TERRESTRIAL POLLUTION IN THE PECHORA BASIN, NORTH-EASTERN EUROPEAN RUSSIA

By Tony Robert Walker, BSc (11014S),MPhil

Thesissubmitted to the University of Nottingham for the degreeof Doctor of Philosophy,February 2003 TABLE OF CONTENTS Page ABSTRACT I

CHAPTER 1. DITRODUCTION 2 I. I. Arctic ecosystems 2 1.2. Industrial activity in the RussianArctic and pollution 3 1.3.The Pechoraregion 6 1.4. Pollution monitoring in remoteregions 9 1.5. Pollution mappingbased on analysesof ecologicalmaterials 10 1.5.1.Snow-pack chemistry 10 1.5.2.Analysis of accumulators 11 1.5.2.1.Lichen chemistry 11 1.5.2.2.Soil chemistry 14 1.5.3.Impacts on communities- lichen biodiversity 17 1.6. The aims of the study 18

CHAPTER 2. MATERIALS AND METHODS 20 2.1. Study areasand samplingregimes 20 2.1.1. TUNDRA programme=dra Degradationin the RussianArctic) 20 2.1.2. SPICEprogramme (Sustainable development of the Pechoraregion In a ChangingEnvironment and society) 25 2.2. Collection of ecologicalmaterials 29 2.2.1. Snow 29 2.2.2. Lichen sampling 31 2.2.3. Soil 32 2.3. Lichen biodiversity determinations 34 2.3.1. Taiga samplingsites 34 2.3.2. Tundra samplingsites 34 2.4. Chemicalanalysis of snow 36 2.4.1. Anion analysisof snow 36 2.4.2. Determinationof pH and excessacidity/alkalinity in snow 36 2.4.3. Gran plot determinationof strong acid concentrationin filtered thawed snow 38 2.4.4. Elementalanalysis of snow 41 2.4.5. Elementalanalysis of suspendedsolids in snow 42 2.5. Chemicalanalysis of lichens 42 2.5.1. Preparationof material 42 2.5.2. Total [Ca], [K], [Mg], [Zn] and [Pb] concentrationsin lichen tissue 43 2.5.3. Total nitrogen concentration([N]lihe,, ) in lichen thalli 43 2.6. Soil analysis 44 2.7. Elementaldeposition rates 45 2.8. Statisticalmethods 46

CHAPTER 3. REGIONAL VARIATION IN THE CHEMICAL COMPOSITION OF WINTER SNOWPACK AND TERRICOLOUS LICHENS IN RELATION TO SOURCESOF ACID EMISSIONS IN THE USA RIVER BASIN, NORTHEASTERN EUROPEAN RUSSIA 47 3.1. Introduction 47 3.2. Materials and methods 48 3.2.1. Study areaand samplingregime 48 3.2.2. Snow and lichen sampling 48 3.2.3. Lichen biomarkersfor nitrogen and acid deposition 49 3.2.4. Chemicalanalysis of snow 50 3.2.5. Chemicalanalysis of lichens 50 3.2.6. Data analysis 51 3.3. Results 51 3.3.1. Snow chemistry 51 3.3.2. Lichen chemistry 63 3.4. Discussion 72 3.4.1. Snow pack chemistry 72 3.4.2. Lichen chemistry 74 3.5. Conclusions 78

CHAPTER 4. ANTHROPOGENIC METAL ENRICHMENT OF SNOW AND SOIL IN NORTH-EASTERN EUROPEAN RUSSIA 81 4.1. Introduction 81 4.2. Materials and methods 82 4.2.1. Study areaand samplingregime 82 4.2.2. Snow sampling 83 4.2.3. Soil sampling 84 4.2.4. Chemicalanalysis of snow 84 4.2.5. Elementalanalysis of suspendedsolids in snow 84 4.2.6. Soil analysis 85 4.2.7. Elementalconcentrations in snow and soil 85 4.3. Resultsand discussion 85 4.3.1. Acidity and alkalinity in filtered snow-melt 85 4.3.2. Elementalanalysis of filtered snow-melt 86 4.3.3. Suspendedsolids in snow 87 4.3.4. Elementalanalysis of particulatesin snow 91 4.3.5. Soil analysis 94 4.3.6. Comparisonof depositionrates with excesssoil loading 98 4.4. Conclusions 102

CHAPTER 5. POLLUTION IMPACTS DUE TO THE OIL AND GAS INDUSTRIES IN THE PECHORA BASIN 103 5.1. Introduction 103 5.2. Statisticalanalysis 104 5.3. Results 105 5.3.1. Lichen material collected 105 5.3.2.- Total [Cal, [K], [Mg] and [Pb] in lichen tissue 106 5.3.3. Total nitrogen concentrationin lichen thalli 110 5.3.4. Soil analysis 113 5.3.5. Lichen biodiversity 116 5.4. Discussion 120

