (Fig. 8) suggests that the base flow water type is particularly location dependent. This ties in with regional variations in the contributions of point sources related to the industrial base and the population density. What is remarkable is that this base flow endmember shows high consistency over time for a given river system (hence the near straight line relationships). Although the endmembers reflect the integrated effect of many inputs, there appears to be relatively little time variation in the base flow water which results.

The dissolved trace elements that dilute with flow appear to demonstrate near conservative behaviour: i.e. little interaction with other elements or with particulate fractions. This is suggested because (a) linear relationships exist with the conservative chloride ion (Fig. 8) and (b) near-linear relation-

ships are observed between determinands even where they have very different geochemical origins and hydrochemical properties. Scatter about the straight line relationships may indicate that some non-conservative reactions take place. However, to a first approximation, hydrological factors are the dominant control. This feature has also been observed for the major ions in the LOIS rivers (Jarvie et al., 1997~).

The above observations raise the question of whether a mixing model would be a useful and appropriate approach for modelling trace elements in these river systems. A mixing model is a very simple way of viewing a system. A sampled water is considered to derive from a mixture of chemically distinct water types (e.g. soil waters, ground waters, sewage effluents) whose composition and contributing volume may vary over time and space (Neal et al., 1990; Robson, 1993; Christophersen et al., 1990, 1993). The simplest case is for conservative mixing to occur between two water types (endmembers) of fixed composition (two component mixing). In this case, different determinands would be expected to display linear relationships with one another. In more complex situations, there may be chemical reactions that take place when mixing occurs, the endmembers may vary with time, and the number of endmembers may be large. For this more complex case, the resultant relationships between determinands may be very varied (linear or non-linear). For the dissolved trace elements which dilute with flow, a conservative model seems appropriate in that it provides a simple explanation of the observed inter-relationships. For these components, the main modelling steps would be to (1) identify the endmember chemistries, and (2) characterise the time variation in endmember mixing proportions, ideally by linking the endmembers to flow. From a modelling point of view it may be more sensible to use multiple endmembers corresponding to known point source inputs rather than an empirically derived base flow endmember. If this is the case then it will be necessary to consider whether the processes occurring when point sources and river waters mix are also conservative. It is possible that non-conservative processes occur when very different water types mix, but that the resulting base flow water type then mixes conservatively with storm waters. The most straightforward approach to resolving this will

C. Neal et al. /// The Science of’ the Total Environment 194/195 (1997) 321-343 339

be to apply river models and test whether conservative mixing concepts hold (Lewis et al., 1997).

Particulate components also display multilineal relationships consistent with mixing processes. However, it is highly unlikely that conservative behaviour is occurring within the main water body for these components. Changing hydrological conditions mean that suspended solids and associated particulate fractions are continually being deposited to or resuspended from the river bed. Non-conservative behaviour is also indicated by the non-linear relationships arising between this group and chloride and the dissolved trace elements which dilute with flow. Linear relationships would be expected if there were just two endmembers mixing conservatively.

For the particulates, it seems more appropriate to view AAP concentration variations in relation to sediment transport. In this case, sediment transport would be modelled and particulate concentrations would be directly related to sediments. Using this approach, the river would be viewed as incorporating two partially independent river transport processes. The first would be the transport and conservative mixing of dissolved components. The second would be the modelling of sediment movement and the associated particulate fractions. It would be necessary to test, using river models, whether it is of value to link AAP and dissolved concentrations using the partition coefficient approach. An alternative that should be allowed for is that AAP and dissolved components behave independently in freshwater rivers.

Note, that inter-relationships between different trace elements tend to be much tighter and more linear than the links with flow. Hydrologic controls are a strong driving force, but the link between endmember proportions and flow is almost certainly non-linear and subject to hys- teresis, memory and washout effects. Ideally, river models will need to try and allow for these factors. Such effects may be highly significant when load estimation is necessary (Webb et al., 1997).

5.2. The role of chemical processes

Whilst hydrological processes clearly play a major role in the Humber rivers, the role of chemical

controls within the river remains uncertain due to a combination of the large and heterogeneous nature of the catchments and the problems associated with filtration. The relatively weak relationships between the dissolved concentrations and the ratio of AAP to suspended solids provides little field indication of riverine chemical controls. Thus, chemical controls may well be a second order effect compared with hydrological factors within these rivers. However, in many instances there is significant scatter in the relationships between the ions and it may be that this arises because of such controls.

The use of partition coefficients within river and estuarine models is common place (Schnoor et al., 1987; Ambrose et al., 1991). Nevertheless, the LOIS data shows limitations to the approach for the Humber system. The partition coefficient approach (Eq. (1)) is likely to provide a rough measure of long term average partitioning, but may not fully incorporate short term dynamics. The significant site to site differences in K,, will also be problematical. If models are to be applied to new river systems then the K,, values will need to be linked to other factors. One way forward may be to consider extensions to the partition equilibrium approach, either by incorporating rate equations and effects relating to suspended solids and salinity (e.g. Gunn et al., 1992) or by making allowance for binding with organics (De Vries and Bakker, 1996). Nevertheless, although the empirical partition coefficient approach to modelling has the appeal of being straightforward to apply, it is clear that this approach is of very dubious merit.

