Metals in water and foams from NOM-rich sub-alpine streams

Similar documents
Assessment of Arsenic and Trace Metal Contaminations in Riverine Water and Sediments Resulted from the Coal Ash Spill in Kingston, Tennessee

Stimulation of Natural Attenuation of Metals in Acid Mine Drainage through Water and Sediment Management at Abandoned Copper Mines

Worldwide Pollution Control Association

Dimethylglyoxime Method Method to 6.0 mg/l Ni TNTplus 856

Pebble Project Surface Water Quality Program Streams, Seeps, and Ponds

Summary of Preliminary Results of EPA Remedial Investigation Molycorp molybdenum mine Questa, New Mexico

MINING POLLUTION OF STREAM SEDIMENTS OF THE SMOLNIK STREAM. O. Lintnerová, P. Šottník, S. Šoltés

EU water analysis using the Thermo Scientific icap 7400 ICP-OES Duo

Investigation of the Impact of Forrest Fires on the Chemistry and Water Quality of Ground Water in Yellowstone National Park

The Determination of Trace Elements in Stainless Steel by Forked Platform GFAAS

Determination of Elemental Impurities in Graphite-based Anodes using the Agilent 5110 ICP-OES

The image part with relationship ID rid4 was not found in the file. Welcome

Use of Fly ash from KKAB, Sweden Sealing a landfill with only fly ash

Ecotoxicology studies with sediment, pore water, and surface water from the Palmerton Zinc site

A Hydrologic Study of the North Hills, Helena, Montana

STUDY OF ELEMENT FINGERPRINTING IN GOLD DORÉ BY GLOW DISCHARGE MASS SPECTROMETRY

Dissolved Organic Carbon Augmentation:

EU Water Analysis Using the Thermo Scientific icap 7400 ICP-OES Duo

Method (0.1 to 8.0 mg/l Cu) TNTplus 860

Mount Polley Mining Corporation an Imperial Metals company Box 12 Likely, BC V0L 1N0 T F

JEFFERSON RIVER METALS TMDL PROJECT. Public Meeting October 14, 2014 Whitehall, MT

Trace Elements: 2011 Agency Meeting

Soil Water Quality of Reforested Mine Site Twelve Years After Reclamation

Use of Physicochemical Changes in NOM to Evaluate THM. Formation During Snowmelt, After Wildfires, and in Pre- Ozonation Water Treatment

1. Introduction. 2. Scope and application. 3. Objectives

A Colorimetric and Ratiometric Fluorescent Chemosensor. with a Large Red-shift in Emission: Cu(II)-only Sensing by

Effects of Precipitation on the Acid Mine Drainage Impacted Hewett Fork Watershed Understanding Storm Response

Heavy metal stabilization in EAFD using magnesia and Sorel cements

OBSERVATIONS OF CHANGING HABITAT AND BENTHIC INVERTEBRATE COMMUNITIES FROM THE SIERRA NEVADA SENTINEL STREAM NETWORK DURING EXTENDED DROUGHT Dave


ABSTRACT: Clean sampling and analysis procedures were used to quantify more than 70 inorganic chemical constituents (including 36 priority

Application of biochar produced from wood and seaweed for the removal of dye in wastewater

Dynamic Waste Water Modeling for Coal Burning Power Plants

9 Mineral particles, mainly windblown dust from local soil: Li, A1, Sc, (V), Cr, Fe, (Co), Ga, Y, La, Sm, Th, U;

Nick Shepherd University of Oklahoma

MONITORING AND RESEARCH DEPARTMENT

RESEARCH AND DEVELOPMENT DEPARTMENT

Chemical quality of household water in Bangladesh

Table I: MCL and MRL Concentrations for Contaminants Monitored Under the Safe Drinking Water Act National Primary Drinking Water Regulations

Prediction of Source Term Leachate Quality from Waste Rock Dumps: A Case Study from an Iron Ore Deposit in Northern Sweden

