River Mease Road Runoff: Impacts on Water and Sediment Quality Final Report Client: Natural England APEM Ref 413482 March 2016 T

River Mease Road Runoff: impacts on water and sediment quality

Final Report

Client: Natural England

APEM Ref 413482

March 2016

This project is part of the IPENS programme (LIFE11NAT/UK/000384IPENS) which is financially supported by LIFE, a financial instrument of the European Community

Registered in England No. 2530851, Registered Address Riverview A17 Embankment Business Park, Heaton Mersey, Stockport, SK4 3GN NJ Rogers1, WH Blake1*, R Goddard1, S Comber1, R Hartley1, S Lewin1 and P.Stone2

1Catchment and River Science Research Group (CaRiS), School of Geography, Earth and Environmental Sciences, Plymouth University, PL4 8AA (*[email protected])

2APEM Ltd

Client: Natural England

Address: APEX Court

City Link

Nottingham

NG2 4LA

Project reference:

Date of issue: ______

Project Director: Dr David Fraser

Project Manager: Dr Peter Stone

Other: Professor Will Blake, Dr Nicola Rogers ______

APEM Ltd Riverview A17 Embankment Business Park Heaton Mersey Stockport SK4 3GN

Tel: 0161 442 8938 Fax: 0161 432 6083

Registered in England No. 2530851

Registered in England No. 2530851, Registered Address Riverview A17 Embankment Business Park, Heaton Mersey, Stockport, SK4 3GN Revision and Amendment Register

Version Date Section(s) Page(s) Summary of Changes Approved by Number

1 10/2/15 5 59 DRAFT for client comment PS

2 10/4/15 5 67 FINAL PS 3 28/4/15 5 67 Final following client comment PS

1. Contents

1. Introduction ...... 7

1.1 Project Brief ...... 7

1.2 Objectives ...... 8

1.3 Review of Road Run-Off and Road-Derived Contaminants ...... 10

1.4 Water Quality and Bioavailability of Metals...... 11

1.5 Sediment Quality ...... 15

2. Methodology ...... 15

2.1 Site Selection and Sediment Collection ...... 15

2.2 Field monitoring ...... 16

2.3 Water quality chemical analyses ...... 16

2.4 Sediment processing and chemical analyses ...... 20

2.5 Walkover Survey to Verify Specific Sources...... 20

3. Results and Discussion ...... 21

3.1 Stream monitoring record and context of water samples ...... 21

3.2 Water Quality Monitoring for Summer and Winter Storm Events ...... 28

3.2.1 Summer storms ...... 30

3.2.2 Winter storms ...... 31

3.2.1 Bioavailability of Metals ...... 37

3.3 Stream sediment and road dust metal content ...... 38

3.4 Fingerprinting road sediment inputs to channel sediment...... 53

3.5 Walkover survey to identify sources of diffuse pollution ...... 57

3.5.1 Wet weather sampling ...... 57

3.5.2 Bioavailability of metals from conduit sources ...... 58

4. Summary and Recommendations ...... 61

5. References ...... 64

List of Figures

Figure 1: Schematic diagram of the biotic ligand model (BLM) showing the inter-relationships between chemistry, physiology, toxicology and the needs of regulatory agencies (re-drawn from Di Toro et al 2001 & Paquin et al 2002)...... 13

Figure 2: All road/stream interaction points with numbered sampling locations for road dust and sediment quality (up and downstream of road crossings)...... 18

Figure 3: Location of Troll 9500 sondes with probes monitoring water depth, electrical conductance and turbidity plus the ISCO automatic water samplers ...... 19

Figure 4: air temperature (AIR T), C; hydrograph (DEPTH), m; and conductivity (SEC), µS; trace for the monitoring point at Packington showing storm flow events and corresponding SEC response. Note SEC peaks in storm flow after air temperature dropped below 0°C which is linked to road gritting ...... 22

Figure 5: Hydrograph and SEC for storm event sampled 07/10/14 ...... 24

Figure 6: Hydrograph and SEC for storm event sampled 15/10/14 ...... 25

Figure 7: Hydrograph and SEC for storm event sampled 07/11/14 ...... 26

Figure 8: Hydrograph and SEC for storm events sampled 10/12/2014 and 11/12/2014 ...... 27

Figure 9: Baseline dissolved metal concentrations for copper, zinc and nickel for ISCO samples collected on 3/09/2014/. Water depth and conductivity are also shown...... 29

Figure 10: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 04/10/2014. Water depth and conductivity are also shown...... 32

Figure 11: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 07/10/2014. Water depth and conductivity are also shown...... 33

Figure 12: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 07/11/2014. Water depth and conductivity are also shown...... 34

Figure 13: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 09&10/12/2014. Water depth and conductivity are also shown ...... 35

Figure 14: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 1/12/2014. Water depth and conductivity are also shown . 36

Figure 15: Bulk concentrations of (a) copper zinc and (b) zinc measured in road dust samples from across the system, categorised by road size ...... 42

Figure 16 Concentrations of (a) Cr, (b) Fe, (c) Cd, (d) Pb, (e) Rh and (f) Pt, measured in road dust samples from across the system, categorised by road size ...... 44

Figure 17: Bulk concentrations of (a) copper and (b) zinc measured in stream sediment downstream of road crossings of different category ...... 46

Figure 18: Concentrations of (a) Pb (b) Rh and (c) Pt measured in stream sediment downstream of road crossings of different category ...... 49

Figure 19: Concentrations of (a) Ni and (b) Cd measured in stream sediment downstream of road crossings of different category ...... 50

Figure 20: The spatial pattern of metal loadings in Gilwiskaw Brook and the wider catchment showing linkages between contaminant concentrations (mg/kg) for copper (Cu) and traffic density according to road classification...... 51

Figure 21: The spatial pattern of metal loadings in Gilwiskaw Brook and the wider catchment showing linkages between contaminant concentration (mg/kg) for zinc (Zn) and traffic density according to road classification...... 52

Figure 22: Output of the Discriminant Function Analysis test showing ability of the fingerprint properties to discriminate the identified sources where 1 is the catchment material, 2 is the A road material, 3 is the B road material, 4 the minor road material and 5 the urban material. Test run in IBM SPSS entering independent variables together to maximise dimensionality of the fingerprints...... 54

Figure 23: Locations of wet weather samples collected on 20th February 2015 ...... 59

List of Tables

Table 1: Examples of contaminant concentrations in road dust and road runoff sediment in the UK with ambient background concentrations in soils from rural locations (from Taylor et al 2014) ...... 10

Table 2 Recommended freshwater standards for selected metals and Specific Pollutants ... 12

Table 3 Canadian Sediment Quality Guidelines for Metals (Freshwater) ...... 15

Table 4: Details of storm events sampled by the ISCO automatic water samplers...... 21

Table 5 Selected sediment metals concentrations (mg/kg): values exceeding CCME ISQG have been highlighted in bold. Values exceeding the PEL have been highlighted in red...... 40

Table 6 Correlations between copper and zinc concentrations in road dusts and indicator metals for road run off ...... 43

Table 7 Correlations between copper and zinc concentrations in stream sediments and indicator metals for road run off ...... 47

Table 8: Results of Kruskall-Wallis test for difference (run using IBM SPSS statistics version 21 software) ...... 55

Table 9: Nominal sediment proportions at each downstream stream/river site (see also Figure 2), estimated by the unmixing model. Data rounded to nearest 5% for clarity. Missing data due to site inaccessibility ...... 56

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1. Introduction

1.1 Project Brief

The River Mease and the Gilwiskaw Brook have been designated as a Special Area of Conservation (SAC) and under the EU Habitats Directive, and a Site of Special Scientific Interest (SSSI) under the Wildlife and Countryside Act. Previous work undertaken by APEM and Plymouth University in the River Mease catchment has identified the importance of roads as conveyors of fine sediment, and sources of contaminates to the river and recognised the potential impacts of sediment on water quality and river health (Blake et al 2014). Sediment fingerprinting projects during summer 2012 and winter 2013 investigated sediment source apportionment within six sub-catchments of the Mease where siltation is impacting ecological status. The data suggested that a greater proportion of material delivered from sources closer to the channel, e.g. channel bank erosion, remained in channel storage whereas material delivered from actively eroding cultivated soil surfaces during major winter events was conveyed efficiently through the system to higher order, downstream channels. Roads were identified as key conveyance pathways delivering sediment washed off fields through gateways via roads to the streams. The markers used to illustrate these transport pathways were road contaminants that labelled the sediment in transit. These contaminants may have significant ecological impacts on water quality in their own right and clearly warranted further investigation.

A second project surveyed the sediment quality in the vicinity of the A42 crossing point with the River Mease at Measham and focused on monitoring water quality during storm events (Taylor et al 2014). The study demonstrated that sediment material and associated contaminants derived from the A42 road are reaching the Mease main channel via at least one outfall, and there are likely to be additional inputs upstream of the targeted study reach. The road was shown to be impacting on water and sediment quality with levels of Cr, Cu, Pb and Zn exceeding sediment quality guideline values for the protection of aquatic life. It was recommended that a wider evidence base be generated to support demand for a review of current infrastructure for detention of road contaminants by the appropriate authority (Taylor et al 2014).

To this end, a summertime survey (summer 2014) of baseline water quality in the reach of the Gilwiskaw Brook that flows under the Packington A42 road crossing was undertaken. In addition, a sediment quality assessment for copper and zinc, two key road contaminants, across a wider range of road/river crossing points was undertaken (Rogers et al., 2014).

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The summer study provided a robust water quality baseline (i.e. metal levels at low flow when road runoff was not entering the stream) against which to assess storm period water quality (reported in the present report). It was noted that while concentrations of copper and zinc were recorded to be above generic Environmental Quality Standards (EQS) levels for water both above and below the A42 crossing, copper and zinc concentrations did not exceed the new site-specific EQS, based on bioavailability. It was hypothesised that metal concentrations might increase at times of storm flow when road contaminants are flushed by rainwater off the local roads and into the Gilwiskaw Brook via drains. This hypothesis is tested by storm period data reported in the present study.

The summer period also provided a first insight into spatial patterns of road contaminants in the channel sediment across a range of road crossings in the River Mease river system. Patterns in copper and zinc showed elevated concentrations in the vicinity of A-road crossings and peak concentrations exceeded recommended guidelines for the protection of aquatic life. The spatial patterns in these two metals showed clear linkages between loading and traffic density (inferred by road class) and urban areas also contributed to contaminant signals due to areal extent of road networks. It was recommended that these patterns be compared to a wider range of known road-derived contaminants which would support interpretations from sediment fingerprinting approaches to assess relative amounts of road material entering the channel at different road/river intersections according to road class. Consequently, the present study aimed to provide a more comprehensive assessment of contaminants and their patterns across the River Mease system.