An alternative to the partition coefficient approach would be to use models based on speciation reactions to describe chemical processes. At present, this is unrealistic because (1) laboratory techniques for determining metal speciation are not suited to large-scale analysis of samples, (2) calculation of the metal speciation is dubious because the trace metal-organic and metal-hydroxide/inorganic ligand system is very complex and important thermodynamic information remains missing and (3) present regional surveys of the type presented here have collected data incom- patible with the approach. This option will only

340 C. Neal et al. / The Science of’ the Total Environment 194/195 (1997) 321-343

be viable in situations where much more detailed data is available and where there is strong evi- dence of the importance of chemical reactions.

5.3. The analytical problem

The analytical and filtration techniques used only allow a crude measure of metal distribution. This occurs because (1) the total acid available concentrations are only operationally defined and (2) the filters used are inefficient in removing microparticles.

It is possible that much of the scatter observed in the data presented here relates to the poor separation between dissolved and acid reactive particulate components and that many of the relationships would be much clearer if there were no analytical limitations. For example, these problems may well affect the evaluation of the partition coefficient approach (Eq. (1)). Particu- late concentrations have been equated with the AAP fraction but these two measures could differ (a) because of fine particulate matter included in the dissolved component and excluded from the AAP fraction, (b) because only the acid available sector of the particulate matter is measured, and (c) the mineral composition of the sediment changes along the river length and the extent of suspended sediment reactivity to the acid extractant might vary over space and time. Alternatively (or in addition) there are major problems con- cerning accurately sampling suspended sediments as these are very variable across a river section. In the present study only one sample has been taken for logistical reasons and it is possible that the time taken for steady state conditions to be achieved between the sediments and the river water is sufficiently long for the suspended sediment sampling error to be large.

It may be that if the above problems were resolved then different relationships between dissolved and particulate phases of the same trace element would emerge. Furthermore, scatter seen in the inter-element relationships may also prove to have an analytical origin.

In terms of environmental monitoring and management, there remains a major question mark over what critical measurements are re-

quired to describe the harmful effect trace elements have on biota: this applies to riverine, estuarine and coastal shelf systems alike. Presently, water quality guidelines and consents have to be based on crude measures involving set filter sizes and set extractant procedures as there is nothing more appropriate at the moment. How- ever, it is important, even with these crude measures, that there is consistency in measurement. Clearly one important area for standardisation is in the use of set filter types and set filtration techniques. For example, successive filtrations of a given water using the same filter paper result in different amounts of fine particulate components being collected. Unfortunately, there is no consen- sus as to methodology (BSI, 1991, 1993). This remains a stumbling block to rigorous environmental monitoring and management programmes for the trace elements.

6. Concluding remarks

The LOIS chemical data for the Humber rivers provides important information on the trace element chemistry which compliments other data sources such as NRA records and the Har- monised Monitoring Scheme (Robson and Neal, 1997a). The collected data is relatively intensive; samples are frequent and are representative of a wide range of flows at the key sites. The information gained is important in relation to estimation of fluxes to the North Sea (Jarvie et al., 1997a) and to critical loads estimation (Webb et al., 1997) both European issues.

The results of this study show, at a descriptive level, simple but striking regional differences relating to the interplay of geological, industrial and urban source contributions with hydrological factors. However, at a more detailed level, it appears to be much more difficult to pinpoint what is occurring, and describing such a wealth of information in a clear straightforward way is a major task. The degree of complexity probably relates to the highly heterogeneous nature of the system. One important way forward will be to bring together different types of information (e.g. water quality, geology, relief, hydrology, land use,

C. Neal et al. ! The Science of the Total Encironment 194/195 (1997) 321-343 341

groundwater) within a GIS and statistical analysis framework. While the methods are presently being developed within the LOIS programme (Rob- son and Neal, 1997b; Robson et al., 1996) this area of research has not been sufficiently developed for use in this study.

At present, environmental quality objectives and environmental legislation tend to be stated in terms of total and dissolved concentrations. This provides a practical approach to controlling the river environment. However, total and dissolved fractions are unsuited to describing chemical equilibrium in such complex systems. Also, the form of an element is known to be the main influence on its fate, behaviour and effect on aquatic life (Ravenscroft and Gardner, 1992). Thus, detailed process based studies are called for. Such studies are impractical at the large scale, but without them key controls may be missed. A major difficulty which must be addressed is the issue of relating theoretical results to the day to day practical monitoring which is used as the basis of river management.

The hydrological mixing of the various river inputs is perhaps the most important process controlling trace element concentrations (and also major ions; see Jarvie et al., 1997~). The observed relationships thus result from a mixture of hydrological and source area controls. The catchments are large and heterogeneous and during flow events the proportion of water derived from each tributary will vary because of the different dis- tances and hence travel times to that point. Like- wise, the velocities of the tributaries and reaches will vary. Under this hypothesis, chemical controls remain uncertain and they may well be of secondary importance in the Humber rivers. This view is not the only interpretation, but it is probably the simplest view which is consistent with trace element and other chemical data. In modelling terms, simplicity is advisable; complexity that is not backed up by data leads to over- parameterisation and uncertainty. We seek the simplest model consistent with the observations and with scientific understanding.

In order to take our understanding further, modelling work should be undertaken (1) to test the feasibility of using a conservative mixing ap-

preach within riverine models and (2) to allow comparison with a partition coefficient approach. For the conservative modelling approach, dissolved components would be decoupled from AAP components and treated independently. This would provide information as to whether chemical equilibrium processes are important when spe- cific sources combine and would provide further insights into the relative roles of chemical and mixing processes.

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