Analysis of Toxic Trace Elements in Coffee Bean Products by HR ICP-OES

Quality Monitoring of Natural Water from Southwest District of Moscow Using Total Reflection X-ray Fluorescence Analysis

THE EFFECTS OF EXTREMELY HIGH DENSITY SEPTIC SYSTEMS ON SURFACE WATER QUALITY IN GWINNETT COUNTY, GEORGIA

Application of PMF analysis for assessing the intra and inter-city variability of emission source chemical profiles

Trace elements leaching from cement mixtures containing fly ash. Nadya Teutsch and Olga Berlin Geological Survey of Israel

Sub-Project A2: Simultaneous Removal of Inorganic Contaminants, DBP Precursors, and Particles in Alum and Ferric Coagulation

PRESENT AND FUTURE RISKS OF EXCESS HEAVY METAL INPUT TO TERRESTRIAL ECOSYSTEMS IN THE KOLA PENINSULA

Drinking Water Supply and

Merits of EPA Method 1640:

A FIELD DEMONSTRATION OF AN ALTERNATIVE COAL WASTE DISPOSAL TECHNOLOGY GEOCHEMICAL FINDINGS. Paul T. Behum. Liliana Lefticariu. Y.

CONTRASTING STREAM WATER NO 3 - AND CA 2+ IN TWO NEARLY ADJACENT CATCHMENTS: THE ROLE OF SOIL CA AND FOREST VEGETATION

Detroit Water and Sewerage Department Water Quality Division Laboratory Analysis of Water Samples Collected at Lake Huron Plant 10/14/2014

Application of New Leaching Protocols for Assessing Beneficial Use of Solid Wastes in Florida. Technical Awareness Group Meeting June 30 th, 2015

APICE intensive air pollution monitoring campaign at the port of Barcelona

Analysis of Mineral and Heavy Metal Content in Beverages Using the Teledyne Leeman Labs Prodigy Plus ICP-OES

Newcastle Creek Community Watershed Water Quality Objectives Attainment Report

Inductively coupled plasma (ICP) spectroscopy for online measurements of trace metal emissions at the 250 kw PACT furnace

Trace Element Analysis of Industrial Wastewater and Sewage with TXRF. Bruker Nano GmbH Berlin, Germany, February 23 rd, 2011

Exporter: SEISHIN Trading Co., Ltd.

Dimethylphenol Method Method LR (0.23 to mg/l NO 3 N or 1.00 to mg/l NO 3 ) TNTplus 835

Seasonal Source Water Quality and Treatment Challenges Town of Newburgh s Chadwick Lake Filtration Plant

SCOPE OF ACCREDITATION TO ISO/IEC 17025:2005

Release of metals from unprocessed and processed black shale due to natural weathering

Chris Gammons, Montana Tech. Rio Tinto, Spain

Sources and transport of mercury and methylmercury in rivers and streams of the Upper Mississippi River watershed

Biochar. A comparison of biochar volumes to increase plant growth and reduce soil acidity. Research Services LLC Silverton, CO (970)

Blank Optimization Using Ultrapure Water Suitable for Trace Ion Analysis.

Riverbank Sediment Characterization & Preliminary Treatment Results

Earth Science Department, University of Arkansas at Little Rock, 2801 S University Ave Little Rock, AR 72204

Radial, Axial or Dual View ICP: Which Do You Choose? Manny Almeida Teledyne Leeman Labs, Inc. Hudson, NH

Supporting Information

Metal/metalloid accumulation/remobilization during aquatic litter decomposition in freshwater

SUMMARY.

