the biosphere: a homogeniser of pb-isotope signals

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Applied Geochemistry 23 (2008) 705–722

www.elsevier.com/locate/apgeochem

AppliedGeochemistry

The biosphere: A homogeniser of Pb-isotope signals

Clemens Reimann a,*, Belinda Flem a, Arnold Arnoldussen b, Peter Englmaier c,Tor Erik Finne a, Friedrich Koller d, Øystein Nordgulen a

a Geological Survey of Norway (NGU), N-7491 Trondheim, Norwayb Norwegian Forest and Landscape Institute, Raveien 9, N-1431 As, Norway

c Department of Freshwater Ecology, Faculty of Life Science, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austriad Earth Sciences, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria

Received 12 October 2007; accepted 13 December 2007Editorial handling by R. Fuge

Available online 5 February 2008

Abstract

Rock, soil, and plant (terrestrial moss, European mountain ash leaves, mountain birch leaves, bark and wood, andspruce needles and wood) samples, collected at 3 km intervals along a 120 km long transect (40 sites) cutting the city ofOslo, Norway, were analysed for their Pb concentration and Pb-isotope ratios. A general decrease in 206Pb/207Pb,208Pb/207Pb and 206Pb/208Pb ratios, with a characteristic low variability in all plant materials and the plant-derived O-hori-zon of soil profiles, compared to rocks and mineral soils, is observed along the transect. It is demonstrated that minero-genic and biogenic sample materials belong to two different spheres, the lithosphere and biosphere, and that geochemicalprocesses determining their chemical and isotopic compositions differ widely. Background variation for both sample mate-rials needs to be established and documented at the continental and global scale before the anthropogenic influence on thegeochemistry of the earth’s surface can be reliably estimated.� 2007 Elsevier Ltd. All rights reserved.

1. Introduction

At present, different estimates of anthropogenicversus natural Pb in the atmosphere exist, from‘‘>90% anthropogenic” (Nriagu, 1979) to ‘‘<10%anthropogenic” (Strauss, 1978; Kovnacka et al.,1990). Nriagu and Pacyna (1988) used a mass balanceapproach in an attempt to prove that the majority ofheavy metals found in the biosphere are of anthropo-genic origin. Other studies demonstrate the majorweaknesses of the chosen approach (e.g., Geological

0883-2927/$ - see front matter � 2007 Elsevier Ltd. All rights reserveddoi:10.1016/j.apgeochem.2007.12.002

* Corresponding author. Tel.: +47 73 904 307.E-mail address: [email protected] (C. Reimann).

Survey of Canada, 1995). Investigations utilizingPb-isotopes at the continental to global scale invari-ably conclude that the majority of the Pb measuredin a variety of materials (precipitation, ice cores,plants used as biomonitors, organic soils) collectedat the earth surface is of anthropogenic origin (e.g.,Sturges and Barrie, 1987; Rosman et al., 1998, 2000;Bollhofer and Rosman, 2001; Novak et al., 2003).Based on isotope measurements, Bindler et al.(1999) estimated that even in northern Sweden morethan 90% of the Pb in the O-horizon of forest soilsis of anthropogenic origin and established that thereexists a ‘‘20th century airborne pollution signal”(206Pb/207Pb ratio of c. 1.15).

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706 C. Reimann et al. / Applied Geochemistry 23 (2008) 705–722

It is well documented that Pb occurs naturally inall plants. Lead is mainly taken up via root hairsand stored as pyrophosphate in cell walls (Dunn,2007). There exist quite a number of plant speciesthat concentrate Pb (accumulators and hyperaccu-mulators). Kovalevsky (1987) showed for examplethat larch and pine can contain 300 times more leadthan ‘‘average plants” collected in eastern Siberia.He demonstrated that Pb is taken up from the C-horizon at a depth of 1–3 m. As early as 1937, whenGoldschmidt first discussed the ‘‘plant pump”

(Goldschmidt, 1937), it was demonstrated that thereexist natural processes that enrich Pb in the organicsoil layer of surface soils. Plants have been success-fully used for biogeochemical exploration (Dunn,2007). This is only possible if the vast majority ofPb in the sampled plant tissues originates from theunderlying geological substrate and not from conti-nental-scale airborne contamination. Furthermore,results of numerous sub-continental to continen-tal-scale geochemical mapping projects carried outduring the last 10 years (e.g., Reimann et al.,1998, 2003; Salminen et al., 2004, 2005) have dem-onstrated that the observed Pb-concentration pat-terns in surface materials are clearly linked tonatural processes (geology and climate and a combi-nation thereof) and not to anthropogenic sources.Known pollution sources are occasionally visiblein these maps, but always at a local scale.

Studies of metal contamination near well-con-strained sources, e.g., roads (e.g., Collins, 1984; Parryand Jarvis, 2006), cities (e.g., Tiller et al., 1987; Rei-mann et al., 2006, 2007a,b) or metal smelters andrefineries (Reimann et al., 1997, 1998; Bonham-Car-ter et al., 2006) invariably show exponentiallydecreasing metal concentrations with distance tosource. At a distance of some tens of metres (high-ways; e.g., Collins, 1984; Parry and Jarvis, 2006), tensof kilometres (cities; e.g., Tiller et al., 1987; Reimannet al., 2006) to a maximum of 200 km (major smelters;e.g., Reimann et al., 1997, 1998; Bonham-Carteret al., 2006) from source, element concentrationsmeasured in a variety of surface sample materialscan no longer be separated from the background var-iation. This exponential decrease in observed concen-trations is a simple function of dilution due to theincrease in surface area being contaminated (Bon-ham-Carter et al., 2006).

Four isotopes of Pb occur naturally: 204Pb, 206Pb,207Pb and 208Pb (Faure, 1986). Lead-206 is a decayproduct of 238U, 207Pb is a decay product of 235Uand 208Pb is a decay product of 232Th, while 204Pb

is not radiogenic (Faure, 1986). The relative naturalabundance of the Pb-isotopes is 1.4% (204Pb) –24.1% (206Pb) – 22.1% (207Pb) and 52.4% (208Pb).Lead deposits show a characteristic variation of iso-topic ratios and stable Pb-isotopes are increasinglyused in environmental sciences as tracers of anthro-pogenic Pb sources (Sangster et al., 2000). The tech-nique works well when the source of Pb is wellknown and the emitted Pb has a typical ratio,clearly deviating from the local background. Forexample, Ault et al. (1970) studied changes in thePb-isotope signature with distance from a majorhighway in the United States. These authors con-cluded that a characteristic shift in the isotopic ratiowas visible in topsoil samples for several hundredmetres from the highway in the main wind direction.Hou et al. (2006) measured Pb concentration andisotopic ratios in soil profiles collected at varyingdistances to the Horne Cu Smelter in Rouyn-Noranda, Canada. The presence of the smelter isclearly indicated by a Pb-concentration peak inthe organic horizons of the soil profiles. The concen-tration peak is accompanied by a dip in the Pb-iso-tope ratio: 206Pb/207Pb from c. 1.16–1.20 to 0.98.This ratio is very close to that of the Rouyn–Noran-da ore processed in the smelter. The concentrationpeak shows the typical exponential decrease withdistance to source and both concentration and iso-topic signature of the smelter become indistinguish-able from background variation at a distance ofabout 100 km from the smelter.