1.2 Objectives

Against the above context and baseline findings of the summer sampling campaign, the overall objectives of the road runoff investigation in the River Mease catchment are to deliver:

1. An understanding of the spatial extent of heavy metal contamination from road runoff along the River Mease channel with identification of areas where sediment quality exceeds guidelines for protection of aquatic life. This will allow a hierarchy of road impacts to be derived i.e. relative importance of unclassified rural lanes, urban road networks and main roads; and

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2. Evidence to test the hypothesis of road runoff driven water contamination events with maximum metal concentration values assessed against new bioavailability-based environmental quality guideline concentrations derived using the biotic ligand model (BLM).

Investigation to date has identified that there is a difference in the processes and delivery of diffuse pollution in the Mease catchment from agricultural land between summer and winter. Baseline concentrations of metals entering the River Mease channel from the A42 crossing point to the river at Packington were established and compared with hand- collected samples, which were collected after a minor rainfall event at this site in late September 2014. This investigation will consider both summer and winter derived pollution with respect to road runoff. This report describes the findings from the full study period (summer and winter) to tackle objectives 1 and 2 above. Full zinc and copper sediment quality data from sediment surveys across the catchment are also presented. The spatial patterns of zinc and copper contamination in found in these sediments are compared with data from a range of trace metals as indicators of road run-off.

The specific deliverables of this report are to:

1. Establish temporal patterns road-related metal pollution dynamics during storm events in the Gilwiskaw Brook at the A42 crossing point in Packington 2. Compare storm water concentrations of a suite of metals in the Gilwiskaw Brook to baseline concentrations, both above and below the main A42 crossing point with the river at Packington 3. Generate site-specific environmental quality standards (EQS) for selected metals using local water quality data and establish the bioavailability of these metals in baseline and storm water samples. 4. Provide a spatial survey of heavy metal contamination in road dust around the vicinity of a range of road/river crossing points and explore the broad metal concentration differences between upstream and downstream sediment in comparison to road dust samples and uncontaminated river sediment (from upstream control areas). 5. To evaluate the risk of sediment contamination to aquatic life by comparing to international sediment quality standards. 6. Provide spatial information on the impact and hierarchy of road derived inputs into the Mease using spatial patterns and sediment fingerprinting approaches.

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1.3 Review of Road Run-Off and Road-Derived Contaminants

Sources of road-derived contaminants, pathways for their entry to watercourses and potential toxic effects were extensively reviewed in an earlier report (Taylor et al 2014) and are only briefly summarised here. The literature suggests that major roads can be a source of a complex mixture of contaminants including vehicular-derived metals, and de-icing salts used during cold weather (as well as complex polyaromatic hydrocarbons which are not considered here). Many of these contaminants are associated with readily mobilised fine sediment fractions and exhibit elevated concentrations (above background) in road dusts. These particles are actively transported to aquatic systems during runoff events via drainage systems, with strong evidence of contaminant loading in runoff samples and immediate receiving waters. There is also evidence of the transport of road-derived particulates through catchment systems. Whilst sediment bound contaminants appear to dominate loadings in road runoff, transport in the dissolved phase can also be of importance in some environments. Of the metal contaminants of interest in the current work copper, zinc, lead, nickel and cadmium were all identified by Taylor et al as contaminants of concern derived directly from vehicle use (Table 1).

Table 1: Examples of contaminant concentrations in road dust and road runoff sediment in the UK with ambient background concentrations in soils from rural locations (from Taylor et al 2014)

Road Dust mg/kga Runoff sediment mg/kgb Background mg/kgc Cd 0 – 13 <1.0 – 1.01 0.39 Cu 16.4 – 6688 95.7 – 151 20.6 Ni 0 – 636 19 – 21.5 21 Pb 0 – 199 128 – 170 52.5 Zn 81 – 3164 401 – 487 81.3 Pd 0.026 – 0.45d <0.15 – <3.7 <0.002e Pt 0.027 – 0.41d <0.2 – <2.7 <0.002e a Charlesworth et al.(2003) b Moy and Crabtree (2003) c Barraclough (2007) d Jackson et al. (2007) e Prichard et al. (2009)

Emissions of Cu and Zn are association with tyre and brake wear and are likely to increase with increase traffic use/traffic volume Napier et al. (2008) Elevated concentrations of Ni in road dust is commonly associated with engine wear and anthropogenic inputs of Ni to freshwaters have almost doubled each decade since 1930 (Beasley and Kneale, 2002). Vehicle-derived concentrations of other potentially toxic metals such as Cd are likely to reduce owing to manufacturing restrictions imposed under the EU End of Life Vehicles

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Directive (2000/53/EC). Vehicle exhaust catalysts are a major source of the Platinum Group Elements (PGEs) (Pt, Pd, Rh, Ru) which commonly found to be elevated above background concentrations in road dust and roadside soil (Table 1). A general consistency in ratios between Pd, Pt and Rh in environmental samples across urban areas suggests that vehicles are a dominant source of PGE emission (Jackson et al. 2010; Prichard et al. 2009a) with clear spatial patterns evident in sediment concentrations, which trend towards higher values close to road sources (Prichard et al. 2008).

Contaminated runoff from road surfaces has been shown to discharge directly to surface waters (Moy and Crabtree 2003) and transport of road-derived contaminants by streams and rivers has been documented resulting in elevated levels of metals such as Pb and Cu (Carter et al. 2006; Carter et al. 2003; Prichard et al. 2008). Total metal loading was shown to be elevated in the first flush of runoff during an event (Wicke et al. 2012) due to the removal of trapped contaminants, This suggests that preceding dry weather may be an important factor to consider when studying contaminant runoff. (Helmreich et al. 2010; Wicke et al. 2012). The temporal dynamics of road dust transport and interactions in runoff solutions are thus important considerations when taking into account contaminant toxicity

The aquatic toxicity of road-related contaminants was reviewed by Beasley and Kneale (2002) and controlled studies have demonstrated the acute and chronic toxicity of these metals to macroinvertebrate species. Fewer studies focus on the bioaccumulation and toxicity of PGEs although some evidence to suggest bioavailability and sub-lethal effects at environmentally relevant concentrations (e.g Sures et al. 2001; Zimmermann et al. 2004). Whether road-derived contaminants exhibit toxicity in aquatic systems is dependent on a complex interaction of factors including chemical speciation, interaction between contaminants including salinity, and the environmental parameters in receiving waters. These factors are taken into consideration in the Environmental Quality Standards used for monitoring surface water and are described further in Section 1.4

1.4 Water Quality and Bioavailability of Metals

The Water Framework Directive (WFD) is a European Directive which introduces a planning process to manage, protect and improve the water environment (Directive 2000/60/EC). Recent updates to the WFD have set new water quality standards for nickel and lead as bioavailable concentrations. The UK has also set Environmental Quality Standards (EQS) for copper, zinc, and manganese as bioavailable metal concentrations. An EQS is the concentration of a chemical in the environment which should not be exceeded in order to 11

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protect the specific endpoint being considered, e.g. aquatic life. These new guidelines are summarised in Table 2.

Table 2 Recommended freshwater standards for selected metals and Specific Pollutants

Element Exposure Annual New EQS Existing EQS Source Statistic μg/L μg/L Cu Long-term Mean 1 1–28 (dissolved)** WFD-UKTAG 2013 (bioavailable)* Ni Long-term Mean 4 50-200 EA 2011 (bioavailable) (dissolved)** Zn Long-term Mean 10.9 8-125 (total) WFD-UKTAG 2013 (bioavailable) plus Ambient Background Concentration Mn Long-term Mean 123 30 (dissolved)** WFD-UKTAG 2013 (bioavailable) Pb 1.2 4-250 WFD-UKTAG 2008 (bioavailable) (dissolved)** Cr Annual Mean 4.7 (Cr III) 5-50 (Cr VI) WFD-UKTAG 2008 3.4 (Cr VI) (dissolved)*** (dissolved) Cd Annual Mean EU UK EA2011 0.08 - 0.25** 5.0 Fe Annual Mean 730 1000 (dissolved) EA2011 (total) As Annual Mean 50 50 (dissolved) EA2011 (dissolved) Al*** Short-term Mean 0.25 (PNEC) 10.0 (pH < 6.5) EA2007 25.0 (pH > 6.5) Long-term 0.05 (PNEC_ 15.0 (pH > 6.5) *Bioavailable means the fraction of the dissolved concentration likely to result in toxic effects ** Depends on water hardness *** For a generic risk approach, a median background concentration for UK rivers of 6.0μgl-1 could be added to the values given

Metal bioavailability depends on a number of physico-chemical parameters which govern metal speciation in solution and thus the potential for the toxic form of a metal to interact with a target organism (biological receptor). Metal ions (MZ+) can, for example, bind to dissolved

2+ organic carbon (DOC) or to other inorganic ligands such as carbonate ions (CO3 ), reducing their potential for binding with biological receptors. Additionally, other cations such as Ca2+ 12

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or H+ (low pH) can compete with the metal ions for binding sites at the biological receptor. These competing interactions reduce the ability of metal ions to bind to sites on the organism and initiate a toxic response.

It is not possible to measure bioavailable concentration of a metal directly and a number of models have been developed to predict the bioavailable concentrations of metals in natural waters (e.g. Pagenkopf 1983, Campbell 1996). One such model, the biotic ligand model (BLM), has been researched and developed over many years (e.g. Di Toro et al 2001, Paquin et al 2002, Niogi and Wood 2004) and is now available for a number of metals. The BLM uses chemical equilibrium modelling to describe the competing reactions of the free metal ion in natural waters and thus the ability of a metal to produce a toxic response in aquatic biota. This model is now utilised as the basis of a regulatory framework to assess metal bioavailability and water quality (Figure 1).

Figure 1: Schematic diagram of the biotic ligand model (BLM) showing the inter- relationships between chemistry, physiology, toxicology and the needs of regulatory agencies (re-drawn from Di Toro et al 2001 & Paquin et al 2002).

The relative complexity of the BLM however, makes it unwieldy as routine tool for regulatory requirements. To assist in assessing compliance with the new standards for bioavailable metals, the UK has developed a simplified metal bioavailability assessment model for each of the available metal BLMs. These models have subsequently been combined into a single tool, the Metal Bioavailability Assessment Tool (M-BAT) (WFD-UKTAG 2014). A similar

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‘user friendly’ BLM software tool had been developed by bio-met (a collaborative initiative led by the European Copper Institute, the International Zinc Association and the Nickel Producers Environmental Research Association) and is currently available from the bio-met website (http://bio-met.net/). The main parameters which influence metal bioavailability are pH, calcium concentration and DOC and calculations with in these models are based on these water quality parameters alone. Comparisons between simplified models such as the M-BAT and the full BLM have shown that the outputs of the simplified models are slightly precautionary compared to the full BLM model (WFD UKTAG 2014).