Special Publication SJ2004-SP22 St. Johns River Water Supply Project Surface Water Treatment and Demineralization Study

March 24, 2016 Shaun Payne & Daniel Large, EAHCP

A3: Contaminant Reduction, Life Cycle Impacts, and Life Cycle Costs of Ion Exchange Treatment and Regeneration

SCHEDULE I LIST I GENERAL STANDARDS AND CRITERIA FOR THE DISCHARGE OF INDUSTRIAL EFFLUENTS INTO INLAND SURFACE WATERS

SinoTropia. Watershed Eutrophication management in China through system oriented process modelling of Pressures, Impacts and Abatement actions

RECOMMENDED SCOPE OF ACCREDITATION (For Testing Laboratories) * Test Method / Standard against which tests are performed

Detroit Water and Sewerage Department Water Quality Division Laboratory Analysis of Water Samples Collected at Lake Huron Plant 6/9/2015

Regional Water Quality NEWSLETTER DATE: Report for November 2017 A Tempe, Glendale, Peoria, Chandler, Phoenix, ADEQ, CAP, SRP, Epcor NSF Central

Analysis of Trace Elements in Seawater Using the Thermo Scientific icap 7000 Series ICP-OES Duo

Biochar for Stormwater Treatment:

Analysis of Metals in Water, Stream Sediments and Floodplain Soils Collected March 21-23, 2005 from the Bayou Creek System. David J.

Regional Water Quality NEWSLETTER DATE: Report for May 2018 A Tempe, Glendale, Peoria, Chandler, Phoenix, ADEQ, CAP, SRP, Epcor NSF Central

CANADA BRITISH COLUMBIA WATER QUALITY MONITORING AGREEMENT

COMPARISON OF ELEMENT CONTENT DISTRIBUTION IN MOSS, GRASS AND SPRUCE NEEDLES IN CONIFEROUS FORESTS IN THE CZECH REPUBLIC IN

Western Forest Fires and Long-term Impacts on Water Quality ASHLEY RUST, PHD

Warm Mineral Springs Sampling by Sarasota County

Collaborative Efforts for Creating a Robust Trace Metals Analytical Procedure for Flue Gas Desulfurization Wastewaters by ICP-MS

Model based monitoring of stormwater runoff quality. Heidi Birch, Luca Vezzaro, Peter Steen Mikkelsen

Direct Analysis of Photoresist by ICP-MS. Featuring the Agilent Technologies 7500s ICP-MS

TITLE: SABS PROFICIENCY TESTING SCHEME, RSA

Changes in DOC and NOM characteristics through watercourses from Fennoscandinavian headwaters to high order streams

Metals in the Benthic Macroinvertebrates in Coal Creek, Crested Butte, CO

Cyanide Analysis: Cyanide Chemistry, Methodology, Interferences, Sample Handling and Regulatory Updates

CHARACTERIZATION OF DYE INDUSTRY EFFLUENT AND ASSESSMENT OF ITS SUITABILITY FOR IRRIGATION PURPOSE

Implications for Exploration With The Use of High Resolution ICP-MS Technology. Eric L. Hoffman, Yakov Kapusta and M. Dzierzgowska


Origin, signature, and interaction of coal bed methane produced water natural organic matter with inorganic solutes

Transcription:

Metals in water and foams from NOM-rich sub-alpine streams Ola Sæther 1, Donald Macalady 2, Øyvind Mikkelsen 1, Shafia Iftekhar 1, Ånund Killingtveit 1 1 Geological Survey of Norway (NGU) Trondheim Norway 2 Colorado School of Mines (CSM) Golden Colorado United States 3 Norwegian University of Science and Technology (NTNU) Trondheim Norway

BACKGROUND River water consists of organic matter from terrestrial and aquatic sources. The terrestrial natural organic matter (NOM) has been subject to physicochemical reactions during transport, e.g. sorption and redox reactions, which affect and possibly homogenize the chemical composition of NOM. Change towards a warmer and wetter climate is assumed to intensify leaching of NOM in sub-alpine environments. This may affect the chemical composition of natural waters and increase costs of water treatment.

INTRODUCTION We have studied metal transport in a dozen tributary streams of lake Jonsvatnet, - the water supply for the city of Trondheim (pop.160 ), NO, by analyzing samples of water and foams floating on the streams. All streams are brown-water streams with elevated concentrations of aqueous natural organic matter (NOM). The NOM content varies seasonally and with episodic rainfall events and annual snow melt.