The Pb-isotope signature technique has also beenused on continental and global scales, when the Pbsource is no longer well constrained (e.g., Sturgesand Barrie, 1987, 1989; Flegal et al., 1989; Hopperet al., 1991; Rosman et al., 1994). For example, Stur-ges and Barrie (1987) indicate that the Pb-isotopecomposition of atmospheric particulate matter inthe eastern United States is distinctly different fromthat in eastern Canada, with the USA aerosols dis-playing a higher 206Pb/207Pb-isotopic ratio than theCanadian aerosols. The higher isotopic ratio in theUSA aerosols was attributed to the use of MississippiValley–type Pb in the production of leaded gasolinein the USA: Pb from this source has an unusually high206Pb/207Pb-isotopic ratio (c. 1.30–1.45) compared toother Pb deposits from around the world (Sangsteret al., 2000). Hopper et al. (1991) describe significantdifferences in the isotope ratios between differentEuropean source regions. The Eurasian Pb-isotopicatmospheric signature is different from the Americansignature, a fact that has been used to deduce the

C. Reimann et al. / Applied Geochemistry 23 (2008) 705–722 707

source of observed increases of Pb concentrations inGreenland snow (Rosman et al., 1994). These authorsobserved a clear increase in the 206Pb/207Pb ratio inGreenland snow from the late 1960s to the early1980s, from c. 1.16 to c. 1.18, which was attributedto the use of Mississippi Valley–type Pb in the pro-duction of leaded gasoline in the USA (Rosmanet al., 1994). It is noteworthy that Sullivan in Canadais the larger Pb-mine with a 206Pb/207Pb ratio of1.0679 (Sangster et al., 2000) – it is not known howmuch Sullivan Pb went into the production of leadedgasoline in North America. Grousset et al. (1994)describe a typical ‘‘North American” aerosol timetrend towards high 206Pb/207Pb-isotope ratios (c.1.17–1.19) and another typical ‘‘European” trendtowards much lower 206Pb/207Pb-isotope ratios(1.10–1.12) during the 1970s and early 1980s. Thepeak in use of leaded gasoline can be linked to bothtrends. The low European values are attributed tothe use of Broken Hill ore for the production of Euro-pean leaded gasoline. Broken Hill ore has a character-istically low 206Pb/207Pb isotope ratio of 1.04(Sangster et al., 2000). Both trends meet at a ratioaround 1.15–1.17 prior to 1968 and following theyears of phasing out of leaded gasoline, first in theUSA and then in Europe. Grousset et al. (1994) usethe Pb-isotope signature of Saharan Holocene loessas an indicator of the natural background signatureof pre-industrial sediments (206Pb/207Pb-isotoperatio c. 1.20).

The interpretation that the use of MississippiValley type ore in the production of leaded gasolinein the USA led to an increase of the observed206Pb/207Pb ratio in aerosols on a large scale wasprobably correct. However, Sturges and Barrie(1987, 1989) and Flegal et al. (1989) concluded, inaddition, that three main sources of atmosphericPb can be distinguished on the basis of the observedPb isotopic ratios: USA automobile exhaust emis-sions, Canadian automobile exhaust emissions,and Canadian industrial sources (mainly smelters).They then used these different ratios for sourceapportionment. The fact that there is a natural con-tribution of Pb to the atmosphere (e.g., from soilerosion, volcanic emissions, forest fire debris, bio-genic emissions and oceanic emissions – Rasmussen,1998) and thus a natural Pb-isotope backgroundvariation was widely ignored in these and most fol-lowing studies. Estimates of the relative contribu-tion of different sources to Pb in the atmosphereand of the continental scale of Pb pollution can onlyyield reliable values when this natural variation of

Pb-isotopes is known, well documented and takeninto consideration.

1.1. Study design

Here a transect was used to determine Pb concen-tration and the Pb isotope ratios 206Pb/207Pb,208Pb/207Pb and 208Pb/206Pb in 11 sample materialscollected at the same 40 sites along a 120 kmsouth–north transect that cuts through the city ofOslo, Norway (Fig. 1). The sample materials includebedrock, complete soil profiles (C-, B- and O-hori-zon) of forest soils, terrestrial moss (Hylocomium

splendens), European mountain ash leaves, birchleaves, birch bark, birch wood, spruce needles andspruce wood. The combination of these materialsis suited to represent the response of a large partof the terrestrial ecosystems to differences in the nat-ural conditions at each site.

The city of Oslo can be considered one of the larg-est sources of anthropogenic Pb emissions in Nor-way. Thus, the impact of urbanisation and traffic onthe Pb-isotopic signature observed along the transectcan be studied relative to natural background fluctu-ations in a number of different situations. At theselected sample density of one site/3 km it was possi-ble to collect largely ‘‘untouched” natural soils evenin the city of Oslo, by using the surrounding forestsand forested parklands. One sample (site 134) wasconsciously taken in the immediate vicinity (20 m)of one of the major highways leading from Oslo tothe Swedish border (E6). A major Pb anomaly wasdetected in Oslo at site 127 (Reimann et al., 2007b)near the contact between Cambro-Silurian sedimentsand a syenite intrusion. High concentrations of Pbwere detected in most sample materials (up to2996 mg/kg Pb in the O-horizon, see Table 1). Followup work at this site resulted in the discovery of Pbmineralisation (galena) in the underlying rocks(206Pb/207Pb = 1.205, 208Pb/207Pb = 2.46, Reimann,unpublished data). Site 127 thus marks a natural Pbanomaly. Numerous skarn type sulfide deposits atthe contact between the Permian intrusives and horn-felsed metalimestones are known to occur in the areaand even downtown in the historical centre of Oslo(e.g., Nilsen and Bjørlykke, 1991). Just north of thecity the transect runs through a large forested area(Nordmarka), extensively used for recreation pur-poses by the local population. Both ends of the tran-sect cross areas with agriculture as the dominant formof land use. At the southern end urbanisation isspreading into this area. The transect also cuts a

Fig. 1. Topographical map of the survey area showing the location of the south–north transect through Oslo and the sample sites identified bysample number. Different grey shades differentiate between forests, agricultural areas and the urban developments (from Reimann et al., 2006).


Table 1Isotope ratios obtained for Mess-3 with standard deviation at NGU, Niels Munksgaards laboratory at Charles Darwin University,Australia (Munksgaard, 2007, pers. comm.) and as published in Vincente-Beckett et al. (2006). In addition to the standard deviation the95% confidence interval of the mean is provided (RSD% for Vincente-Beckett et al. (2006)

208Pb/207Pb 208Pb/206Pb 207Pb/206Pb

NGU (n = 139) 2.4981 2.0232 0.8099Standard

deviation0.0027 0.0024 0.0009

95% conf. int. ofmean

0.00045 0.00040 0.00015

Niels Munksgaard 2.5052 2.0297 0.8102Standard

deviation0.007 0.004

95% conf. int.ofmean

0.0053 0.0030

Vincente-Beckettet al. (2006)

2.0247 0.8075

Standarddeviation

0.0009 0.0038

RSD% 0.0456 0.4669


number of different rock types. Precambrian gneissesoccur at both ends of the transect, Cambro-Siluriansedimentary rocks, including black shales occur inthe city of Oslo and at the northern end of the transectin the Randsfjord area. The magmatic rocks of theOslo Rift occur at the northern fringes of the cityand throughout the forest to the north of Oslo.

Some of the key questions to be answered by thisstudy are:

– What is the influence of the city of Oslo on thePb-isotope ratios observed in the different samplematerials?

– For what distance can the anthropogenic Pb-iso-tope signal be followed before it disappears in thenatural background variation?

– Does the Pb-isotope signal change between thesample materials?

– Are minerogenic sample materials (bedrock andC- and B-horizon of soil profiles) a reliable back-ground for Pb-isotope signals observed in bio-genic materials (O-horizon of soil profiles, plantmaterials)?

– Is it possible to establish a natural backgroundvariation for Pb-isotopes in the different samplematerials?

2. Sampling and analytical methods

Criteria for site selection and details on samplingand analyses of the rock and soil samples are pro-

vided in Reimann et al. (2007a). Reimann et al.(2006) cover moss sampling and analysis, includingquality control results for all element concentrationmeasurements of plant samples. Reimann et al.(2007b,c) describe plant sampling and analyses forall other species and plant materials. All thesepapers provide a geological map of the survey area.