These software tools provide a simplified version of the BLM which requires no specialist software and can be routinely used by regulators to estimate the site-specific bioavailable concentration of metals at a given site. These can then be compared directly to the

EQSbioavailable to assess water quality and compliance to the WFD at that site. The UK M-BAT has been developed to cover the metals for which a bioavailable EQS has been derived, namely UK Specific Pollutants zinc, copper and manganese, and the EU Priority substance nickel. The Excel version of this software tool was expected to be available at the end of 2014, but at the time of writing had not been released on the WFD UKTAG website (http://www.wfduk.org/resources/rivers-lakes-metal-bioavailability-assessment-tool-m-bat accessed 05/02/2015). For analysis of the data presented in this report the ‘user friendly BLM software tool’ from bio-met was used to estimate site specific EQSs and bioavailable concentrations of copper, zinc, and nickel which are classified as Specific Pollutants under the WFD.

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1.5 Sediment Quality

The Water Quality Guidelines Task Group of the Canadian Council of Ministers of the Environment (CCME) have developed chemical concentrations recommended to support and maintain aquatic life associated with bed sediments (Table 3).

Table 3 Canadian Sediment Quality Guidelines for Metals (Freshwater)

Concentration mg/kg dry Element Date weight ISQG PEL Cr 37.3 90 1998 Cu 35.7 197 1998 Zn 123 315 1998 As 5.9 17 1998 Cd 0.6 3.5 1997 Hg 170 486 1997) Pb 35 91.3 1998 ISQG - Interim Sediment Quality Guideline PEL - Probable Effects Level

These values are derived from available scientific information on biological effects of sediment-associated chemicals and are intended to support the functioning of healthy ecosystems. The sediment quality guidelines protocol relies on the National Status and Trends Program approach and the Spiked-Sediment Toxicity Test approach (Canadian Council of Ministers of the Environment. (1995). The Interim Sediment Quality Guideline (ISQG) corresponds to threshold level effects below which adverse biological effects are not expected. The Probable Effects Level (PEL) corresponds to concentrations above which adverse biological effects are frequently found. There are currently no specific sediment quality guidelines for the UK and the Canadian guidelines have been used as a measure of sediment quality throughout this report.

2. Methodology

2.1 Site Selection and Sediment Collection

Twenty representative road crossings were selected in collaboration with the Natural England team (Figure 2). Based on our knowledge of the catchment and twin goals of assessing the impact of the road hierarchy and the footprint of the A42, a sampling along a ‘transect’ from the headwaters of the Gilwiskaw Brook was undertaken, with more intensive 15

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sampling in the Ashby de la Zouch area, into and down the Mease main channel. This allows us to capture the influence of a range of road types and the spatial extent of the urban and A42 inputs. At each site, upstream and downstream representative samples of bed sediment have been collected using the stilling well method, which was used in prior work in the catchment (Taylor et al, 2014). Two sites were inaccessible at the time of sampling thus the sampling has yielded 36 bed sediment samples for analysis where each comprises multiple samples collected from representative channel bed locations. The remaining resource was reallocated to repeat sampling of site 1, as detailed at Figure 2, through the winter season to explore changes in sediment quality through the winter period. Representative source materials (road sweepings), from the local road network has been collected at each site. One spatially-integrated sweep sample was collected for each site, wherein replication was achieved across sites of the same character, e.g. replication has been achieved for A roads, B roads and local roads (18 samples).

2.2 Field monitoring

Monitoring of temporal patterns of metal inputs from roads was achieved using Troll 9500 sondes with probes monitoring (i) water depth, (ii) electrical conductance (related to total dissolved solids) and, in the stream, (iii) turbidity (related to total suspended solids and/or discolouration) plus ISCO automatic water samplers equipped with glass bottle carousels (12 bottles per set). The sondes were stationed above and below the main identified input of road runoff at the A42 crossing point with Gilwiskaw Brook (Figure 3) in August 2014. The ISCO water samplers were installed on Wednesday 3rd September following receipt of specialist glass bottles (required for DOC analysis to support interpretation of metal bioavailability). The Trolls monitored stream conditions at 15 minute intervals and provided the storm hydrograph context for the water quality sampling. The ISCOs were set to trigger by a rise in water level, after which they captured samples at 30 minute intervals for 11 hours. Two samples were collected in each bottle to create an hourly window for each data point (11 bottles per carousel plus a control). Winter and summer storm events were targeted with a goal of 2 summer/autumn (pre road gritting) and 2 winter storms (post road gritting).

2.3 Water quality chemical analyses

Water samples were returned to the laboratory on ice within 24 hours of collection and fixed for storage and analysis. For analysis of metals, all glassware and plastic consumables were 16

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acid washed in 10% HNO3 and thoroughly rinsed with high purity water prior to use. For DOC measurement all glassware (including the ISCO autosampler glass bottles prior to field deployment) were washed in 10% HCl overnight and dried in a muffle furnace.

For analysis of total metals a well-mixed subsample of each water sample was digested in acid in a Mars microwave digestion system. For analysis of dissolved metals a second sample was filtered to < 0.45 µm and acidified. Water samples were analysed by ICP-OES and/or ICP-MS (as appropriate to concentration) for total and dissolved P, Ca, Mn, Fe, Ba, Cu, Zn, Al, P, B, V, Cr, As, Se, Mo, Ru, Rh, Pd, Ag, Cd, Sb, Pt, Tl and Pb using standard analytical methodology. Field blanks and matrix-matched experimental blanks were included with each batch of analysis. High background concentrations and contamination issues were experienced for some metals, most notably aluminium and zinc, and rigorous quality control procedures were applied throughout.

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Figure 2: All road/stream interaction points with numbered sampling locations for road dust and sediment quality (up and downstream of road crossings).(ND = no data collected) 18

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Figure 3: Location of Troll 9500 sondes with probes monitoring water depth, electrical conductance and turbidity plus the ISCO automatic water samplers

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Dissolved organic carbon (DOC) was quantified by high temperature catalytic combustion, and is dependent on the quantitative oxidation of DOC to CO2 which was measured by a non-dispersive infrared gas analyser. pH measurements for each water sample were taken in duplicate prior to acid fixation of the samples. Measurements of local water quality parameters (calcium, dissolved organic carbon (DOC) and pH were then be used to calculate site-specific metal bioavailability for Cu, Ni and Zn using the BLM derived regulatory models described in section 1.2. above.

2.4 Sediment processing and chemical analyses

Sediments samples were returned to the laboratory, dewatered, freeze dried and sieved to obtain the < 63 µm (silt) fraction. Sediments were analysed for bulk metal content by X-ray Fluorescence (XRF). Total extractable metals were obtained by aqua-regia digest and samples were analysed for a full suite of trace metals (B, Na, Al, Si, P, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Zr, Mo, Ru, Rh, Pd, Ag, Cd, Sb, Ba, Pt, Tl, Pb) by high resolution ICP-MS and/or ICP-OES (as appropriate to concentration).

2.5 Walkover Survey to Verify Specific Sources

The sediment fingerprinting and water/sediment quality analysis provide an evidence base for the relative contribution of different classifications of source type. To address the issues identified from the analysis requires an understanding of the specific sources of pollution at the point where they enter the watercourse. To identify specific sources we undertook a walkover survey of the river.

A survey was walked from just downstream of the point where the A444 road crosses the River Mease close to Netherseal, upstream along the Mease to the confluence with the Gilwiskaw Brook, and then following the entire length of the Gilwiskaw Brook. The survey followed the standardised methodology adopted by the Environment Agency recording all features which are potential sources or pathways of diffuse pollution and applying a grade of severity to each grade. Results were recorded into an ArcGIS GIS along with photographs and bespoke reports of any highly significant sources.

The aim of the walkover survey was to complement the sediment fingerprinting and quality investigation, providing a combined approach that allows engagement with catchment stakeholders and identified specific locations where measures may need to be considered to reduce a specific pollution threat. A full report of the walkover survey methodology and results is included in Appendix 1.

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3. Results and Discussion 3.1 Stream monitoring record and context of water samples

The stream monitoring record commenced on 05/08/2014 with the installation of the probe systems upstream, and downstream of the A42 crossing at Packington plus one of the main road drain pipes that connects road drains to the stream. Automatic water samplers (ISCO model) were installed on 03/09/2014 and pre-loaded with carousels of glass bottles when the weather forecast indicated high probability of suitable events for sampling. This was also necessarily controlled to some extent by working hours and staff availability. The probes were removed from the stream on 14/01/15 after all ISCO storm water sampling had been undertaken. Details of the storm events sampled are provided in Table 4 and water quality form these discussed in section 3.2. This section focusses on the broader hydrological context of the system.

Table 4: Details of storm events sampled by the ISCO automatic water samplers.

ISCO activation - each bottle spaced at Type one hour intervals from activation time Time of P1 (Upper) Time of P2 (Lower)

Sample set 1 Baseline 03/09/2014 13:00 03/09/2014 13:00 Sample set 2 Storm 04/10/2014 11:09 04/10/2014 10:32 Sample set 3 Storm System error* 07/10/2014 12:40 Sample set 4 Storm 07/11/2014 06:27 07/11/2014 06:23 Sample set 5 Storm 09/12/2014 23:58 10/12/2014 00:08 Sample set 6 Storm System error* 11/12/2014 20:44

*System error: the ISCO automatic sampler failed on these occasions and no samples were collected.

Storm flow is commonly observed to lead to a dilution of solutes in stream water which have (as in this case) base flow that is dominated by solute-rich groundwater. In winter, gritting of the road surface acts to enhance the specific electrical conductance (SEC, correlated to dissolved solutes) of road runoff with potential to act as a tracer of road input to the stream, often seen as short-lived spikes in electrical conductance. The hydrograph and SEC traces for the monitoring period (Figure 4), which also shows air temperature courtesy of Nigel Smith at Gables End Weather Station, Packington (http://www.nrms.info/index.php) demonstrates this nicely. For storm events during the period August to November the stream water SEC pattern is one of dilution during storm events with consistent patterns of dilution reflecting quickflow inputs from surface and shallow subsurface runoff (i.e. rainwater).

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deficient in dissolved solutes compared to soil and groundwater). In events after air temperature (AIR T) dropped below 0°C, presumably when road gritting operations began, there is a notable shift in specific electrical conductance (SEC) response where events from early December show SEC spikes in stream water. This demonstrates the direct link between road drainage and the stream. The SEC traces of sites both upstream and downstream of the A42 at Packington (Figure 5) show very similar patterns and while the A42 road rain indicates high SEC inputs into the study reach, there is a notable impact on SEC from the upstream urban drainage area. The relative importance of ‘diffuse’ road contamination from urban areas versus the point source input from the A42 is discussed in the context of water and sediment quality data in sections 3.2 and 3.3.