Trondheim City Jonsvatnet

Quaternary geological map of Jonsvatnet. Source: Reite (1983)

METHODS Fourteen different locations in the Jonsvatnet catchment were selected for which 11 were sampled frequently (i.e. 22x during Aug 07- May 08). More than 350 samples of water and 40 of foam were collected and analyzed. - NOM content Determined as concentration of dissolved organic carbon (DOC) on filtered samples (0.45µm) in mgc/l - SUVA(Specific UV-Absorbance @254nm ) a) Water samples analyzed w/simadzu UV mini 1240 UV-Vis spectrometer on liquid samples in 1.0cm quartz cell in L/mgC b) Foam samples were diluted 10x with deionized water to concentrations yielding a maximum absorbance less than one. - ph a) Standard glass electrode w/radiometer Copenhagen phm80 b) and after adding 1g of NaNO 3 to the water sample. - EC (Electrical Conductivity) Radiometer Analytical Ion Check 30 in liquid sample in μs/cm - Metal content 35 major, minor, and trace metals were determined for each sample using ICP-MS in mg/l.

Sample Periods and Sites For a better interpretation results were distributed in periods: Period 1: August and September Period 2: October and November Period 3 : February Period 4: Spring (March, April and May)

Site 1 SITE 1 Period 1 Period 2 DOC (mgc/l) 13.2 7.7 Abs 254nm (1.0cm cell) 0.507 0.308 SUVA (L/mgC) 0.0377 0.0398 ph (w NaNO3) 5.79 6.78 Conductivity (ms/cm) 50.9 63.5 Discharge (L/s) 225 64

Site 4 SITE 4 Period 1 Period 2 Period 3 Period 4 DOC (mgc/l) 9.9 11.9 8.1 6.7 Abs 254nm (1.0 cm cell) 0.41 0.418 0.337 0.295 SUVA (L/mgC) 0.041 0.04 0.039 0.044 ph (w NaNO3) 6.35 6.74 6.59 6.64 Conductivity (ms/cm) 55.5 56.7 48.4 44.6 Discharge (L/s) 344.6 765 1233.5 209

Site 5 SITE 5 Period 1 Period 2 Period 3 Period 4 DOC (mgc/l) 7.9 7.7 7.5 5.7 Abs 254nm (1.0cm cell) 0.363 0.321 0.29 0.242 SUVA (L/mgC) 0.045 0.042 0.038 0.042 ph (w NaNO3) 6.32 6.52 6.64 6.5 Conductivity (ms/cm) 67 44.3 44 40.6 Discharge (L/s) 124 309.3 896 121.7

Site 6 SITE 6 Period 1 Period 2 Period 3 Period 4 DOC (mgc/l) 6.9 6.2 5.4 4.7 Abs 254nm (1.0cm cell) 0.282 0.241 0.205 0.201 SUVA (L/mgC) 0.041 0.04 0.038 0.042 ph (w NaNO3) 6.05 6.82 6.64 6.42 Conductivity (ms/cm) 87.6 75.2 69.3 53.8 Discharge (L/s) 222.5 282.7 692 155.6

Site 7 SITE 7 Period 1 Period 2 DOC (mgc/l) 7 5.45 Abs 254nm (1.0cm cell) 0.243 0.296 SUVA (L/mgC) 0.035 0.086 ph (w NaNO3) 6.52 6.53 Conductivity (ms/cm) 75.1 59.1 Discharge (L/s) 74.5 132

Site 8 SITE 8 Period 1 Period 2 DOC (mgc/l) 12.9 10.4 Abs 254nm (1.0cm cell) 0.463 0.386 SUVA (L/mgC) 0.036 0.037 ph (w NaNO3) 5.48 6.51 Conductivity (ms/cm) 54.3 61 Discharge (L/s) 11 15.7

Site 9 SITE 9 Period 1 Period 2 DOC (mgc/l) 10 8.2 Abs 254nm (1.0cm cell) 0.4 0.344 SUVA (L/mgC) 0.04 0.042 ph (w NaNO3) 6.38 6.97 Conductivity (ms/cm) 67.6 109 Discharge (L/s) 31 47