All Pb-isotope ratio measurements were carriedout on an inductively coupled plasma sector fieldmass spectrometer (ICP-SFMS; ELEMENT 1,Finnigan MAT, Bremen, Germany). Rock and min-eral soil samples were pulverised in an agate diskmill. They were then digested in 7 N HNO3 in acidwashed borosilicate bottles in an autoclave at200 kPa (120 �C) for 30 min. Although HNO3 aloneis not capable of extracting elements bound in a sil-icate matrix, this leaching process is generally usedin environmental exposure assessment in accor-dance with US EPA Method 3050. Samples contain-ing organic material were first decomposed by dryashing at 480 �C before they were digested by 7 NHNO3. Dry ashing is the preferred decompositionmethod for plant materials and metals such as Pb,Zn and Cd are normally retained at temperaturesbelow 500 �C (Van Loon and Barefoot, 1989). Sev-eral recent publications have compared wet and dryashing procedures for the determination of Pb-iso-topes in organic materials (e.g., Engstrom et al.,2004; Kylander et al., 2004; Komarek et al., 2006).These authors show that there are only very smalland insignificant differences in isotope ratios result-ing from the different extraction/digestion


techniques as long as careful precautions are takento avoid contamination of the samples during thedigestion procedures. The present authors usedboth, wet and dry ashing procedures for five sam-ples from the Oslo transect and the differences werestatistically insignificant. Dry ashing was finallychosen because it allows the handling of largersamples, resulting in a more representative measure-ment. All samples were diluted to Pb-concentrationsbetween 15 and 25 lg L�1 and a HNO3-concentra-tion of 5% prior to ICP-SFMS analysis. The com-mon Pb-isotope standard NIST SRM 981 wasused to correct for instrumental mass discriminationduring Pb-isotope ratio measurements. The analyti-cal signals of the isotopes 206Pb, 207Pb and 208Pbwere corrected for digestion blanks before isotoperatios from each of the 600 measurements were cal-culated. The mean and standard deviation of thesewere then calculated for each sample. Likewise thestandard NIST SRM 981 was corrected for reagentblank, before it was used for mass bias correctionson the samples.

Fig. 2. Boxplots comparing Pb-concentrations (upper left) and Pb isotohorizon of soil profiles, moss (Hylocomium splendens), MASH = Eurmountain birch bark, BWO: mountain ash wood, SNE: spruce needlemeasured in the rock samples is larger than the scale shown in the dia

The ICP-SFMS instrument was tuned on a dailybasis to provide approximately 5.5 � 106 cps 206Pb,5 � 106 cps 207Pb and 1.2 � 107 cps 208Pb for a15 lg L�1 NIST SRM 981 solution. During tuningthe ratios 207Pb/206Pb and 208Pb/206Pb were moni-tored to be able to adjust the lenses towards the cor-rect isotope ratios. The SEM (Secondary ElectronMultiplier) installed in the ICP-SFMS has two dif-ferent collection modes, analogue mode and count-ing mode. In analogue mode the secondaryelectrons are collected after they have passed sevendynodes; this mode is used for large ion currentsand there is no loss in counts due to dead time. Incounting mode, which is used for small ion currents,the secondary electrons are collected after they havepassed all 19 dynodes. In this mode it is no longerpossible to record all counts and the signal thushas to be corrected for dead time. Due to the highPb concentrations (15–25 lg/L) in the solutionsanalysed, only the analogue detector mode wasused. In this detector mode, uncertainties due todead time are avoided.

pe ratios in the 11 sample materials. C-, B-, O-hor: C-, B-, and O-opean mountain ash leaves, BIL: mountain birch leaves, BBA:s, SWO: spruce wood. The actual variation of the isotope ratiosgrams.

able 2

ead concentration (mg/kg) and lead isotope ratios in the 11 sample materials

D XCOO YCOO ALT FLITHO Pb (mg/kg) 206Pb/208Pb

Rock C-hor B-hor O-hor Moss MASH BIL BBA BWO SNE SWO Rock C-hor B-hor O-hor Moss MASH BIL BBA BWO SNE SWO

01 578741 6708487 218 GNN 3.7 12 13 19 2.2 0.43 0.37 0.21 0.3 0.02 0.08 0.463 0.509 0.507 0.4952 0.4785 0.4829 0.4824 0.4782 0.4907 0.4907 0.4815

02 582865 6706649 431 GNN 2.2 13 14 23 2.72 0.36 0.39 0.63 0.34 0.02 0.12 0.485 0.499 0.487 0.4857 0.4751 0.4787 0.4787 0.4744 0.4815 0.4815 0.4789

03 581155 6720326 430 GNN 1.3 15 17 90 2.42 0.35 0.68 0.66 1.38 0.04 0.21 0.487 0.504 0.497 0.4739 0.4746 0.4826 0.4773 0.4730 0.4803 0.4803 0.4783

04 580482 6711512 475 GNN 6.9 11 12 75 2.22 0.48 0.43 0.87 0.73 0.05 0.33 0.457 0.515 0.507 0.4732 0.4757 0.4803 0.4769 0.4735 0.4753 0.4753 0.4776

05 584618 6701621 410 GNN 3.4 4 6 29 2.99 0.51 0.38 0.67 0.73 0.1 0.24 0.508 0.497 0.491 0.4759 0.4757 0.4794 0.4792 0.4762 0.4824 0.4824 0.4753

06 581453 6698513 296 CS 17 10 15 26 2.71 0.27 0.27 0.25 0.21 0.08 0.09 0.487 0.494 0.495 0.4848 0.4771 0.4817 0.4796 0.4764 0.4843 0.4843 0.4795

07 579850 6695899 220 CS 8.5 21 9 29 1.69 0.27 0.29 0.34 0.16 0.09 0.1 0.494 0.490 0.482 0.4824 0.4769 0.4815 0.4801 0.4769 0.4796 0.4796 0.474

08 581636 6694137 325 CS 21 22 19 29 1.49 0.28 0.25 0.44 0.21 0.1 0.06 0.487 0.512 0.514 0.4929 0.4780 0.4833 0.4803 0.4755 0.4988 0.4988 0.4898

09 585167 6692022 390 CS 8.6 16 14 27 1.74 0.33 0.3 0.59 0.25 0.16 0.05 0.495 0.529 0.522 0.4989 0.4782 0.4843 0.4812 0.4757 0.4907 0.4907 0.4844

11 582095 6688877 480 CS 4.6 11 20 34 2.05 0.34 0.37 0.47 0.27 0.14 0.11 0.493 0.504 0.492 0.4858 0.4764 0.4803 0.4798 0.4751 0.4831 0.4831 0.479

12 580702 6686100 296 CS 5.6 12 11 33 1.84 0.28 0.32 0.25 0.43 0.18 0.14 0.493 0.504 0.504 0.4784 0.4771 0.4801 0.4787 0.4757 0.4798 0.4798 0.4809

13 583087 6684132 360 CS 4.1 12 14 27 1.71 0.28 0.29 0.61 0.17 0.09 0.11 0.486 0.504 0.498 0.4899 0.4766 0.4798 0.4794 0.4739 0.4859 0.4859 0.4796

14 589716 6679640 500 ORM 5.6 17 15 104 2.27 0.49 0.44 0.65 1.03 0.15 0.63 0.484 0.507 0.513 0.4751 0.4764 0.4785 0.4789 0.4764 0.4803 0.4803 0.4781

15 586913 6675154 500 ORM 0.6 8 25 48 4.48 0.48 0.59 2.35 0.24 0.24 0.497 0.501 0.488 0.4756 0.4755 0.4769 0.4776 0.4757 0.4757 0.4757

16 584623 6677522 556 ORM 2.6 7 17 84 2.71 0.38 0.49 1.42 0.27 0.21 0.492 0.505 0.504 0.4743 0.4778 0.4760 0.4764 0.4764 0.4759

17 589418 6680992 500 ORM 6.1 19 7 45 2.75 0.34 0.4 1 0.5 0.11 0.03 0.487 0.512 0.497 0.4840 0.4764 0.4798 0.4785 0.4760 0.4803 0.4803 0.4775

18 588861 6672243 522 ORM 1.8 12 9 126 3.47 0.59 0.61 0.79 1.41 0.17 0.36 0.510 0.502 0.502 0.4746 0.4757 0.4773 0.4780 0.4742 0.4773 0.4773 0.4748

19 591885 6668839 504 ORM 3.7 12 28 104 5.22 0.53 0.62 1.2 1.48 0.18 0.32 0.487 0.500 0.494 0.4749 0.4771 0.4782 0.4782 0.4760 0.4771 0.4771 0.4773

21 592250 6664455 400 ORM 1.4 6 11 88 3.88 0.73 0.64 0.77 2.11 0.21 0.22 0.492 0.489 0.501 0.4734 0.4748 0.4766 0.4760 0.4751 0.4733 0.4733 0.4743

22 593299 6660953 340 ORM 2.7 6 11 72 4.95 0.78 0.66 1.7 1.85 0.19 1.03 0.491 0.488 0.498 0.4740 0.4757 0.4764 0.4771 0.4733 0.4755 0.4755 0.4765