5.4.1. Chemicalimpacts on lichens and top-soil 120 5.4.2. Lichen biodiversity 123 5.5. Summaryand the broadercontext 127 CHAPTER 6. CONCLUSIONS 130

REFERENCES 142

ACKNOWLEDGEMENTS 169

APPENDICES 171

PUBLICATION ABSTRACT

The chemical compositionof snow, terricolous lichens and top-soil along with abundanceand diversity of lichen communitieswere assessedin the Pechora and Usa basins,North-Eastern European Russia. Transects were established through the principal industrial towns of Vorkuta, Inta and Usinsk to assessthe spatial extent of acid or alkaline and metal deposition.A further eight sites were selectedto assesslocal impactsof oil and gas operations.

In the Usa basin decreasesof nitrogen concentrationin the lichen Cladonia stellaris and winter depositionof non-seasalt sulphatemoving northward were attributedto long rangetransport of oxides of nitrogen and sulphur from lower latitudes.Increased ionic contentand pH of snow, along with elevatednitrogen concentrationsand modified cation ratios in lichens (Cladonia arbuscula and Flavocetraria cucullata) within 2540 kni of Vorkuta and Inta were attributed to local depositionof alkaline coal ash.Nitrate concentrationin snow did not vary with proximity to perceivedpollution sources.Trace metal compositionof winter snowpack,snow-melt filter residuesand top-soils indicatedelevated concentrationsof elementsassociated with alkaline combustionash around coal mining operationsin Vorkuta and Inta, adding significantly to the soil metal loading as a result of ash fallout. Around the petrochemicalindustry near Usinsk there was little evidenceof trace metal deposition.Acid depositionwas associatedwith pristine areas,whereas alkaline combustionash near to emissionsources more than compensatedfor the acidity due to S02 and NO,,. There were limited perturbationsin the chemicalsignals in lichens,top-soils and lichen diversity closeto an oil and gas industrial complex on the Kolva river. Here, there were elevationsof lead and nitrogen concentrationsin lichen apicesand in the apical : basalnitrogen ratio in Flavocetraria cucullata, with lower lichen diversity of epigealand epiphytic lichens.Elevated concentrations of Ba and Ca were found in soil-ash,probably as a result of local emissions from constructionactivity and gasflaring, rather than from long-range transport.Virtually all other sites remainedunmodified and reflected backgroundconcentrations. The ecological impactsof the measuredpollution loads are discussed. CHAPTER 1. INTRODUCTION

1.1. Arctic ecosystems

The Arctic is a fragile environmentand is generallyregarded as a vast sparsely populatedwilderness (Cheng et aL, 1993).Arctic and Subarcticecosystems possesslandscapes that are amongstthe most spectacularand least impactedin the world (Rapportet aL, 1997).They extendfrom extremepolar desertsof the RussianArctic, northern Canadaand Greenlandto the closedcanopy shrub tundra of the low Arctic, and the alpine tundra of mountainregions. They also exhibit much greaterbiological diversity than is commonly perceived (Wookey, 2002). The Arctic representsabout 5.5% of the total landmasson earth (Jonassonel aL, 2000). Most of it is locatedin the northernparts of Russiaand Canada,with smaller areasin Alaska and Scandinavia.The land is snow-coveredfor much of the year, with most of the ground remaining frozen as permafrost,a characteristicof the severeclimate (Fitzpatrick, 1997).Plants and animalsin theseenvironments have to survive extremelylow temperatures during winter, and have lower tolerancesto additional man-inducedstresses, suchas pollution and climate change(Stanhill, 1995;Crawford, 1997;Huntley and Cramer, 1997; Oechelet aL. 1997;Press et aL, 1998;Lavrinenko and Lavrinenko, 1999;Molau et al., 1999).Consequently, despite their daunting size and natural beauty,some Arctic and Subarcticregions are beginningto display signs of degradationas a consequenceof economicdevelopment and resource-exploitation:e. g. Norilsk in Siberia(Vlasova et al., 1991),the Kola Peninsula,Russia (Kapitsa and Golubeva,1997; Reimann et al., 1999), PrudhoeBay, Alaska (Pelley, 2001) and northernAlberta, Canada(Strosher, 2000).