Site 10 SITE 10 Period 1 Period 2 DOC (mgc/l) 10.6 9.5 Abs 254nm (1.0cm cell) 0.477 0.375 SUVA (L/mgC) 0.045 0.039 ph (w NaNO3) 5.74 6.66 Conductivity (ms/cm) 54.6 41 Discharge (L/s) 55 55

Site 11 SITE 11 Period 1 Period 2 Period 3 Period 4 DOC (mgc/l) 10.2 5.9 5.9 4.6 Abs 254nm (1.0cm cell) 0.407 0.2216 0.218 0.123 SUVA (L/mgC) 0.039 0.039 0.037 0.041 ph (w NaNO3) 6.64 6.73 6.68 6.35 Conductivity (ms/cm) 77 82.8 67.1 59 Discharge (L/s) 197.8 231 750 80.4

Site 11 A SITE 11A Period 1 Period 2 DOC (mgc/l) 10.3 9.9 Abs 254nm (1.0cm cell) 0.484 0.407 SUVA (L/mgC) 0.048 0.041 ph (w NaNO3) 6.86 6.95 Conductivity (ms/cm) 74.5 69 Discharge (L/s) 75.5 113

Site 13 SITE 13 Period 1 Period 2 Period 3 Period 4 DOC (mgc/l) 6.4 5.4 5 Abs 254nm (1.0cm cell) 0.246 0.199 0.142 SUVA (L/mgC) 0.039 0.036 0.04 ph (w NaNO3) 7.04 7.02 6.92 Conductivity (ms/cm) 184.9 139.8 126.2 Discharge (L/s) 119.6 363

Some general observations (all streams) Highest value (period) Lowest value (period) DOC 1 4 Abs (254 nm) 1 4 SUVA 4 3 Discharge 3 4 ph 2 1 Conductivity 1 / 2 4

NOM mgc/l NOM trends NOM (x,t) 20 18 16 14 Falling trend with time of year 12 10 8 NOM1 NOM2 NOM3 NOM4 6 4 2 0 0 1 2 3 4 5 6 7 8 9 10 11 11A 12 13 14 Site NOM concentration in mgc/l as function of period at the different sampling sites.

Flow (l/s) NOM mgc/l NOM (mg C/L) vs. Flow (L/s) NOM (x,t) 20 15 10 NOM1 NOM2 5 0 0 1 2 3 4 5 6 7 8 9 1400 10 11 1211A 13 14 Site NOM3 NOM4 Flow (x,t) 1200 1000 NOM; highest in period 1 and lowest in Period 4. Flow highest in Period 3 and lowest in Period 4. 800 600 400 Period 1 Period 2 Period 3 Period 4 200 0 11A 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Site

SUVA (L/mg C) 0.0600 0.0550 0.0500 0.0450 SUVA1 SUVA2 SUVA3 SUVA4 0.0400 0.0350 0.0300 11A 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 SUVA highest in period 1 and 4

Metals vs. DOC in water

Foam studies

Correlations in foam Site 1 Cd114 (1) Hg220 (1) Pb208 (1) Mg25 Al27 (1) Si30 P31 S34 (1) Ca43 Mn55 (1) Fe57 (1) Cu63 (1) Zn67 (1) As75 (1) Cd114 (1) Hg220 (1) -0.2 Pb208 (1) 0.5-0.8 Mg25-0.5 0.9-0.8 Al27 (1) -0.6 0.9-0.9 1.0 Si30 0.5-0.8 0.5-0.9-0.8 P31-0.9 0.1-0.6 0.4 0.5-0.2 S34 (1) -0.6 0.9-0.9 1.0 1.0-0.8 0.5 Ca43-0.5 1.0-0.9 1.0 1.0-0.9 0.3 1.0 Mn55 (1) -0.3 0.3-0.8 0.3 0.5 0.1 0.7 0.5 0.3 Fe57 (1) -0.5 0.9-0.9 1.0 1.0-0.9 0.4 1.0 1.0 0.3 Cu63 (1) -0.1 0.8-0.9 0.7 0.7-0.3 0.3 0.8 0.7 0.8 0.7 Zn67 (1) 0.6-0.8 1.0-0.9-1.0 0.7-0.6-1.0-0.9-0.6-0.9-0.8 As75 (1) -0.4 1.0-0.9 1.0 1.0-0.8 0.3 1.0 1.0 0.4 1.0 0.8-0.9 Correlation greater then ± 0.75 in approx 60% of all relations Correlation greater then ± 0.5 in approx 80% of all relations foam samples collected over a period of approx 5 weeks