23 593328 6657946 420 ORM 9.1 18 12 243 3.98 0.59 0.82 2.81 2.58 0.27 0.32 0.493 0.503 0.484 0.4740 0.4748 0.4764 0.4769 0.4733 0.4742 0.4742 0.475

24 595140 6656129 290 ORM 4.9 9 7 198 5.95 0.49 0.76 5.75 4.29 0.15 0.3 0.483 0.492 0.487 0.4744 0.4755 0.4785 0.4782 0.4724 0.4762 0.4762 0.4768

25 598010 6652619 205 ORM 7.1 9 19 115 6.45 0.82 1.17 3.3 4.31 0.16 2.73 0.485 0.491 0.481 0.4731 0.4742 0.4760 0.4753 0.4735 0.4748 0.4748 0.4752

26 597394 6653685 307 ORM 14 8 173 4.62 0.71 1.46 3.88 6.88 0.13 0.77 0.493 0.492 0.4744 0.4746 0.4773 0.4760 0.4715 0.4744 0.4744 0.4751

27 592592 6645600 160 CS 9.7 95 141 2996 8.81 0.96 7.2 2.23 52.21 0.22 6.43 0.504 0.486 0.498 0.4843 0.4764 0.4815 0.4857 0.4737 0.4866 0.4866 0.486

28 593200 6642327 30 CS 1.8 9 16 89 3.67 1.1 0.8 2.9 2.59 0.11 0.22 0.489 0.492 0.488 0.4734 0.4757 0.4762 0.4760 0.4728 0.4746 0.4746 0.4745

29 597751 6649203 235 CS 10 15 429 6.21 0.65 1.24 2.11 7.15 0.19 1.29 0.493 0.482 0.4719 0.4760 0.4757 0.4760 0.4728 0.4744 0.4744 0.4734

31 597503 6650780 187 ORM 3.4 12 9 180 4.22 0.75 0.81 1.32 5.1 0.17 0.78 0.493 0.498 0.490 0.4748 0.4746 0.4762 0.4760 0.4771 0.4757 0.4757 0.4751

32 602548 6646851 230 CS 1.5 36 13 261 5.86 0.65 1.32 8.61 3.98 0.15 2.2 0.638 0.489 0.490 0.4768 0.4771 0.4780 0.4785 0.4726 0.4822 0.4822 0.4848

33 600209 6640474 195 GNS 5.9 11 19 128 3.95 0.87 1.17 8.25 5.52 0.13 0.76 0.500 0.500 0.488 0.4739 0.4755 0.4766 0.4769 0.4724 0.4760 0.4760 0.4751

34 602583 6637390 110 GNS 2.2 11 16 112 7.68 1.3 0.71 4.98 0.93 0.28 0.32 0.545 0.497 0.497 0.4734 0.4762 0.4771 0.4785 0.4717 0.4833 0.4833 0.4797

35 602264 6633965 180 GNS 7.7 16 16 100 3.55 0.9 0.67 1.95 1.35 0.15 0.59 0.470 0.503 0.497 0.4731 0.4778 0.4815 0.4796 0.4760 0.4757 0.4757 0.4758

36 605115 6630922 176 GNS 2.8 8 10 81 3.45 0.55 0.63 1.03 3.11 0.14 0.26 0.497 0.497 0.497 0.4743 0.4757 0.4771 0.4769 0.4753 0.4773 0.4773 0.476

37 605674 6628925 194 GNS 3.3 6 9 92 3.69 0.71 0.77 0.93 2.46 0.14 0.24 0.440 0.502 0.501 0.4739 0.4753 0.4773 0.4769 0.4744 0.4760 0.4760 0.4767

38 608245 6625964 140 GNS 13 10 55 2.37 0.76 0.42 0.57 1.27 0.11 0.4 0.504 0.496 0.4754 0.4753 0.4771 0.4771 0.4776 0.4762 0.4762 0.4769

39 605175 6614207 120 GNS 2.1 13 17 80 3.32 0.64 0.53 1.83 1.71 0.15 0.42 0.604 0.507 0.489 0.4775 0.4776 0.4789 0.4780 0.4757 0.4764 0.4764 0.4755

41 608279 6623043 175 GNS 1.8 6 16 79 2.73 0.31 0.5 0.84 0.04 0.04 0.550 0.507 0.490 0.4754 0.4755 0.4782 0.4773 0.4742 0.475

42 609123 6618431 180 GNS 12.1 15 22 403 3.66 0.67 0.56 0.84 7.42 0.13 1.51 0.472 0.516 0.502 0.4751 0.4789 0.4789 0.4794 0.4778 0.4805 0.4805 0.4777

43 612533 6609356 150 GNS 2.6 10 7 101 3.23 0.79 0.52 1.35 2.43 0.08 0.6 0.551 0.489 0.493 0.4741 0.4766 0.4769 0.4792 0.4730 0.4764 0.4764 0.4773

44 607746 6603365 118 GNS 3.8 6 8 113 3.68 1.06 0.9 1.18 2.32 0.18 0.23 0.441 0.512 0.493 0.4736 0.4776 0.4762 0.4771 0.4728 0.4760 0.4760 0.4749

Minimum 0.6 4 6 19 1.49 0.27 0.25 0.21 0.16 0.02 0.03 0.440 0.486 0.481 0.4719 0.4742 0.4757 0.4753 0.4715 0.4733 0.4733

Median 4 12 14 88 3.46 0.59 0.59 0.90 1.48 0.15 0.28 0.492 0.501 0.495 0.4749 0.4760 0.4784 0.4781 0.4747 0.4771 0.4771

Maximum 21 95 141 2996 8.81 1.30 7.20 8.61 52.21 0.28 6.43 0.638 0.529 0.522 0.4989 0.4789 0.4843 0.4857 0.4782 0.4988 0.4988

(continued on next page)

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208 Pb/207Pb 206Pb/207Pb

Rock Chor Bhor Ohor Moss MASH BIL BBA BWO SNE SWO Rock Chor Bhor Ohor MASH BIL BBA BWO SNE SWO

01 2.899 2.528 2.516 2.4836 2.430 2.430 2.425 2.433 2.461 2.428 2.4344 1.342 1.2885 1.2763 1.2300 1.175 1.17 1.161 1.208 1.165 1.1721

02 2.753 2.505 2.499 2.4517 2.426 2.423 2.425 2.418 2.449 2.428 2.4351 1.336 1.2495 1.2177 1.1906 1.16 1.161 1.145 1.179 1.161 1.1663

03 2.703 2.516 2.500 2.4329 2.433 2.430 2.427 2.417 2.449 2.424 2.4387 1.317 1.2681 1.2416 1.1533 1.173 1.159 1.14 1.176 1.159 1.1664

04 2.401 2.514 2.521 2.4229 2.432 2.423 2.428 2.421 2.428 2.424 2.4297 1.097 1.2947 1.2790 1.1465 1.164 1.159 1.144 1.154 1.155 1.1605

05 2.462 2.587 2.545 2.4526 2.419 2.430 2.432 2.427 2.457 2.430 2.4213 1.251 1.2857 1.2495 1.1674 1.165 1.164 1.153 1.185 1.161 1.1509

06 2.471 2.504 2.484 2.4586 2.433 2.430 2.426 2.426 2.454 2.434 2.4422 1.204 1.2363 1.2287 1.1921 1.17 1.165 1.156 1.189 1.17 1.1710

07 2.479 2.465 2.522 2.4539 2.428 2.426 2.425 2.439 2.438 2.424 2.4132 1.225 1.2084 1.2160 1.1839 1.168 1.165 1.162 1.169 1.16 1.1438

08 2.473 2.472 2.472 2.4563 2.434 2.430 2.430 2.423 2.453 2.435 2.4407 1.204 1.2647 1.2720 1.2109 1.174 1.166 1.15 1.223 1.161 1.1955

09 2.482 2.478 2.487 2.4601 2.433 2.430 2.434 2.430 2.449 2.442 2.4349 1.228 1.3097 1.2983 1.2279 1.177 1.171 1.156 1.202 1.17 1.1793