The storm event sampled 07/10/14 (Figure 5) was in the middle of a sequence of similar magnitude events following a dry period in September and is typical of the stream response in the early autumn. The upstream (P1) and downstream (P2) hydrograph shapes are very similar with a slight lag in peak downstream linked to flood wave transit time. The SEC traces also show similar response with marked dilution by storm flow and sporadic pulses of more solute rich water on the falling limb. At this time, the road drain pipe (RD) appears to be discharging groundwater prior to the event so it also shows a dilution response in terms of SEC. Water samples were collected both upstream and downstream of the A42 for this event.

The storm event sampled 15/10/14 (Figure 6) was of a similar magnitude to the first event. Water samples were collected downstream of the A42 only for this event due to a system error on the upstream ISCO. Nevertheless, this still affords a good opportunity to compare spikes in the hydrograph data (DEPTH, SEC) with metal concentrations post the storm water input. The hydrograph and SEC trace responses are also similar to the event of 07/10/14 although the SEC pulses are closer to the peak flow and correlate with similar features in the road drain within this event. SEC patterns are, however, similar upstream and downstream.

The storm event sampled 07/11/14 (Figure 7) had multiple hydrograph peaks in relation to a series of rainfall events which followed a few days dry weather, allowing contaminants to build up on the road surface. During this time the air temperature dropped below 0°C and the SEC response of the road drain suggests gritting had taken place leading to salt wash off into the stream with multiple SEC spikes in the road drain and corresponding peaks stream water showing response to each rain event. Water samples were collected both upstream and downstream of the A42 for this event. 23

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Figure 5: Hydrograph and SEC for storm event sampled 07/10/14

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Figure 6: Hydrograph and SEC for storm event sampled 15/10/14

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Figure 7: Hydrograph and SEC for storm event sampled 07/11/14

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Figure 8: Hydrograph and SEC for storm events sampled 10/12/2014 and 11/12/2014

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The event sampled 10/12/14 (Figure 8) was after road gritting was suspected to have taken place and there is a noteworthy spike in SEC at both sites prior to the event which is possibly linked to the road gritting activity directly. The event itself is quite low in magnitude which offers an excellent basis upon which to test the ‘worst-case scenario’ in terms of road runoff i.e. less scope for dilution of contaminants which had had a while to build up in preceding dry weather. This was closely followed by the event sampled on 11/12/14 (These are downstream samples only, but again this allows comparison of spikes in the hydrograph data (DEPTH, SEC) with metal concentrations post the storm water input) (Figure 8). This offers good opportunity for comparison of storm water quality in a higher magnitude event.

3.2 Water Quality Monitoring for Summer and Winter Storm Events

Data for the complete set of metal analysis for the baseline and storm events are given in the accompanying electronic appendix (Appendix1_Mease Report_Feb_2015_Waters .xlsx). This includes total and dissolved metals, selected dissolved metals (where values which exceed the new generic EQS (Table 2) are highlighted in bold) and the platinum group elements (ruthenium, rhodium, palladium, platinum) which are a specific indicator of road derived contaminants.

Chemographs of dissolved copper, zinc and nickel were plotted with respect to the hydrograph data to determine what impact the local A42 road drain had on metal concentrations in the water column during summer and winter storm events. These metals were chosen as key indicator metals for road runoff and because the measured dissolved concentrations of copper and zinc in the ISCO samples were observed to be above the generic EQS for these metals on several occasions (Appendix 1 to Mease Report_Feb_2015.xlsx).

Baseline dissolved metal concentrations (Figure 9) are generally low as expected for the baselines samples. Dissolved copper concentrations ranged from 0.6 - 1.6 µg/L compared to the current generic EQS guideline value of 1 µg/L (Table 2). Dissolved zinc concentrations were generally below 7 µg/L compared to the current generic guideline value of 10.9 µg/L and dissolved nickel concentrations were all below 5 µg/L compared to the current guideline value of 4 µg/L.

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Figure 9: Baseline dissolved metal concentrations for copper, zinc and nickel for ISCO samples collected on 3/09/2014/. Water depth and conductivity are also shown.

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3.2.1 Summer storms

During the storm event on 04/10/14 (Figure 10) all metal concentrations in the system were seen to increase compared to the baseline samples (Figure 9). Dissolved copper ranged from 3.5 µg/L to 6.9 µg/L, dissolved zinc ranged from, 3.1 µg/L to 39 µg/L, dissolved nickel ranged from 1.4 µg/L to 10 µg/L. (The absolute measured dissolved concentrations of zinc should be treated with caution at this time due to the difficulty in obtaining reliable blank measurements for these samples (see section 2.3), but nevertheless the chemographs for zinc are included here as the concentrations of this metal follow a similar pattern to that of nickel during the storm event.) For these metals, a peak in dissolved concentrations was observed after about 3 hours of sampling on the falling limb of the hydrograph (i.e. when the stream levels were dropping after the flood event) with metals returning to baseline levels (< 5 µg/L) as the flush of storm water receded. Downstream (P2) metal concentrations were generally lower than upstream (P1) concentrations indicating the local A42 road drain had little impact on metal concentrations in the water column during this event. It is noteworthy that the falling limb bulge in SEC seen in both P1 and P2 SEC traces around 14:00-15:00 corresponds with a rise in zinc and copper concentrations indicating a metal source upstream of the monitored A42 crossing. There is also a notable SEC peak in the Road Drain (RD SEC) record early in the event but this did not correspond to a rise in stream metals in this event.

Only downstream (P2) samples were collected during the storm event on 07/10/14 (Figure 11). Dissolved copper concentrations ranged from 3.2 µg/L - 4.5 µg/L, slightly elevated from the baseline concentrations and above the current EQS. Dissolved zinc concentrations ranged from 1.2 µg/L to 15 µg/L, but exceeded the current EQS during one measurement window. Dissolved nickel concentrations ranged from 0.21 µg/L - 0.59 µg/L, all below the current EQS. Again a similar pattern of elevated metal concentrations is seen in the chemographs with metals peaking around 4 - 5 hours after the increase in water flow/depth. There was no notable SEC pattern other than dilution in the road drain or stream datasets in this event.

During the storm event on 07/11/14 (Figure 12) the SEC trace from the road drain shows a notable flush of road solutes in the early stages of the storm event but this was prior to the triggering of the ISCO samplers. During the sampling time period, however, dissolved copper concentrations were observed to increase from 2.7 µg/L to 4.9 µg/L over the course of the storm. Dissolved zinc concentrations ranged from 4.2 µg/L -11 µg/L and dissolved

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nickel concentrations ranged from 0.38 µg/L to 0.94 µg/L. Elevated concentrations of copper and zinc may be of concern and the bioavailability of these metals was investigated further (see section 3.2.1). Downstream (P2) dissolved metals concentrations were remarkably similar to upstream (P1) concentrations however, and while the elevated metal concentrations correlate with a second, more muted SEC response from the road drain, the similarity between P1 and P2 again indicates the A42 road drain had little impact on metal concentrations during the sampled section of this event and that upstream sources were dominating the water quality signal at this time.

3.2.2 Winter storms The range of dissolved metal concentrations measured during the storm event commencing on 09/12/2014 (Figure 13) were very similar to those measured for the storm 07/11/2014. However for this event, initially high concentrations of dissolved copper (9.7 µg/L) and nickel (1.5 µg/L) in the downstream location (P2 CU, P2 NI) correspond to a marked increase in conductivity in the water flowing from the A42 road drain (RD SEC at 00:00 on 09/12/2014). This is important since, as noted above, in previous events the trigger time of the samplers meant that this early flush from the A42 was not captured for analysis. This demonstrates that the A42 drain is having an impact on stream water quality during the early stages of the storm hydrograph. Dissolved copper concentrations in this system remained above the generic EQS and may again be a cause for concern so bioavailable concentrations and local EQS were calculated (Section 3.2.1). These high concentrations correspond with periods of higher SEC on the falling limb which, as observed in earlier events, appear to be related to an upstream input (e.g. the more extensive urban area upstream of the A42 crossing).

Only downstream (P2) samples were collected during the storm event on 11/12/2014 (Figure 14). As previously observed, concentrations of dissolved copper (2.6 µg/L – 5.7 µg/L were above the generic guideline value and bioavailable concentrations were investigated further (Section 3.2.1) Increasing concentrations of dissolved copper (from 2.6 to 5.7 µg/L) and nickel (from 0.42 to 0.82 µg/L) were observed from 04:00 on 12/12/ 2014. This corresponds to an increase in both water depth (P2 DEPTH) and conductivity (RD SEC) from the A42 road drain outfall from this point onwards, which considering evidence from the prior sampled storm event, points to the A42 road drain as a source of elevated metals in the downstream system.

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Figure 10: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 04/10/2014. Water depth and conductivity are also shown. 32

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Figure 11: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 07/10/2014. Water depth and conductivity are also shown. 33

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Figure 12: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 07/11/2014. Water depth and conductivity are also shown.

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Figure 13: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 09&10/12/2014. Water depth and conductivity are also shown

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Figure 14: Dissolved metal concentrations for copper, zinc and nickel collected by ISCO samplers during the storm event 1/12/2014. Water depth and conductivity are also shown

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Evidence from the storm sample analysis indicates that the water quality of the Gilwiskaw Brook at the A42 crossing point at Packington is affected by both upstream sources and road drains at the crossing point. While the latter are temporally discrete, high metal concentration flushing events on the rising limb of winter storms, the former are likely to be linked to more spatially extensive sources implied by the duration of SEC response and correlating elevated metal peaks, in many events. ‘Diffuse’ pollution from the extensive road network and many drainage points in the urban environment is a likely source but the influence of past mine workings and processing areas cannot at this stage be ruled out. Evidence from spatial patterns in sediment quality permits further insight into the relative importance of these sources (section 3.3).

3.2.1 Bioavailability of Metals Copper, Nickel and Zinc (Cu, Zn, Ni) Data for calculated bioavailable concentrations of copper nickel and zinc, (calculated using the bio-met.net software (http://bio-met.net/)) for the baseline and storm events are given in the accompanying electronic appendix (Appendix 1 to Mease Report_Feb_2015.xlsx). From these data it is clear that in all samples bioavailable concentrations of copper nickel and zinc are well below the derived Local EQS calculated for each sample and all have a Risk Characterisation Ratio (RCR) less than 1. This indicates that concentrations of these metals measured in water sampled from the channel are not of concern. In accord with the principals of the BLM (as described in section 1.4), these results are due to the high levels of measured DOC (a competitive binding ligand for metal ions in solution) and calcium (which competes for metal binding sites at the biotic ligand) in the waters which greatly reduce the potential for metal interaction with, or toxicity to, aquatic life.