Correlations in foam Site 4 Cd114 (1) Hg220 (1) Pb208 (1) Mg25 Al27 (1) Si30 P31 S34 (1) Ca43 Mn55 (1) Fe57 (1) Cu63 (1) Zn67 (1) As75 (1) Cd114 (1) Hg220 (1) -0.3 Pb208 (1) -0.4 0.8 Mg25-0.4 0.9 0.9 Al27 (1) -0.4 0.7 0.8 0.9 Si30-0.2 0.9 0.9 0.7 0.5 P31-0.2 0.8 0.8 0.9 1.0 0.6 S34 (1) -0.4 0.8 0.9 1.0 1.0 0.7 1.0 Ca43-0.3 0.7 0.8 0.9 1.0 0.6 0.9 0.9 Mn55 (1) -0.3 0.7 0.7 0.7 0.8 0.6 0.9 0.8 0.8 Fe57 (1) -0.4 0.7 0.8 0.9 1.0 0.6 1.0 1.0 0.9 0.8 Cu63 (1) -0.2 0.8 0.9 0.8 0.6 0.9 0.7 0.8 0.7 0.5 0.6 Zn67 (1) 0.7 0.0-0.1-0.1-0.1 0.1-0.1-0.1 0.1-0.1-0.2 0.2 As75 (1) -0.4 0.8 0.9 1.0 1.0 0.7 1.0 1.0 1.0 0.8 1.0 0.7-0.1 Correlation greater then ± 0.75 in approx 51% of all relations Correlation greater then ± 0.65 in approx 64% of all relations Correlation greater then ± 0.5 in approx 74% of all relations Foam samples collected over a period of 10 weeks