11 2.490 2.510 2.484 2.4602 2.430 2.431 2.433 2.429 2.453 2.443 2.4354 1.229 1.2641 1.2229 1.1953 1.168 1.168 1.152 1.185 1.166 1.1665

12 2.495 2.492 2.498 2.4420 2.430 2.422 2.428 2.428 2.441 2.438 2.4431 1.229 1.2564 1.2598 1.1682 1.163 1.163 1.154 1.171 1.165 1.1748

13 2.513 2.504 2.488 2.4625 2.435 2.427 2.425 2.410 2.453 2.440 2.4349 1.220 1.2607 1.2381 1.2063 1.164 1.163 1.141 1.192 1.165 1.1678

14 2.527 2.490 2.486 2.4301 2.432 2.426 2.425 2.432 2.440 2.437 2.4379 1.222 1.2619 1.2746 1.1548 1.161 1.16 1.158 1.172 1.162 1.1657

15 2.622 2.511 2.472 2.4409 2.428 2.429 2.430 2.433 2.434 2.4371 1.304 1.2582 1.2059 1.1611 1.159 1.16 1.157 1.162 1.1593

16 2.617 2.531 2.487 2.4309 2.429 2.435 2.435 2.434 2.4331 1.289 1.2771 1.2522 1.1532 1.16 1.159 1.16 1.161 1.1579

17 2.517 2.488 2.503 2.4524 2.432 2.435 2.427 2.426 2.453 2.438 2.4296 1.226 1.2743 1.2444 1.1874 1.168 1.161 1.152 1.178 1.163 1.1600

18 2.630 2.513 2.505 2.4305 2.420 2.428 2.430 2.421 2.436 2.436 2.4337 1.341 1.2622 1.2564 1.1539 1.159 1.159 1.148 1.162 1.161 1.1556

19 2.564 2.496 2.474 2.4359 2.421 2.428 2.429 2.424 2.437 2.430 2.4367 1.248 1.2484 1.2221 1.1572 1.161 1.161 1.153 1.163 1.16 1.1630

21 2.533 2.511 2.511 2.4259 2.431 2.430 2.423 2.437 2.426 2.438 2.4265 1.246 1.2290 1.2580 1.1491 1.158 1.154 1.158 1.148 1.163 1.1509

22 2.588 2.522 2.495 2.4289 2.433 2.429 2.427 2.411 2.436 2.435 2.4420 1.271 1.2319 1.2435 1.1521 1.157 1.156 1.138 1.158 1.159 1.1637

23 2.514 2.498 2.482 2.4293 2.429 2.423 2.424 2.413 2.430 2.431 2.4363 1.241 1.2570 1.2014 1.1515 1.154 1.157 1.141 1.152 1.16 1.1572

24 2.493 2.502 2.493 2.4363 2.427 2.433 2.430 2.414 2.438 2.437 2.4397 1.203 1.2296 1.2150 1.1558 1.164 1.161 1.138 1.161 1.164 1.1634

25 2.545 2.502 2.466 2.4258 2.431 2.426 2.428 2.416 2.436 2.434 2.4283 1.234 1.2275 1.1871 1.1477 1.155 1.154 1.143 1.156 1.16 1.1540

26 2.497 2.504 2.4250 2.430 2.430 2.431 2.417 2.431 2.433 2.4375 1.2313 1.2331 1.1508 1.16 1.158 1.138 1.153 1.161 1.1581

27 2.486 2.459 2.499 2.4509 2.424 2.440 2.451 2.414 2.452 2.442 2.4483 1.254 1.1954 1.2435 1.1871 1.174 1.188 1.141 1.193 1.176 1.1900

28 2.507 2.486 2.482 2.4090 2.433 2.423 2.425 2.415 2.426 2.445 2.4269 1.227 1.2222 1.2120 1.1406 1.154 1.156 1.143 1.151 1.165 1.1515

29 2.505 2.450 2.4178 2.425 2.426 2.425 2.413 2.417 2.438 2.4296 1.2362 1.1812 1.1416 1.154 1.153 1.138 1.146 1.158 1.1502

31 2.575 2.510 2.481 2.4286 2.432 2.428 2.429 2.426 2.425 2.432 2.4324 1.268 1.2511 1.2147 1.1530 1.156 1.156 1.155 1.153 1.154 1.1557

32 3.686 2.470 2.494 2.4324 2.429 2.431 2.434 2.414 2.442 2.445 2.4549 2.353 1.2090 1.2210 1.1598 1.162 1.167 1.14 1.177 1.17 1.1902

33 2.787 2.518 2.476 2.4235 2.434 2.430 2.424 2.395 2.430 2.434 2.4293 1.392 1.2599 1.2092 1.1485 1.158 1.156 1.13 1.156 1.159 1.1541

34 2.639 2.494 2.495 2.4101 2.434 2.431 2.439 2.394 2.432 2.437 2.4310 1.439 1.2393 1.2397 1.1411 1.159 1.168 1.127 1.175 1.161 1.1661

35 3.305 2.502 2.497 2.4280 2.433 2.439 2.437 2.422 2.441 2.444 2.4405 1.555 1.2580 1.2411 1.1487 1.174 1.169 1.151 1.161 1.167 1.1610

36 2.554 2.528 2.529 2.4332 2.431 2.436 2.434 2.423 2.445 2.440 2.4494 1.270 1.2565 1.2577 1.1542 1.162 1.162 1.149 1.167 1.162 1.1659

37 3.657 2.544 2.528 2.4307 2.431 2.428 2.435 2.415 2.439 2.436 2.4403 1.609 1.2760 1.2652 1.1521 1.159 1.161 1.148 1.161 1.16 1.1633

38 2.518 2.505 2.4371 2.436 2.432 2.432 2.427 2.433 2.438 2.4454 1.2694 1.2436 1.1588 1.16 1.161 1.156 1.158 1.162 1.1663

39 4.363 2.544 2.526 2.4463 2.430 2.438 2.429 2.424 2.436 2.435 2.4441 2.636 1.2890 1.2350 1.1680 1.167 1.161 1.151 1.16 1.161 1.1623

41 3.811 2.527 2.479 2.4387 2.429 2.427 2.430 2.424 2.438 2.4402 2.094 1.2805 1.2161 1.1594 1.161 1.161 1.149 1.163 1.1590

42 2.382 2.508 2.476 2.4249 2.427 2.429 2.426 2.433 2.434 2.437 2.4349 1.126 1.2946 1.2426 1.1522 1.163 1.163 1.162 1.169 1.166 1.1632

43 3.373 2.505 2.549 2.4303 2.424 2.430 2.421 2.416 2.438 2.437 2.4463 1.857 1.2250 1.2575 1.1522 1.159 1.162 1.142 1.161 1.159 1.1676

44 2.789 2.583 2.508 2.4316 2.426 2.427 2.427 2.420 2.436 2.436 2.4388 1.229 1.3233 1.2363 1.1519 1.156 1.161 1.146 1.159 1.163 1.1583

2.382 2.459 2.450 2.4090 2.419 2.422 2.421 2.394 2.417 2.424 2.4132 1.097 1.195 1.181 1.141 1.154 1.153 1.127 1.146 1.154 1.144

2.554 2.505 2.495 2.4327 2.430 2.430 2.429 2.423 2.438 2.436 2.4365 1.251 1.258 1.240 1.154 1.162 1.161 1.149 1.162 1.162 1.163

4.363 2.587 2.549 2.4836 2.436 2.440 2.451 2.439 2.461 2.445 2.4549 2.636 1.323 1.298 1.230 1.177 1.188 1.162 1.223 1.176 1.196

or the location of the sample sites see Fig. 1. Coordinates are UTM-coordinates. ALT: altitude in m above sea level, FLITHO: lithology observed at sample site in the field, GN ambrian gneisses in the Randsfjord area at the northern end of the

ansect, CS: Cambro Silurian sediments, ORM: magmatic rocks of the Oslo Rift (predominantly syenites), GNS: Precambrian gneisses in the Oslo area and to the south of Os -, O-hor: C-, B-, and O-horizon of soil profiles, moss (Hylocomium

lendens), MASH = European mountain ash leaves, BIL: mountain birch leaves, BBA: mountain birch bark, BWO: mountain ash wood, SNE: spruce needles, SWO: spruc

able 1 (continued)

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When using an ICP-SFMS for Pb-isotope analy-ses, it is theoretically possible to also measure thelow abundance isotope 204Pb. However, when deal-ing with natural samples mathematical correctionsmust be used to account for contributions fromHg on the signal at 204Pb. Furthermore the methodgets more complicated because two detection modesneed to be used or the samples have to be diluted toa concentration appropriate for counting mode.Both effects cause poor precision. For this reason204Pb is almost never reported when Pb-isotoperatios are measured with ICP-SFMS.