Lead and Manganese (Pb and Mn) Software is also available to calculate bioavailable manganese concentrations but this data has not been included because no dissolved Mn concentrations exceeded the generic EQS for, Mn 123 µg/L, (Table 2) and using the tiered risk assessment approach no further action is required. Dissolved lead concentrations slightly exceeded the generic EQS (1.2 µg/L) on only two occasions during Event 2 reaching 1.3 µg/L and 1.6 µg/L. As yet, no regulatory BLM software is available for determining bioavailable lead concentrations but these concentrations of dissolved lead are well below the previous guidelines for dissolved lead (4 – 250 µg/L, Table 2) and are unlikely to be problematic to aquatic life.

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Chromium, Cadmium, Iron, Arsenic and Aluminium (Cr, Cd, Fe, As, Al) Dissolved concentrations of chromium, cadmium, iron and arsenic (Appendix1_Mease Report_Feb_2015_Waters.xlsx) were all generally below the generic EQS (Table 1) for these metals even for very soft surface waters. Dissolved cadmium concentrations slightly exceeded the generic EQS (0.08 – 0.25 µg/L depending on water hardness) on two occasions, during Event 2 and Event 6, reaching 0.086 and µg/L and 0.084 µg/L respectively but cannot be considered problematic to aquatic life at these concentrations.

Aluminium concentrations however were high across all the water samples analysed (Appendix1_Mease Report_Feb_2015_Waters.xlsx) but possible sources of dissolved aluminium in the River Mease waters include input from historical mining activities in the area. Dissolved aluminium concentrations ranged from 2.6 – 10.4 µg/L in the baseline samples (03/09/2014) and reached concentrations as high as 70 µg/L in water samples collected during storm event 6 (11/12/2014). These concentrations of aluminium compare to a suggested Probable No Effect Concentrations (PNEC values) for aluminium of 0.05 µg/L (long-term) to 0.25 µg/L (short-term) in UK freshwaters. Clearly the dissolved aluminium concentrations measured in these waters have the potential to impact up on aquatic life, although there is currently a lack of officially adopted environmental standards for aluminium in surface waters in the UK (Environment Agency, 2007).

There were measureable concentrations of the platinum group elements in many of the samples (Appendix1_Mease Report_Feb_2015_Waters.xlsx) but no clear trends were observed for elevated levels of these metals in the downstream samples.

3.3 Stream sediment and road dust metal content

Sediment samples were collected from a range of road-stream junctions (Figure 2) spanning a road hierarchy in the area (from A road to minor road including urban areas). These samples were analysed for metal content by X-Ray Fluorescence (XRF), ICP MS or ICPOES to explore any differences in metal concentration between upstream and downstream sediment and for comparison to road dust samples. Data for the complete set of metal analysis for the sediments and road dusts are given in the accompanying electronic appendix (Appendix2_Mease Report_Feb_2015_Sediments.xlsx). Selected data for the metals of concern listed in the Canadian Sediment Quality Guidelines (SQG - Table 3) are given in (Table 5).

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High concentrations of metals were found in both upstream and downstream sediments. High concentrations of metal were found in the control samples, with concentrations exceeding the Interim Sediment Quality Guideline (ISQG), but these concentrations were slightly lower than found in the upstream or downstream samples. Control sediments exceeded the Probable effect Level (PEL) in one case only (for As at site 4) but this is likely to be related to historical mining activity rather than pollution from road run-off. .

Many of the sediments exceeded the Canadian ISQG and notably for Zn, As and Pb the PEL was also exceeded in a number of samples. Zinc concentrations were all especially high and exceeded the PEL in most cases. Copper, zinc, cadmium and lead are all indicators of road run off impacts and the source of these metals was explored further in the following sections. As expected, high levels of copper zinc and lead were also found in the road dusts with levels of copper and lead in particular being higher in road dusts collected from A roads than from other sources.

For the sediments collected in the vicinity of the A42 at Packington during the winter months (Table 5), copper concentrations only exceeded the ISQG but not the PEL. Zinc concentrations however, exceeded the ISQG in the upstream samples but exceeded the PEL in the downstream sediments. As expected for road dusts collected in the winter months all metals exceeded the PEL. Copper (Cu) and zinc (Zn) concentration were observed to be much higher in the road dusts collected during the winter months than during the summer months which indicates a potential source of pollution from road run-off during this time. Notably, chromium concentrations which were much higher in the winter collected sediments than the summer ones, with all concentrations of this metal exceeding the PEL during this period. Lead (Pb) concentrations were also high in all the winter sediments and road dusts but were within the same concentrations range as samples collected in the summer.

Levels of arsenic were high in many sediment samples but this metal is not usually associated with road run off pollution and high concentrations of arsenic were not found as a source in any water samples (Section 3.2). These high arsenic concentrations may be a legacy from historical mining activities in the area and result from this metal’s propensity to accumulate in the sediments.

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Table 5 Selected sediment metals concentrations (mg/kg): values exceeding CCME ISQG have been highlighted in bold. Values exceeding the PEL have been highlighted in red.

SITE SAMPLE ID Type U/S IMPACT Cr Cu Zn As Cd Pb ISQG 37.3 35.7 123 5.9 0.6 35 PEL 90 197 315 17 3.5 91.3 SUMMER COLLECTED SEDIMENTS 4 S04USGBt UP CONTROL 67.5 52.8 245 22.3 1.05 45 6 S06USMt UP CONTROL 59.8 36.7 176 11.4 0.52 48 10 s10USSF UP CONTROL 43.6 25.0 169 9.80 0.57 55.8 11 S11USGB UP CONTROL 55.2 41.7 193 15.1 1.06 67 8 S08USGBt UP A ROAD 65.3 104 1070 21.1 1.51 115 13 s13USM UP A ROAD 54.7 48.9 382 16.3 1.06 72.1 1 S01USGB UP URBAN 1020 83.1 402 21.8 1.08 131 3 S03USGB UP URBAN 18.5 68.1 449 13.8 0.95 150 9 S09USGB UP URBAN 50.2 92.3 472 12.0 1.29 214 5 S05USGB UP MINOR ROAD 62.5 54.9 347 21.3 1.02 78 7 S07USGB UP MINOR ROAD / 72.7 56.4 377 20.8 0.87 90 14 s14USHB UP MINORA42 ROAD 46.0 62.4 851 16.5 3.61 115 12 s12USM UP MIXED 57.2 68.2 440 15.6 1.07 108 15 s15USM UP MIXED 55.1 46.7 490 16.2 1.59 86.7 16 s16USM UP MIXED 64.7 45.9 406 19.9 1.49 75.5 18 s18USM UP MIXED 71.9 41.1 404 17.5 1.29 68.1 1 S01DSGB DOWN A42 93.5 88.0 438 26.7 1.14 127 8 S08DSGBt DOWN A ROAD 72.9 122 769 18.4 1.56 127 11 S11DSGB DOWN A ROAD 54.2 43.3 198 10.9 0.92 80 12 s12DSM DOWN A ROAD 81.7 160 978 19.3 1.59 126 13 s13DSM DOWN A ROAD 65.5 57.2 475 18.5 1.13 95.7 14 s14DHB DOWN A ROAD 49.6 83.1 656 15.3 3.24 118 5 S05DSGB DOWN B ROAD 58.8 47.5 343 25.1 0.87 67 6 S06DSMt DOWN B ROAD 74.2 45.3 192 12.0 0.55 49 3 S03DSGB DOWN URBAN 85.1 78.8 557 18.9 0.94 132 9 S09DSGB DOWN URBAN 56.6 97.2 507 14.7 1.06 224 4 S04DSGBt DOWN MINOR ROAD 42.3 59.0 323 24.8 1.35 65 7 S07DSGB DOWN MINOR ROAD / 57.3 53.6 344 21.0 0.76 91 10 s10DSSF DOWN MINORA42 ROAD 43.9 27.4 182 9.08 0.76 57.4 17 17DSM DOWN MINOR ROAD 69.9 32.9 195 12.39 0.92 47.3 15 s15DSM DOWN MIXED 64.4 50.4 477 17.8 1.62 83.8 16 s16DSM DOWN MIXED 69.1 48.5 399 20.5 1.58 69.0 18 s18DSM DOWN MIXED 65.4 38.9 359 18.4 1.21 58.7 19 s19DSM DOWN MIXED 73.8 38.2 296 14.19 1.02 47.5 8 RD8GBt ROAD ROAD A ROAD 88.5 145 338 9.2 0.51 107 11 RD11GB ROAD ROAD A ROAD 91.7 154 646 12.5 0.77 289 12 rd12 ROAD ROAD A42 131 733 2760 21.9 2.15 218 13 rd13 ROAD ROAD A ROAD 63.2 130 697 9.74 1.11 155 14 rd14 ROAD ROAD A ROAD 81.4 239 674 10.5 1.47 330 19 rd19 ROAD A ROAD 63.5 106 337 7.22 0.51 67.5 5 RD05GB ROAD ROAD B ROAD 58.2 101 356 12.6 0.62 95.0 6 RD06Mt ROAD ROAD B ROAD 54.1 310 381 10.9 0.50 223 3 RD03GB ROAD ROAD URBAN 51.4 71.5 234 14.7 0.74 84 9 RD09GB ROAD ROAD URBAN 72.3 128 389 8.9 0.40 102 1 RD01A42 ROAD MINORROAD ROAD 286 373 971 14.1 1.16 406 4 RD04GBt ROAD ROAD MINOR 47.5 71.5 367 14.6 0.72 69 7 RD07GB ROAD ROAD MINOR 53.6 105 338 12.6 0.94 90 10 rd10sr ROAD ROAD MINOR 53.5 109 544 8.80 0.54 184 15 rd15 ROAD ROAD MINOR 35.1 46.0 325 7.73 0.43 89.9 16 rd16 ROAD ROAD MINOR 41.3 28.5 135 6.90 0.36 54.2 17 rd17 ROAD ROAD MINOR 41.8 39.7 123 8.19 0.37 66.8 18 rd18 ROAD ROAD MINOR 54.6 51.7 153 7.15 0.54 56.9 ROAD 40

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WINTER COLLECTED SEDIMENTS PACKINGTON A42US1A UP A ROAD A42 224.7 39.8 301.5 < LOD < LOD 110.5 PACKINGTON A42US1B UP A ROAD A42 146.2 27.3 258.1 16.3 < LOD 110.6 PACKINGTON A42US5 UP A ROAD A42 193.0 33.2 212.8 < LOD < LOD 110.3 PACKINGTON A42DS6 DOWN A ROAD A42 189.3 55.3 382.5 53.3 < LOD 118.1 PACKINGTON A42DS2A DOWN A ROAD A42 176.7 44.1 365.4 < LOD < LOD 109.9 PACKINGTON A42RD3A ROAD A ROAD A42 280.8 309.7 1513.2 27.7 < LOD 232.7 PACKINGTON A42RD3B ROAD A ROAD A42 329.0 331.2 1657.3 < LOD < LOD 261.2 PACKINGTON A42RD4 ROAD A ROAD A42 283.6 448.4 1055.8 19.6 < LOD 110.2

Our approach to understanding of the impacts of roads in the River Mease catchment is to undertake detailed analysis on the Gilwiskaw Brook and to use the detailed understanding in combination with a sampling at selected road crossings throughout the catchment. Bulk copper and zinc data, key road indicators measured by XRF analysis, were presented in the Final Summer Report (Rogers et al 2014). These data indicated that road hierarchy has a major influence on the levels of high abundance contaminants available for wash off into the stream network, with both zinc and copper highly elevated in the material collected from A roads and a clear gradient in concentrations down to the minor roads sampled (

Figure 15).