Relations foams vs. water 21.8.07 28.8.07 4.9.07 14.9.07 AVG STDEV RSD % 22.10.07 1.11.07 8.11.07 AVG STDEV RSD % Cd114 (F) 1.22 0.52 0.38 0.40 0.74 0.20 3.61 Cd114 (S) 0.137 0.031 0.020 1.029 0.020 1.364 0.198 8.9 16.6 19.3 0.4 11.3 8.5 75.2 36.0 0.1 18.2 18.1 17.9 99.0 Hg220 (F) 0.36 0.48 0.25 0.29 0.01 0.10 0.01 Hg220 (S) 0.050 0.027 0.011 0.008 0.0054 0.0075 0.0038 7.1 17.8 23.8 36.0 21.2 12.1 56.9 2.6 13.7 2.1 6.1 6.6 107.3 Pb208 (F) 4.74 5.96 6.42 2.87 0.80 2.03 0.62 Pb208 (S) 1.068 0.430 0.665 0.741 0.074 0.269 0.104 4.4 13.8 9.7 3.9 8.0 4.7 59.2 10.8 7.5 5.9 8.1 2.5 30.9 Mg25 (F) 2233.94 3606.04 3601.21 2859.84 1450.00 1585.00 969.00 Mg25 (S) 1 003 794 745 865 894 707 764 2.2 4.5 4.8 3.3 3.7 1.2 32.2 1.6 2.2 1.3 1.7 0.5 28.8 Al27 (F) 614.85 2798.91 3199.95 1341.90 684.00 903.80 321.70 Al27 (S) 27.2 115.5 131.8 128.1 111.0 138.3 113.9 22.6 24.2 24.3 10.5 20.4 6.7 32.6 6.2 6.5 2.8 5.2 2.0 39.5 Si30 (F) 1854.63 1784.25 1437.75 1261.35 764.00 899.70 893.00 Si30 (S) 861 766 797 920 1 173 1 012 1 018 2.2 2.3 1.8 1.4 1.9 0.4 22.1 0.7 0.9 0.9 0.8 0.1 16.6 Ca43 (F) 14697.93 30836.27 34610.52 16776.90 16152.00 11128.00 9537.00 Ca43 (S) 6 239 4 825 4 582 5 283 5 095 4 173 4 461 2.4 6.4 7.6 3.2 4.9 2.5 51.3 3.2 2.7 2.1 2.7 0.5 19.4 Fe57 (F) 1109.74 10036.72 9902.56 4596.53 750.60 2078.40 595.20 Fe57 (S) 127.8 181.0 214.8 186.7 185.6 196.8 169.3 8.7 55.4 46.1 24.6 33.7 21.1 62.6 4.0 10.6 3.5 6.0 3.9 64.9 Cu63 (F) 85.00 67.99 82.57 25.98 6.23 8.71 6.99 Cu63 (S) 4.07 2.85 2.56 14.18 0.89 4.09 0.67 20.9 23.9 32.3 1.8 19.7 12.9 65.3 7.0 2.1 10.4 6.5 4.2 64.0 As75 (F) 2.26 7.56 7.11 3.24 0.62 1.63 0.49 As75 (S) 0.35 0.28 0.28 0.28 0.253 0.336 0.233 6.4 26.8 25.4 11.4 17.5 10.2 58.0 2.4 4.9 2.1 3.1 1.5 48.3 51.5 51.9 P1 P2 Relation between concentration of Cd, Hg, Pb, Mg, Al, Si, Ca, Fe, Cu, and As in the foam and stream in period 1 and 2.

Overall factors Rel val global Cd114 2.5 Pb208 12.6 Al27 14.4 Si30 1.0 P31 72.0 S34 4.8 Mn55 19.6 Fe57 20.8 Cu63 10.0 Zn67 6.6 As75 8.8 Hg202 15.6 Mg25 2.3 Ca43 3.1 All foam samples collected related against water samples in same period

NOM production (mg C/L) Water samples: Average 7.79 ± 0.11 Plant extracts: Feather moss Sphagnum moss Spruce Cones Spruce Needles Sorbus (Ash) Willow (Alaskan) Alder Birch(European) Bamboo 1.6 2.4 9.0 15.4 21.4 23.5 31.0

SUVA (absorbance/mg C/L) Feather moss 0.032 Sphagnum moss 0.041 Spruce cones 0.022 Spruce needles 0.006 Sorbus (ash) 0.008 Willow 0.013 Alder 0.008 Birch 0.016 Bamboo 0.040

SUVA of Natural Waters: Streams and Rivers 1. Streams entering Jonsvatnet, Norway, 250 samples of 13 sites over 8 months: 0.0402 ± 0.0047. Range 0.0249-0.0577 2. Other Central Norway streams, 8 sites, 1 sample each: 0.0401 ± 0.0045. Range 0.0312-0.0456 3. Other rivers and Streams, 10 samples worldwide: 0.0407 ± 0.0079. Range 0.0252-0.0508

Conclusions SUVA values for natural waters are typically around 0.04 L/mg C. Of the plant extracts analyzed, only the mosses have equivalent SUVA values. Despite a much lower NOM production per unit biomass, mosses may be the more important contributors to the long-term NOM reservoirs in the streams.

Conclusions (cont d) Period 3 (Winter) has the lowest values for SUVA, and period 4 (spring) has the highest SUVA value but the lowest DOC concentration. Foams acts as metal collectors in environmental systems and seems to be of importance through the mobility of metals as metal transporters. Fe, Mn, Al, Pb and Hg are in general 15 20 times higher in the foams compared to concentrations found in the streams.

Thank you for your attention!