To control the day-to-day variation in digestionand instrumental performance the reference mate-rial MESS-3 (NRC, National Research CouncilCanada) was used, and evaluated in the same wayas the samples. A standard deviation of 0.0027was obtained for the isotope ratio 208Pb/207Pb and0.0009 for 207Pb/206Pb after 10 independent diges-tions, six days of analysis and 105 analyses (Table1). From these data, the reproducibility of the Pb-isotope ratios was estimated to be approximately0.11% for all ratios. Replication of the entire proce-dure, as was done with MESS-3, accounts for mostof the inherent uncertainty components. Repeatedanalyses of the reference material can, of course,not account for uncertainty contributions fromsample heterogeneity. The inhomogeneous natureof the organic samples can, however, be overcomeby using dry ashing and a large sample size.Although Mess-3 is not officially certified for Pb-isotope ratios this standard has been frequently usedfor isotope determinations during the last couple ofyears and ample data on the Pb-isotope composi-tion of this standard exists. Table 1 compares thepresent results with those of two Australian groups.While the quality of isotope ratio measurements byICP-SFMS has previously been questioned, severalauthors have demonstrated during the last few yearsthat these instruments are able to deliver results thatagree well with TIMS measurements (e.g.,Gwiazdaet al., 1998; Townsend and Snape, 2002; Krachleret al., 2004).

3. Results

Clearly the highest Pb-concentrations areobserved in the O-horizon (Fig. 2, Table 2). Majordifferences between the sample materials becomeapparent even at a cursory glance. O-horizon, birchbark, wood and spruce wood show a larger varia-tion in Pb-concentrations than the mineral soils.

The isotope ratios show a distinct shift betweenthe ‘‘geogenic” (rocks, C- and B-horizon) and the‘‘biogenic” (O-horizon and plant materials) samplematerials. The rock samples display the largest var-iation, covering all observed isotope ratios. Varia-tion decreases in general substantially from therocks to the mineral soils and again to all organicsample materials.

Pb-concentrations in nine of the sample materialsas observed along the transect are compared inFig. 3. The main changes in lithologies along thetransect and the location of Oslo are indicated inthe Figure. Samples sites 134 (E6) and 127 (Pb min-eralisation) are identified in all transects.

Variations in the 206Pb/207Pb ratio in the samenine sample materials shown in Fig. 3 are plottedin Fig. 4 along the transect. The main changes inrock types and the location of Oslo and the Rands-fjordarea and sites 134 and 127 are again indicated.

Fig. 5 shows a plot of Pb concentration versusthe 206Pb/207Pb ratio for six selected samplematerials.

The variation in the 206Pb/207Pb ratios versus the208Pb/207Pb ratios in a selection of the sample mate-rials (not all plant materials shown) is compared inFig. 6. The ‘‘world Pb ores” regression line shown inthe diagram connects the Pb-isotope data of morethan 150 lead deposits from around the globe (datafrom Sangster et al., 2000). The isotopic signaturesof the Pb-deposits cover a wide range of isotoperatios, two of the largest recently mined Pb-depositsin the world (Broken Hill and Mississippi Valley-type) appear on opposite ends of the diagram. Alimited number of analyses of European leaded gas-olines (from Novak et al., 2003) all plot towards theBroken Hill signature, suggesting that Broken HillPb was predominantly used in the production ofEuropean leaded gasoline.

4. Discussion

Fig. 2a indicates that Pb is strongly enriched inorganic soils (O-horizon) compared to the valuesobserved in rocks and mineral soils (B- and C-hori-zon). The plant materials show varying and differentspecies-specific Pb-concentrations that are wellbelow the values found in the rocks and soils(Fig. 2a). Reimann et al. (2007b) demonstrated thatthe strong Pb-enrichment in the O-horizon is pri-marily driven by the kinetics of formation and decayof organic matter, as originally explained in Golds-chmidt (1937, the plant pump). Thus, the commonly

Fig. 3. Local variation in Pb-concentrations in nine sample materials along the south–north transect through Oslo. The location of Osloand the Randsfjord area is indicated at the top of the diagram. The dashed lines mark major lithological breaks: GNS: Precambriangneisses to the south of Oslo, CS: Cambro-Silurian sediments, ORM: Oslo Rift magmatic rocks (here predominantly syenites) and GNN:Precambrian gneisses at the northernmost end of the transect. Site 127: lead mineralisation in Oslo, site 134: 10–20 m from highway E6.The smoothed lines shown are calculated using Tukey’s running median (Tukey, 1977).


observed high enrichment of elements like Pb in theO-horizon of forest soils is independent of anyapparent source and predominantly not of anthro-pogenic origin. The difference to the well establishedcycles of major nutrients like N and P is that forthese elements the uptake rate is very high whencompared to the pool, while for metals like Pb theuptake rate is very low when compared to the totalpool. The recycling via litterfall is, however, thesame: this leads to the observed enrichment. Thenatural enrichment of Pb and several other ele-ments, often associated with anthropogenic emis-sions, in organic soils, has also been described ona much larger scale from the Kola Peninsula (Rei-mann et al., 2001), and, though less dramatically,for agricultural soils on the sub-continental scalefrom all of Northern Europe (Reimann et al.,2003). The high Pb-concentrations in birch andspruce wood compared to birch leaves and spruce

needles are a clear indication of the importance ofplant uptake (Fig. 2a).

Lead isotopes show systematic shifts between thesample materials (Fig. 2b–d). Bedrock samplesshow the largest variation. Soil formation leads toa decreasing variation; most distinct for the208Pb/207Pb ratio (Fig. 2c). Stern et al. (1966) inves-tigated the effects of chemical weathering on Pb-iso-tope ratios and found that weathered zircons appearto have lost up to 85% of their radiogenic Pb. Erelet al. (1994) studied the Pb-isotope systematics ofweathering and found that the isotopic compositionof Pb changed systematically with the degree ofweathering towards lower radiogenic signals (lower206Pb/207Pb ratios). In the surface environment,with abundant organic matter, a further U–Th–Pbfractionation in the fine fraction of sediments (soils)can also be related to their organic C content (Gau-thier-Lafaye et al., 1996). A systematic change in the

Fig. 4. Local variation in 206Pb/207Pb-isotope ratios in nine sample materials along the south–north transect through Oslo. The location ofOslo and the Randsfjord area is indicated at the top of the diagram. The dashed lines mark major lithological breaks: GNS: Precambriangneisses to the south of Oslo, CS: Cambro–Silurian sediments, ORM: Oslo Rift magmatic rocks (here predominantly syenites) and GNN:Precambrian gneisses at the northernmost end of the transect. Site 127: lead mineralisation in Oslo, site 134: 10–20 m from highway E6.The smoothed lines shown are calculated using Tukey’s running median (Tukey, 1977).

Fig. 5. Pb-concentrations versus 206Pb/207Pb-isotope ratios for six selected sample materials. All other plant materials (moss, spruce,mountain ash) plot into the same field as birch leaves and wood. Site 127: lead mineralisation in Oslo, site 134: 10–20 m from highway E6.


Fig. 6. 206Pb/207Pb versus 208Pb/207Pb diagram. The location of Broken Hill, the Upper Mississippi valley type deposits and the ‘‘world Pbores line” are taken from data published by Sangster et al. (2000), the central European gasoline field is taken from Novak et al. (2003), the‘‘GEOS samples line” is a best fit regression line for the sample materials collected along the transect. Values for the rock samples cover astill considerably larger field towards higher values than shown here (see Table 1).


Pb-isotope systematics from rocks to soils is thus aneffect that should be expected and must be consid-ered when using Pb-isotopes for sourceapportionment.