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(a)

(b)

Figure 15: Bulk concentrations of (a) copper zinc and (b) zinc measured in road dust samples from across the system, categorised by road size

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Detailed analysis of samples from across the River Mease network have been analysed for a full suite of trace metals for this full report, including road-specific metals e.g. Pt, by high resolution ICPMS and ICPOES. Due to the previously clear pattern of road hierarchy influence on copper and zinc concentrations identified in the previous report (Rogers et al 2014), correlation analyses were undertaken to identify metals which co-varied with these indicator metals. Full data and correlation matrices are presented in the accompanying appendix (Appendix2_Mease Report_Feb_2015_Sediments.xlsx).

Selected correlations between copper and zinc concentrations in road dusts and indicator metals for road run off (V, Cr, Fe, Ni, Cd, Pb and the platinum group elements) are presented in Table 6. Note that the lack of ‘significant’ correlations in A road samples reflects the lower sample number (n = 6).

Table 6 Correlations between copper and zinc concentrations in road dusts and indicator metals for road run off

Metal All RD data (n= 18) A Road (n = 6) Minor Road (n = 8) Cu Zn Cu Zn Cu Zn V ns ns ns ns ns ns Cr 0.845** 0.721** ns ns 0.762* ns Fe 0.659** 0.624** ns ns 0.952** 0.881** Ni 0.893** 0.751** ns ns 0.810* 0.738* Cd 0.606** 0.707** 0.829* 0.943** 0.929** 0.857** Pb 0.895** 0.878** ns ns 0.810** 0.833**

Rh 0.812** 0.730** ns ns 0.886** 0.838** Pd 0.558** 0.540** ns ns 0.929** 0.905** Pt 0.908** 0.776** ns ns 0.905** 0.833** *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). ns. Not significant

Several of the metals, Cr, Fe, Cd, Pb, Rh and Pt, Pt showed significant correlation to Cu and Zn and very similar trends to the data for these metals when categorised according to the road hierarchy (Figure 16). Key observations are:  Concentrations of the selected metals are generally elevated in the material collected from A roads and demonstrate a trend to lower concentrations in the minor roads sampled  This broadly indicates that road hierarchy has a major influence on the levels of contaminants available for wash off into the stream network

No apparent trend for road dust metals data and road hierarchy was observed for Ni and Pd despite significant correlations with Cu and Zn.

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Boxplot of road dust Cr concentrations by road type Boxplot of Pb concentrations by road type 300 450

400 250 350 200 300

g g 150 250

C P 200 100 150

50 100

0 50 A ROAD_Cr B ROAD_Cr MINOR ROAD_Cr URBAN_Cr A ROAD_Pb B ROAD_Pb MINOR ROAD_Pb URBAN_Pb

(a) (d)

Boxplot of road dust Fe Concentrations by road type Boxplot of Rh concentration in road dust by road type 80000 0.018

0.016 70000 0.014

60000 0.012

k 0.010

50000 m

0.008

F 40000 0.006

0.004 30000 0.002

0.000 20000 A ROAD_Rh B ROAD_Rh MINOR ROAD_Rh URBAN_Rh A ROAD_Fe B ROAD_Fe MINOR ROAD_Fe URBAN_Fe (b) (e)

Boxplot of road dust Pt concentrations by road type Boxplot of Cd concentrations by road type 0.12

2.0 0.10

0.08

1.5 g

/ 0.06

C 1.0 0.04

0.02

0.5 0.00 A ROAD_Pt B ROAD_Pt MINOR ROAD_Pt URBAN_Pt A ROAD_Cd B ROAD_Cd MINOR ROAD_Cd URBAN_Cd (f) (c)

Figure 16 Concentrations of (a) Cr, (b) Fe, (c) Cd, (d) Pb, (e) Rh and (f) Pt, measured in road dust samples from across the system, categorised by road size

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The levels of bulk Cu and Zn contamination in road dust were also reflected in the pattern of metal concentrations in the stream sediment (Figure 17) when categorised according to the road hierarchy. These were discussed fully in the previous report (Rogers et al 2014) and the key observations are summarised below:

 The range of concentration of metals at the sites upstream of all sampled road inputs can be considered a background control. Concentrations of Cu and Zn, which are widely associated as an indicator of road runoff, were lower in the upstream sites than the downstream locations (Figure 17).  The downstream range of Zn and Cu concentrations seen in the stream sediment were clearly elevated in the vicinity of A roads, in excess of PEL in the case of Zn.  The streams likely to be affected by urban runoff show metals concentrations in excess of those taken in vicinity of rural minor roads despite the similar contaminant loadings (  Figure 15). This must be a consequence of the overall greater urban road surface area illustrating the diffuse nature of this source with respect to the urban stream reaches.  The stream sediment samples downstream of the minor roads showed no evidence of enhancement in bulk metal concentrations.  Many sites along the River Mease main river have a mixed upstream road input and the range of moderately elevated concentrations at these sites shows that dilution by other sediment inputs and residence time are important factors controlling at-a-point metal loadings.

Overall, copper and zinc concentrations both upstream and downstream of A roads (Figure 2, site1 and site 8) were higher than the concentrations for these metals associated with inputs from minor B roads (Figure 2, site 5 and site 7). Concentrations of copper and zinc upstream and downstream of urban areas at Ashby (Figure 2, site 9) and Packington (Figure 2, site 3) were higher than the minor road sites as were the road dust sweepings at these sites. Whilst A roads by themselves are the most important contributors of these metals, there is also a cumulative effect associated with less significant inputs from the wider minor/urban road network especially associated with Ashby-de-la-Zouch and Packington.

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(a)

(b)

Figure 17: Bulk concentrations of (a) copper and (b) zinc measured in stream sediment downstream of road crossings of different category

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Correlation analysis was undertaken to identify which metals which co-varied with copper and zinc concentrations as key indicators of contamination from road run off (Table 7).

Table 7 Correlations between copper and zinc concentrations in stream sediments and indicator metals for road run off

Metal All data (n=33) Up Stream (n=16) Down Stream (n=17) Cu Zn Cu Zn Cu Zn V Ns ns ns ns ns ns Cr Ns ns ns ns ns ns Fe Ns 0.469** ns ns ns 0.538* Ni Ns 0.374* ns ns ns ns As 0.432* ns ns ns ns ns Cd 0.474** 0.744** ns 0.806** 0.558* 0.730** Pb 0.854** 0.806** 0.844** 0.759** 0.882** 0.847**

Rh o.868** 0.753** 0.892** 0.659** 0.851** 0.815** Pd 0.615** ns 0.656** ns 0.546* ns Pt 0.678** 0.492** 0.700** ns 0.668** 0.551* *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). ns. Not significant

Several of the metals e.g. Pb, Rh and Pt showed significant correlation to Cu and Zn and very similar trends to the data for these metals when categorized according to the road hierarchy (Figure 18). Key observations are:  Concentrations of Pb and Rh in the upstream control samples are lower than downstream locations reflecting the lack of road inputs in the headwaters sampled as control. For Pt the broad range of concentrations of metals in the upstream control samples makes interpretation of the results with respect to road hierarchy more difficult but trends are still similar to those described below. This contamination of control areas is likely linked to air pollution from exhaust pollution.  The downstream sediment, i.e. sediment collected from below road crossings, range of metal concentrations were clearly elevated in the vicinity of A roads indicating main road impact on aquatic habitat.  The streams likely to be affected by urban runoff show metals concentrations in excess of those taken in vicinity of rural minor roads despite the similar contaminant loadings. This must be a consequence of the overall greater urban road surface area illustrating the diffuse nature of this source with respect to the urban stream reaches. It is also noteworthy that for Pb and Rh the loadings from urban runoff are greater than the A roads.

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 The stream sediment downstream of the minor roads and sites along the River Mease main river which have a mixed upstream road input showed no evidence of enhancement in metal concentrations implying that low traffic density and low overall surface are do not present a pollution risk to the stream network, i.e. the minor roads and mixed inputs are not problematic in terms of pollution impacts.

For a second group of metals (Ni and Cd) the trends were less clearly linked to road network and hierarchy (Figure 19). Key observations are:  Concentrations of metals in the upstream control samples are lower than the downstream range of metal concentrations seen in the stream sediment in the vicinity of A roads implying a major road impact as for metals listed in previous section.  The streams likely to be affected by urban runoff, however, do not show elevated concentrations of these metals  The stream sediment downstream of sites along the River Mease main river which have a mixed upstream road input showed some evidence of enhancement in these metal concentrations compared with control sites.

No apparent trends for downstream sediment metals data and traffic density were observed for Cr, Fe and Pd despite correlations with copper and zinc.

The spatial pattern of metal loadings in Gilwiskaw Brook and the wider catchment shows clear linkages between contaminant level for copper (Cu) and zinc (Zn) and traffic density according to road classification (Figure 20 and Figure 21). Patterns emerge with clustering around the Ashby urban centre and A42 on Gilwiskaw. It is also interesting to note that that the Zn downstream footprint is greater than the Cu footprint. This further reflects the sediment copper concentrations being generally below the Probable Effect Level (PEL) threshold, whilst the sediment zinc concentrations were generally found to be above this threshold (Table 5). Targeting mitigation measures on A roads would be an appropriate strategy to reduce metal inputs to stream and river sediment habitats. While the urban areas are also a contributor due to spatial extent, mitigation would be severely hampered by the complexity of urban drainage systems and multiple points of storm water entry.