A pronounced shift can be observed betweenminerogenic and organic sample materials. All plantsamples and the O-horizon show even lower Pb-iso-tope ratios and a much lower variation than theminerogenic materials collected at the same sites.The low ratios are independent of the observed con-centrations (Fig. 2). Here O-horizon and birchwood show the highest variation in isotope ratios,birch bark the lowest isotope ratios.

Assuming that Norway’s largest city is a sourceof anthropogenic Pb e.g., from the previous use ofleaded gasoline, transects should show a positivePb-concentration peak (Fig. 3) and a negative206Pb/207Pb-isotope ratio gradient (Fig. 4) whenapproaching the city. Terrestrial moss (H. splen-

dens) provided generally the best impression of theimpact of the city on element concentrationsobserved along the transect (Reimann et al., 2006).The elements Ag, Al, Au, Bi, Cd, Co, Cr, Cu, Fe,Mo, Ni, Pb, Pt, Sb, Th, Ti and Zn all show a peakin moss samples collected in Oslo and its surround-ings (see Fig. 3a for Pb).

Fig. 3 indicates that several but not all of thesample materials show a clear impact of the locationof Oslo and highway site 134 on the measured Pbconcentration. There is a general decline of Pb con-

centrations throughout Nordmarka, underlain bythe Oslo Rift magmatic rocks.

The O-horizon samples are characterised by ahigh local variation in element concentrationsobserved along the transect, a clear argumentagainst a predominantly anthropogenic source ofalmost all the Pb via long range atmospheric trans-port. By far the highest Pb-concentration isobserved at site 127 in Oslo above mineralisation.Site 134 (E6) is almost invisible, although it is pos-sible to detect a slight trend towards increasingPb-concentrations above the gneisses to the southof Oslo when approaching the city from the south(Fig. 3d). Site 134 shows, however, the expectedlow 206Pb/207Pb-isotope ratio (Fig. 4d) indicativeof gasoline Pb.

The birch samples demonstrate the importance ofPb uptake and detoxification along the xylemupstream, site 127 shows the highest concentrationsin wood and leaves but rather low concentrations inbark (Fig. 3b, e, h). Birch, shedding its leaves eachyear, clearly uses this opportunity for detoxification(Reimann et al., 2007c), well reflected in low Pb-concentrations and variation in bark (Fig. 3e). Asa consequence, the ‘‘Oslo anomaly” is well visiblein birch bark. Birch bark is the only sample materialwhere both the expected Pb concentration peak andthe Pb-isotope ratio dip are clearly displayed(Figs. 3e, 4e) and mark the anthropogenic impactof Oslo.


Spruce (Fig. 3f) prevents uptake of Pb into theneedles more efficiently than birch (Fig. 2a) intoits leaves. Lead concentrations in the needles donot reflect the location of Oslo. Only site 134 ismarked by a single high value (Fig. 3f). Several highvalues are found in the spruce wood, with the high-est value at site 127, indicating that the uptake pre-vention maybe breaking down at a site with veryhigh Pb-concentrations in the soils. When compar-ing the results of the different plant species, includ-ing mountain ash, it is visible that each plantfollows its own strategy with regards to the uptakeof Pb. There appear considerable differences in Pb-concentrations in the different plants collected atthe same site. In both, spruce needles and mountainash leaves, site 134 returns the highest Pb values.Both species are clearly protected against excessivePb uptake from the underlying soils (see site 127)and can thus provide a better indication of contam-ination than birch, using its leaves for detoxifica-tion. Concentrations reported in spruce woodcompared to birch wood show clearly that spruceuses uptake prevention mechanisms that birch doesnot possess. In consequence the composition of theplant community present at any one sample site willhave important influence on the observed Pb-con-centrations in surface soils.

When studying Fig. 4 in detail, several samplematerials show a cluster of samples with unusuallylow isotope ratios directly to the north of Oslo, onentering the Oslo Rift magmatic rocks (e.g., moss,Fig. 4a; birch leaves, Fig. 4b; birch bark, Fig. 4e).The main wind direction in Oslo is from south tonorth, thus this pattern could be interpreted as theexpected anthropogenic signal. However, the C-horizon samples show a similar pattern (Fig. 4g)with low values on entering the Oslo Rift magmaticrocks and higher values within the same bedrocktype towards the north. It is thus also possible thatthe plants just reflect this natural pattern.

When plotting Pb-concentrations against the206Pb/207Pb-isotope ratio (Fig. 5) for a selection ofsample materials (the other biogenic materialswould just overplot the birch samples), minerogenicand biogenic sample materials plot into completelyseparated fields. At site 127 the Pb-isotope ratio isalmost constant in all sample materials, while theratios change widely at site 134. It should also benoted that 2 bedrock samples display the lowest iso-tope ratios. Total variation in the isotopic ratios ofthe bedrock samples is not even fully shown in thisdiagram. The diagram provides strong evidence that

completely different processes determine Pb concen-trations and isotope ratios in the geosphere and inthe biosphere.

Fig. 6 shows the variation of a selection of thesample materials in a 206Pb/207Pb versus 208Pb/207Pbdiagram. Again, all other plant materials plot intothe same range as indicated by the birch samplesshown here. Based on the data published in Sangsteret al. (2000) the regression line for world Pb depositswas added. The location of the Broken Hill and theMississippi Valley deposits within this diagram isalso indicated. They plot at the extreme oppositeends of the diagram, while the majority of Pb depos-its cluster in the same area as the majority of thepresent samples. The 206Pb/207Pb-isotope ratios ofmost Pb mines around the world fall into a rangeof 1.15–1.22 in this diagram. The regression line cal-culated for all transect samples falls very close to theworld Pb deposits regression line. This does notindicate that all samples are contaminated with Pbfrom mining and smelting (not very likely for therock samples). It rather demonstrates the large nat-ural background variation in Pb-isotope ratios.Double ratio diagrams lead to forced correlationsand require great care and understanding wheninterpreting the observed patterns. In Fig. 6 207Pbinfluences both axes, the samples are not free tovary.

Again two different fields emerge in Fig. 6: min-eral soils and organic sample materials. The organicsample materials plot into the direction of the Bro-ken Hill deposit. In the environmental literature thisis usually taken as proof of severe contamination ofthe surface environment on the continental scale.What in fact is visible in the diagram is a typical‘‘organic sample material background variationfield”. It is also noteworthy that the variation inthe isotopic results obtained from the rock samplescollected along the transect covers the whole rangeof the observed variation in all other samples (seeTable 2 and Fig. 2b–d). Note the presence of tworock samples as the lowermost samples plotted inthe diagram. In the absence of an isotopicallyclearly defined Pb-source this diagram thus cannotbe used to suggest any anthropogenic impact. Thecentral European gasoline field indicated in Fig. 6is based on very limited data published in Novaket al. (2003). Birch bark has the longest exposuretime of the collected plant materials to atmosphericcontamination and the slight shift of birch barkaway from the other plant materials is thus proba-bly the expected anthropogenic signal. This


provides a clear impression of the scale and impactof anthropogenic sources versus natural processesand variation.

It thus appears that biogenic sample materialsmay be generally characterised by their own isotoperatios (206Pb/207Pb: 1.14–1.17, 208Pb/207Pb: 2.41–2.45, 206Pb/208Pb: 0.474–0.482). This interpretationis backed by determinations of Pb-isotope ratiosin tree rings dating back to 1880–1920. Severalauthors report 206Pb/207Pb ratios of 1.17 in treerings of different species (spruce and sycamore)from different parts of the world but within compa-rable climate zones (Canada, Great Britain, Swe-den; Watmough and Hutchinson, 2002; Bindleret al., 2004; Savard et al., 2006). These low ratioscan neither be explained by Pb-isotope ratios inthe underlying mineral soils nor by high proportionsof anthropogenic Pb with sufficiently low Pb-iso-tope ratios in the atmosphere. While some Cana-dian smelters may emit Pb with such low ratios,European Pb ores usually show much higher isoto-pic ratios (Sangster et al., 2000) and leaded petrolwas first introduced in 1923 (Faure, 1986). Further-more, Ault et al. (1970), in their classical highwaycontamination study, analysed not only topsoilbut also Pb-isotopes in tree rings. As alreadypointed out by Gast (1970) and Holtzmann(1970), Ault et al. (1970) fail to explain the observedunusually low Pb-isotope signature in the tree rings.Holtzmann (1970) points out that the Pb in thewood appears to originate from sources outsidethe range of mean isotopic compositions of the soiland air and that ‘‘possibly the tree is capable ofacquiring Pb only from particular minerals orclays”.

The ‘‘mineralogical fractionation” suggested byHoltzmann (1970) is but one possible explanationof the observation. Haack et al. (2003) defined acorrelation line for the ‘‘European Standard Pollu-tion ESP” in the (208Pb/206Pb)/(207Pb/206Pb) dia-gram. The ESP was established based on theobservation that the topsoils from 7 soil profiles col-lected in Northern Germany defined an excellentcorrelation line. Lead from Norwegian bogs, Scot-tish plants, pelagic sediments and aerosols fromthe Northern Atlantic also plot on this line. Sootfrom the exhausts of Swiss cars, dust from a roadtunnel in Zurich and part of the sewage sludges inZurich all plot on this line (Hansmann and Koppel,2000). Moss and O-horizon samples collected on theKola Peninsula, Russia, again plot on this line(Haack et al., 2004). The authors conclude that this

must be the expression of a continent-wide mixingsystem of two dominant apparent end componentsand each of these, in turn must be the result of mix-ing and homogenisation of numerous sources(Haack et al., 2002). They postulate that the twosources are geogenic Pb from rocks and soils andthat the other end member is anthropogenic Pbfrom many different sources. Such a continental-scale atmospheric mixing model could explain theobserved homogeneous Pb-isotope signature in allbiogenic sample materials. However, the206Pb/207Pb ratios observed in the plant materialsare too low to be explained by a continental-scalemixing model of anthropogenic Pb from countlessanthropogenic sources. All the Pb in European soilsand vegetation would have to originate from butone source: Broken Hill. In addition, the differentspecies can show quite different Pb-isotope ratiosat one and the same sample site. The usuallyobserved exponential decrease in Pb-concentrationswith distance from a defined contamination sourceprovides a further argument against the ‘‘continen-tal-scale mixing” hypothesis. It is thus more likelythat the two end members defining the ESP are geo-genic and biogenic Pb, the latter entering the atmo-sphere via wind erosion of organic soils, pollen, orforest fires. The ESP would then rather represent aEuropean baseline isotope signal (EBIS) againstwhich the impact of anthropogenic sources wouldhave to be measured in the form of deviations fromthis line.

Lead is a very heavy element and mass-depen-dent fractionation between the Pb-isotopes is gener-ally considered insignificant to non-existent, giventhe small mass differences. The whole use of Pb-iso-topes in environmental studies is based on theassumption that no secondary isotopic fractionationof Pb can occur in the environment. However,Schauble (2007) has recently investigated isotopicfractionation of the very heavy elements Hg andTh in the context of mass independent nuclear fieldshift effects. Stirling et al. (2007) have demonstratedisotopic fractionation for the heaviest naturallyoccurring element U during the biologically remedi-ated reduction of U(VI) to U(IV). Weyer et al.(2007) also present data indicating U ‘‘stable” iso-tope fractionation in nature. Rademacher et al.(2006) present measurements of mass-dependent Uisotope fractionation induced by U(VI) reductionby Fe0 and bacteria. Actually a whole lot of isotopesystems, from rather light to heavy is presentlybeing studied in the context of mass-dependent


and mass-independent isotopic fractionation mostlydue to biological processes (e.g., Hg: Bergquist andBlum, 2007; Estrade et al., 2007; Laffond et al.,2007; Fe: Guelke and von Blankenburg, 2007;Guelke et al., 2007; Kiczka et al., 2007; Cu: Kimballet al., 2007; Ca: Heuser et al., 2007; Zn: Jouvinet al., 2007). There is thus absolutely no reasonwhy Pb should not also show a biologically medi-ated isotope fractionation at the earth surface. Itclearly needs consideration of the whole biosphere(and not only human beings) when studying traceelement cycling at the earth’s surface.

Given the surprisingly similar ratios in all theplant materials analysed and the unusually low var-iation in the isotope ratios even for very differentrock types, in addition to the small Oslo signal, itappears most likely that the observed effect is drivenby a minor fractionation of Pb-isotopes duringuptake into and each passage through the bio-sphere. It must be noted that even an extremelysmall effect will go through a biomagnification pro-cess, determined by the formation and decay kinet-ics of the organic soil horizon. Over time this leadsto an individual and characteristic signal showingthe observed low variation (Fig. 2b–d) once a steadystate is reached. If a steady state is not reached, ahigher variation of measured Pb-isotopes has to beexpected, depending on local site conditions (e.g.,in the Randsfjord area in Fig. 4, due to an unusuallyhigh pH, for the region, and thus a faster decompo-sition of the organic layer; Reimann et al., 2007b).Collection of Pb-isotope data at the continentalscale is urgently needed to document and under-stand these features.

Steinmann et al. (2007) have recently demon-strated that such a process influences REE concen-trations and Nd-isotope compositions in organicsurface soils and the receiving waters in the Streng-bach catchment, Vosges mountains. Prunier et al.(2007) demonstrated U series disequilibria in soilsystems of the same catchment. These authors con-clude that their data point to the important role ofthe vegetation in controlling the geochemical/isoto-pic signatures of the soil’s surface horizons and soilsolutions by litter recycling and root uptake. Fromthe above observations, a successive change of iso-tope ratios in a soil profile from surface (biosphere)to depth (geosphere) would have to be expected forpurely natural reasons and without any input of Pbfrom anthropogenic sources. The ‘‘20th century air-borne pollution signal” as defined by Bindler et al.(1999) (206Pb/207Pb ratio of c. 1.15) is the natural

background signal for organic material under pres-ent-day climatic conditions at the earth surface andis not related to anthropogenic sources.

5. Conclusions

The influence of the city of Oslo on the observedPb-isotope ratios in the 11 sample materials is, atthe scale of the transect, almost negligible. Only sin-gle sample sites show a shift in the isotopic ratios insome sample materials when, for example,approaching a major highway. In this study birchbark is clearly the best indicator of anthropogenicsources. The scale of contamination is clearly mea-sured in metres to some hundreds of metres alongthis transect and not in many kilometres. Naturalbackground variation is high in the geogenic samplematerials. The variation observed for the rock sam-ples covers the whole variation measured in all othersample materials. Weathering and soil-forming pro-cesses lead to a decreased variability in the minero-genic soil horizons. The biogenic sample materials(plants and the plant-derived O-horizon of the soilprofiles) show an isotopic signal, characterised bylow variability that is clearly removed from the sig-nal displayed by minerogenic sample materials.

All biogenic sample materials show almost thesame isotopic ratios all along the profile. Ratios of206Pb/207Pb: 1.14–1.17, 208Pb/207Pb: 2.41–2.45,206Pb/208Pb: 0.474–0.482 can probably be used fordefining a background field for the natural variationof Pb-isotopes in biological sample materials in theNorthern Hemisphere. It is this background fieldagainst which contamination at the Earth’s surfaceand in the atmosphere needs to be assessed.

An isotope ratio measured in the C-horizon of asoil profile cannot be used as the ‘‘geogenic back-ground” for an isotope ratio measured somewhereelse in the soil profile, especially not for the plant-derived O-horizon, even if they are collected atexactly the same site. Depth-related shifts in isotoperatios in soil profiles (and other sediment profiles)need to be interpreted in relation to the depth distri-bution of organic material – a systematic shift fromlower biogenic isotope ratios to higher minerogenicisotope ratios is the expected natural signal and haslittle to do with anthropogenic sources.

Using Pb-isotopes to judge human impact or toassess the amount of anthropogenic Pb in a soilsample is only valid if carried out in relation to aclearly defined source or if time trends are studied.When studying time trends, effects caused by


climate change must be taken into consideration.Changing proportions of minerogenic and biogenicdust in aerosol samples can explain many of theobserved variations in the Pb isotope signal. Cli-mate change and land-use changes like de-foresta-tion or local differences in land-use practice will,at the large scale, all have more importance forobserved shifts in Pb-isotope ratios than contamina-tion from traffic or industry.

Acknowledgements

The authors would like to thank Prof. JorgMatschullat and an anonymous reviewer for thor-ough reviews and the many helpful suggestions toimprove the clarity of the manuscript.

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