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Boxplot of stream sediment Pb downstream of different road type 250

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b b b b b b P P P P P P L D D N D D O A A A A E R O O B O IX T R R R R M N A B U R O s /s C /s /s / O d d d d IN M M M M A M M A A E A A E /s E R E E R d R T R R T S T T T M S S S S A E R T S

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Boxplot of stream sediment Rh downstream of different road type 0.007

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Boxplot of stream sediment Pt downstream of different road type 0.014 0.012 0.010

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P 0.004 0.002 0.000 t t t t t t P P P P P P L D D N D D O A A A A E R O O B O IX T R R R R M N A B U R O s /s C /s /s / O d d d d IN M M M M A M M A A E A A E /s E R E E R d R T R R T S T T T M S S S S A E R T S

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Figure 18: Concentrations of (a) Pb (b) Rh and (c) Pt measured in stream sediment downstream of road crossings of different category

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Boxplot of stream sediment Ni downstream of different road type 300

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0 i i i i i i N N N N N N L D D N D D O A A A A E R O O B O X T R I N R R U R M A B R O s /s C /s /s / O d d d d IN M M M A M M A M A E A A E /s E R E E R d R T R R T T S T T S M S S S A E R T S

Boxplot of stream sediment Cd downstream of different road type 3.5

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d d d d d d C C C C C C L D D N D D O A A A A E R O O B O IX T R R R R N U M O A B s R s C s s / O / / / d N d M d d I A M M M E M M A A A A E /s E R E E R d R T R R T T S T T M S S S S A E R T S

Figure 19: Concentrations of (a) Ni and (b) Cd measured in stream sediment downstream of road crossings of different category

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3.4 Fingerprinting road sediment inputs to channel sediment

The fingerprinting approach used has followed standard procedures that have been described in prior studies (Blake et al, 2014; Taylor et al., 2014). To provide an indicative quantitative evaluation of the contribution of different road networks to contaminated sediment in the channel, geochemical fingerprints of A road, B road, minor road and urban areas were established through analysis of the spatially-integrated road sediment samples collected from the study sites identified in Figure 2. These were then compared to upstream sediment from the control sites which are assumed to represent catchment material not contaminated by road pollution i.e. a general catchment sediment material source. The clear difference between this material and the road material (e.g.

Figure 15) allows for the discrimination between road material and other catchment material to address the key question of which road systems input the most contamination to the river network. The information provided by this analysis should be interpreted in the context of the prior section which is addressing the same question but through spatial analysis.

Major and minor elements were first subjected to the non-parametric Kruskal-Wallis test for difference across the above source geochemical data types. Results provided a potential sediment fingerprint of Zn, Cu, Ba, Mo, Rb, Mn, Cr, Ca, K and Al (Table 8). The discriminatory power of these fingerprint properties was next tested by applying Discriminant Function Analysis (DFA). Results indicate (Figure 22) that the above properties are able to distinguish catchment sediment from road material well with A roads showing a clear distinction, presumable linked to pollutant levels and traffic volume/type, but signature overlap between B roads, minor roads and urban roads, as might be expected.

Having established the discriminatory power and scope of the geochemical fingerprints, material from the downstream location of each studied crossing point identified in Figure 2 was compared to the source signatures using a quantitative unmixing model as per prior work (Blake et al, 2014). The results are illuminating and closely in line with the evaluation of key contaminants Cu and Zn (

Figure 15 and Figure 17). All control sites, upstream of road crossings show a ca. 100% (Table 9) contribution from catchment materials as would be expected.

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Table 8: Results of Kruskall-Wallis test for difference (run using IBM SPSS statistics version 21 software)

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Catchment A road B road Minor road Urban SITE material material material material material 1 71 ± 10 19 ± 6 6 ± 7 3 ± 4 2 ± 2 2 NO DATA 3 67 ± 13 28 ± 10 1 ± 1 3 ± 5 1 ± 2 4 64 ± 11 1 ± 2 8 ± 5 24 ± 9 4 ± 4 5 73 ± 8 4 ± 4 2 ± 3 13 ± 8 8 ± 7 6 89 ± 8 0 ± 0 1 ± 2 7 ± 6 2 ± 3 7 81 ± 9 4 ± 3 4 ± 4 6 ± 6 6 ± 6 8 66 ± 4 28 ± 4 3 ± 3 1 ± 2 1 ± 2 9 54 ± 10 18 ± 7 5 ± 6 5 ± 5 18 ± 12 10 96 ± 5 0 ± 0 1 ± 1 1 ± 1 2 ± 5 11 97 ± 3 1 ± 1 1 ± 1 1 ± 1 1 ± 1 12 45 ± 6 46 ± 10 8 ± 8 1 ± 2 0 ± 1 13 69 ± 11 10 ± 7 6 ± 3 8 ± 8 6 ± 5 14 52 ± 10 36 ± 7 5 ± 6 5 ± 6 2 ± 3 15 69 ± 11 20 ± 7 4 ± 5 6 ± 6 1 ± 2 16 74 ± 12 10 ± 7 5 ± 6 7 ± 7 4 ± 5 17 NO DATA 18 67 ± 10 10 ± 9 11 ± 9 9 ± 8 3 ± 5 19 87 ± 5 6 ± 4 6 ± 1 2 ± 2 4 ± 5 20 NO DATA

A strong A road signal is picked up at the sites where the A42 intersects with the Gilwiskaw Brook and River Mease main stem river (sites 1, 8, 12 and 13 – See Figure 20 and 21). The proportion of road derived material downstream of these sites remains elevated with a gradual dilution towards the catchment outlet in the River Mease main stem channel. The model does not imply a major contribution from B roads in the system and minor roads/urban roads only make a contribution at selected sites 4, 7 and 9 where site 9 is notably downstream of the town of Ashby-de-la-Zouch. Overall the fingerprinting data are indicative of a significant contaminated sediment contribution from A roads with a lesser but notable input from urban/minors roads near the larger population centre. The sediment fingerprints cannot provide a black-and-white answer to source apportionment since, especially in this case variability in source terms introduces an element of uncertainty into results. In this case, Goodness of Fit (GOF) measurements, i.e. the closeness of modelled sediment mixtures compared to observed, ranged from 62 to 91 % demonstrating that the data in Table 9 should be considered, as standalone evidence, a good indication of road inputs at the time of sampling rather than exact amounts. Coupling, however, this output with the 56

APEM Scientific Report 413482 analysis presented in section 3.2, increases the weight of evidence that the representative A roads that were sampled are a major contributor to heavy metal pollution in the Mease and Gilwiskaw Brook network and that measures need to be taken to reduce this impact. It also indicates a more subtle contamination of sediment at many other road crossings that are not picked up by the fingerprinting.

3.5 Walkover survey to identify sources of diffuse pollution

The walkover survey has identified a total of 87 sources of diffuse urban pollution. Full details of the walkover survey findings are presented in Appendix 1. No Grade 1 sources (those that impact on the entire river) were identified during the walkover. However, an abundance of low grade pollution sources with localised impact may still present a significant risk to the catchment.

Conduit sources were identified as the most abundant in the catchment with particularly high densities in the developed/semi-urban areas. A total of 60 conduits were identified, 36 of which are pipes and 18 of which were classed as road runoff. The types of effluents that are commonly associated with these types of discharges include nutrients and heavy metals. The observations of conduit sources fit with the findings of the water quality, sediment quality and sediment fingerprinting analysis.

The Gilwiskaw Brook, in Ashby-De-La-Zouch and Packington, appears to have a particularly high number of conduit source inputs. This is most likely due to the higher number of roads and hard standing areas in these semi-urban environments, confirming the findings of the quality and fingerprinting analysis which highlighted the importance of urban and road sources. These areas, in particular, require the introduction of measures that will help to mitigate the impact of both pipe discharges and road runoff.

The exact location of the observed conduit sources is documented in the walkover survey report and associated GIS. The evidence from the quality and fingerprinting investigation combined with the potential location of sources provides a powerful tool for the consideration of measures to address the connectivity between potential road and urban sources with the watercourse.

3.5.1 Wet weather sampling

A total of 48 samples were collected from 8 conduit source sites on 20th February 2015. The sites were selected so as to be representative of the range of different road types, to cover

APEM Scientific Report 413482 the potential cumulative downstream impact of road input and from a health and safety perspective. Full details of the walkover survey site location are given in the accompanying report (Appendix 2). From each site a sample was taken up stream of the conduit (U), at the conduit source (S) and downstream from the conduit input (D). Each site was sampled in duplicate to create a 48 sample data set (samples labelled 1 or 2_sample site/location (U/S/D). Full data for the contaminant metal concentrations in the walkover survey samples are given in the accompanying electronic appendix (Appendix 1 to Mease Report_Feb_2015.xlsx)

3.5.2 Bioavailability of metals from conduit sources

Aluminium (Al) Aluminium concentrations were high in all the walkover survey water samples analysed (Appendix1_Mease Report_Feb_2015_Waters.xlsx). Possible sources of dissolved aluminium in the River Mease waters include input from historical mining activities in the area which may also affect conduits and associated road run off. All dissolved aluminium concentrations exceeded the current guidelines and ranged from 19 – 50 µg/L in the samples collected directly from the conduit sources and from 16 – 90 µg/L across all the river water samples. Aluminium concentrations were highest upstream and downstream at site 1 (79 and 90 µg/L respectively) in the first set of samples but no conduit source was collected at this site so it is impossible to link these findings to run-off. These concentrations of aluminium are much higher than the suggested Probable No Effect Concentrations (PNEC values) for aluminium of 0.05 µg/L (long-term) and 0.25 µg/L (short-term) in UK freshwaters. Evidently the dissolved aluminium concentrations measured in these waters have the potential to impact upon aquatic life, although the current lack of officially adopted environmental standards for aluminium in surface waters in the UK (Environment Agency, 2007) provides no clear basis for tackling this issue.

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Ashby-de-la-Zouch

AT 3

Packington

8 5 7 Measham

Figure 23: Locations of wet weather samples collected on 20th February 2015

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Chromium, Manganese, Iron, Nickel, Arsenic, Cadmium, and Lead (Cr, Mn, Fe, Ni, As, Cd, Pb) The measured dissolved concentrations of these metals were generally below the generic Environmental Quality Standards (EQS) (Table 2) so inputs from the conduits cannot be considered problematic. High concentrations of dissolved manganese were measured in the source samples from two sites 2_ATS (208 µg/L) and 2_5S (205 µg/L) on the second sampling sweep only. At these sites manganese concentrations were also slightly elevated in downstream receiving water samples compared to the upstream samples (i.e. 2_ATU, 1.99 µg/L compared to 2_ATD_4.43 µg/L and 2_5U, 1.25 µg/L compared to 2_5D, 5.05 µg/L) but these dissolved manganese concentrations in the receiving waters remain well below the generic EQS of 123 µg/L.

Copper and Zinc (Cu, Zn) Copper and zinc concentrations were high in all samples and exceeded the current generic Environmental Quality Guidelines (Table 2) in most cases (Appendix1_Mease Report_Feb_2015_Waters.xlsx). Therefore, for the upstream and downstream samples, local EQS and bioavailable metal concentrations were calculated for these metals using the bio-met.net software tool to determine if contaminant inputs from the conduit sources had the potential to adversely impact the aquatic biota in the channels. Measured dissolved organic carbon (DOC) concentrations ranged from 4.8 mg/L to 10.5 mg/L and calcium (Ca2+) concentrations ranged from 28.3 mg/L to 100 mg/L in the upstream and downstream samples in the walkover survey. Values for bioavailable concentrations of copper and zinc, (calculated using the bio-met.net software (http://bio-met.net/)) in the walkover survey samples are given in the electronic appendix (Appendix 1_ Mease Report_Feb_2015_Waters.xlsx).

From the bio-met modelling data it is clear that in all samples bioavailable concentrations of copper and zinc were below the derived Local EQS calculated for each sample, and all have a Risk Characterisation Ratio (RCR) less than 1. This indicates that, in water samples taken from the channels upstream and downstream of the conduits identified walkover survey, measured concentrations of copper and zinc were not of concern at the time of sampling. In accord with the principals of the BLM (as described in section 1.4), these results are due to the high levels of measured DOC (a competitive binding ligand for metal ions in solution) and calcium (which competes for metal binding sites at the biotic ligand) in the waters which greatly reduce the potential for metal interaction with, and subsequent toxicity to, aquatic life.

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Platinum Group Elements (PGE) There were measureable concentrations of the platinum group elements, which are linked to road runoff, particularly Rh and Pd in many of the samples (Appendix1_Mease Report_Feb_2015_Waters.xlsx) but no clear trends were observed for elevated levels of these metals in the samples downstream of the conduit inputs.

These results indicate that water pollution impacts from the conduit sources identified in the walkover survey were not a specific issue at the time of sampling.

4. Summary and Recommendations

The results from the summer field monitoring investigations on the Gilwiskaw brook (Rogers et al 2014) provided a robust water quality baseline data set against which data from pre and post road gritting winter storm events can be compared and evaluated. During the measured winter storm events monitored from October to December 2014, spikes in metal concentrations demonstrate the link between stream water quality and the surrounding road network.

Looking in detail at the A42 road crossing at Packington, in the baseline water quality samples, concentrations of both copper and zinc were marginally above the generic EQS both above and below the main A42 crossing point with the Mease channel. However, bioavailable concentrations of these metals were all well below the sites-specific EQS derived from the local water chemistry. Concentrations of dissolved copper, zinc and nickel were elevated in the storm events compared to the baseline samples but were broadly similar across the storm events. The specific link with elevated metal concentrations in the stream and inputs from the A42 road drain however, is much clearer for the winter storm events (collected on 09/12/2014 and 11/12/2014) than for the events monitored earlier in the year. A tiered approach to risk assessment was used to demonstrate that during the storm events the concentrations of dissolved metals in the waters remained below the locally- derived site-specific EQS required by the Water Framework Directive. These results indicate that water pollution impacts on aquatic life are not a specific issue.

The demonstrated link between elevated metal concentrations and storm water inputs though is important. The sediment quality data demonstrate contamination to river bed substrate that is in excess of guidelines for risk to aquatic life. At road crossing nodes throughout the catchment, elevated copper, zinc and lead concentrations were observed in stream sediments that are in proximity to A class roads with hotspots at crossings with the 61

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A42. Sediment fingerprinting supports a significant proportion of road-related sediment inputs at these sites. For example, there was a notable increase in Cu associated with sediment from the Gilwiskaw Brook site above to below the A42 crossing (site 8) with concentrations reaching 122 ± 11 mg/kg-which is in excess of the Canadian interim freshwater sediment quality guideline (ISQG) of 35.7 mg/kg and is approaching the probable effect levels (PEL) of 197 mg/kg. A similar pattern was observed at the Stretton site above and below the A42 crossing (site 12). Here concentrations of copper reached 160 ± 0.3 mg/kg, zinc 978 ± 14.7 mg/kg and lead 126 ± 7.1 mg/kg in the downstream sediments. All these values are above the ISGQ values for these elements (35.7 mg/kg, 123 mg/kg and 35 mg/kg respectively) with the latter two results for zinc and lead also exceeding the PEL (315 mg/kg and 91.3 mg/kg) for adverse effects on aquatic life.

These elevated levels of sediment contaminants coupled with the known high residence time of fine sediment in these channels (prior sediment tracing work) presents a problem. The spatial analysis of sediment quality and the fingerprinting show the importance of A road crossings as ‘point’ sources but also the importance of urban areas in terms of spatial extent (this could be considered a type of ‘diffuse’ source given the multiple drainage entry points).

Some evidence was also identified as to an effect of historic mining activity within the catchment. Elements associated with mining which may be slowly released into the watercourse through leaching were detected.

The spatial pattern of metal loadings in Gilwiskaw Brook and the wider catchment sediment shows clear linkages between contaminant level and inferred traffic density according to road classification. Targeting mitigation measures on A roads is recommended to reduce metal inputs to stream and river sediment habitats. Mitigation should attempt to reduce the connectivity between road generated runoff (and associated sediment transport) and discharge into the watercourse. While the urban areas are also a contributor due to spatial extent, mitigation would be severely hampered by the complexity of urban drainage systems and multiple points of storm water entry.

The walkover survey identified a large number of potential sources where diffuse pollution enters the watercourse. The majority of the sources related to conduits or pathways by which pollution can enter the watercourse. Of these, there were a significant number of sources classified as road runoff or pipes, the latter associated with urban developments. The walkover survey, combined with the sediment quality and fingerprinting analysis 62

APEM Scientific Report 413482 provides a spatial database of issues and potential sources which can now be used to target further investigations of specific potential sources and pathways. The key area identified for action is the A42 road crossings on Gilwiskaw Brook where the greatest elevation in metals concentrations was observed in bed sediments with a notable downstream footprint in terms of Zn pollution.

The exact locations of potential diffuse pollution connections to the Gilwiskaw Brook are identified and mapped in the walkover survey report and associated GIS (Appendix 1). The fingerprinting study, and wet weather survey, confirm the importance of addressing sources of pollution associated with road pathways/sources. The most significant sources appear to be those north of the A42 crossing of the Gilwiskaw Brook and extending into Ashby de la Zouch (sample point 3 upstream to point 1 in Figure 23).

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5. References Blake WH, Haley S , Smith HG, Goddard R, Comber S, Gaspar L, Taylor A. (2014). River Mease Sediment Fingerprinting: An evaluation of Sediment Sources and Pathways in the River Mease. APEM 412766a, March 2014, 37pages.

Campbel PGC (1996) Interactions Between Trace Metals and Aquatic Organisms: A Critique of the Free Ion Activity Model. Metal Speciation and Bioavailability in Aquatic Systems. Ed. Andre Tessier and David R. Turner. Vol. 3. New York: John Wiley & Sons, Inc. p 45-102.

Canadian Council of Ministers of the Environment. (1995) Protocol for the derivation of Canadian sediment quality guidelines for the protection of aquatic life. CCME EPC-98E. Prepared by Environment Canada, Guidelines Division, Technical Secretariat of the CCME Task Group on Water Quality Guidelines, Ottawa. [Reprinted in Canadian environmental quality guidelines, Chapter 6, Canadian Council of Ministers of the Environment, 1999, Winnipeg.]

Di Toro DM, Allen HE, Bergman HL, Meyer JS, Paquin PR, Santore RC. (2001) Biotic Ligand Model Of The Acute Toxicity Of Metals. 1. Technical Basis. Environmental Toxicology and Chemistry, 20, 2383-2396.

Environment Agency (2007) Proposed EQS for Water Framework Directive Annex VIII substances: aluminium (inorganic monomeric). ISBN: 978-1-84432-651-8 http://www.wfduk.org/sites/default/files/Media/aluminium.pdf

Environment Agency (2011) Chemical Standards Report Nickel http://evidence.environment- agency.gov.uk/ChemicalStandards/report.aspx?cid=97.

Environment Agency (2011) Chemical Standards Report Cadmium. http://evidence.environment-agency.gov.uk/ChemicalStandards/report.aspx?cid=29.

Environment Agency (2011) Chemical Standards Report Iron. http://evidence.environment- agency.gov.uk/ChemicalStandards/report.aspx?cid=84

Environment Agency (2011) Chemical Standards Report Arsenic. http://evidence.environment-agency.gov.uk/ChemicalStandards/report.aspx?cid=11

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European Commission (2000). Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy. http://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=CONSLEG:2000L0060:20090625:EN: PDF.

WFD- UKTAG (2008); UK Environmental Standards and Conditions; (Phase 1); Final report (SR1 – 2006), April 2008. http://www.wfduk.org/sites/default/files/Media/Environmental%20standards/Environmental% 20standards%20phase%201_Finalv2_010408.pdf

WFD-UKTAG (2013) Updated Recommendations on Environmental Standards River Basin Management (2015-21) 80 pages http://www.wfduk.org/sites/default/files/Media/Environmental%20standards/UKTAG%20Envir onmental%20Standards%20Phase%203%20Final%20Report%2004112013.pdf

WFD-UKTAG (2014) River and Lake Assessment Method Specific Pollutants (Metals) Metal Bioavilability Assessment Tool M-BAT Water Frame Work Directive ISBN: 978-1-906934- 57-6 http://www.wfduk.org/sites/default/files/Media/Characterisation%20of%20the%20water%20e nvironment/Biological%20Method%20Statements/MBAT%20UKTAG%20Method%20Statem ent.pdf

Pagenkopf GK (1983). Gill Surface Interaction Model for Trace-Metal Toxicity to Fishes: Role of Complexation, pH and Water Hardness. Environmental Science and Technology 17: 342– 347. doi:10.1021/es00112a007

Paquin PR; Gorsuch JW, Apte SC, Batley GE, Bowles KC, Campbell PGC, Delos CG, Di Toro DM, Dwyer RL, Galvez F, Gensemer RW, Goss GG, Hogstrand C, Janssen CR, McGeer JC, Naddy RB, Playle RC, Santore RC, Schneider U, Stubblefield WA, Wood CM, Wu KB. (2002). The biotic ligand model: a historical overview Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology. 133 (1-2): 3–35.doi:10.1016/s1532- 0456(02)00112-6

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Niogi S; Wood CM. (2004). Biotic Ligand Model, a Flexible Tool for Developing Sit-Specific Water Quality Guidelines for Metals Environmental Science and Technology 38 (23): 6177– 6192. doi:10.1021/es0496524.

Taylor A , Blake WH , Comber S, Goddard R, Fisher A, Smith HG, Gaspar L, Darmovzalova J. (2014) Investigation of road runoff inputs from the A42 into the River Mease, UK: winter 2013/14 APEM March 2014 38 pages.