For centuriesthe Arctic has sustainedtraditional lifestyles, suchas reindeer- herding, hunting and fishing (Forbes,1999). Historically, the Arctic had experiencedfew effects of industrial developmentto the southuntil the middle of last century.However, the ever-increasingdemand by the industrialised

2 world for energy,minerals, timber and other resources,has resultedin the searchfor, and the exploitation of, resourcesin Arctic regionsand adjacent higher latitudes (Klein, 2000). In addition, long-rangetransport brings pollution to the Arctic from industrial regionsat mid-latitudesdriven by global atmosphericcirculation patterns(Rahn, 1984;Dayon et aL, 1985;Dovland, 1987;Barrie, 1986a,b; Barrie et aL, 1992;Jaffe et aL, 1993;Ryaboshapko el aL, 1998;Reierson, 2000). Frequent'Arctic haze', first describedalmost 50 yearsago by Mitchell (1956), is now known to be causedby air pollution (Rahn, 1982;Barrie et aL, 1989;Heintzenberg, 1989; Tuovinen, 1990). Accordingly, pollution in the Arctic, particularly air pollution is well- documented(Ottar, 1989;Pacyna, 1995; Steinnes, 1997; Xie et aL, 1999a,b).

1.2. Industrial activity in the Russian Arctic and pollution

Exploitation of non-renewableresources such as mineralsand hydrocarbonsin Arctic and Subarcticregions has increasedduring recentdecades (IUCN, 1993).This is part of a global trend of increasingindustrialisation of the Arctic (Klein, 2000), which is especiallyprevalent in parts of Alaska (e.g. Prudhoe Bay Jaffe et aL, 1995b;Pelley, 2001), and northernRussia (Ziegler, 1987).The latter region hasthe most extensiveindustrial developmentsnorth of the Arctic Circle (Pryde, 1991).These include the mining and metallurgical industriesin the Norilsk areaof Taimyr and on the Kola Peninsula;both theseareas are notorioussources of acid and metal emissions(e. g Vlasova et aL, 1991; Touvinen et aL, 1993; Shahgedanovaand Burt, 1994;Tommervik et aL, 1995; Rigina et aL, 1999).

Terrestrialpollution in RussianArctic environmentshas, until recently, receivedlittle attentionoutside of Russia.Environmental data on the Russian Arctic (e.g. on atmosphericemissions and air quality) are limited (Spiro et aL, 1992;Tuovinen et al., 1993;Ryaboshapko et aL, 1994,1997; Rovinsky et al., 1995;Benokovitz et aL, 1996;,kyriis et aL, 1997a,b; Pacyna,1998). The openingup of the former Soviet Union has revealedmajor environmental

3 problemsat high latitudes,some of which are in the vicinity of its western borders(Tuovinen et aL, 1993;Asgeir-AlmAs et aL, 1995).A prominent exampleis the impact of air pollution aroundthe metallurgical complexeson the Kola Peninsula(Feshbach, 1995). Several authors have classified the area as severelydamaged and certain areashave frequently beendescribed as an 'industrial desert' (Jaffe et aL, 1995a;Caritat et al., 1996ab; Reimannet aL, 1996,1997a,1999,2000; Gregureket al., 1998ab).

Globally, coal combustionremains the dominantanthropogenic source of sulphuremission, with Russiabeing one of the principal emitters(Lefohn et aL, 1999).Numerous studies have documentedthe releaseand effects of ecologically hazardousproducts of fossil fuel combustion(e. g. Dignon, 1992; Singh et aL, 1995;Vassilev and Vassileva,1997; Larssen, et al., 1998,2000 a, b; Kizilshtein and Kholodkov, 1999;Jalkanen, et al., 2000). Electricity is one of Russia'smost polluting industries(Turnbull, 1990),accounting for approximately25% of all industrial atmosphericemissions in Russia(Hill, 1997,2000). This is partly becausecoal with a high sulphur contenthas traditionally beenused for power generation,resulting in significant pollution from emissionsof oxides of sulphur and nitrogen.

Exploitation of natural resourcessuch as coal, oil and gashas been of paramountimportance for the industrialisationof the far north of the former Soviet Union (Ziegler, 1987;Revich, 1995).More recently, gasand oil recoveryhas shown signs of major expansionin the Russiannorth (Forbes, 1999;Lausala and Valkonen, 1999;Locatelli, 1999;Wilson, 2000). Examples of this are gas exploration and developmenton the Yamal Peninsula(Klein, 2000) and oil and gasexploration of the Timan-Pechoraprovince, which includesboth the NenetsAutonomous Region and the Komi Republic (Lausala and Valkonen, 1999;Cottrell, 2002). Industrialisationat high latitudeshas resultedin the developmentof many large Arctic and Subarctictowns, 34 of which are now inhabitedby a total of 3.5 million people(Revich, 1995), addingto the risk of environmentalpollution (Alexeeva-Popovaet al., 1995).

4 Industrialisationproduces significant acid emissionsdeep into relatively pristine Arctic territory. Russiais the single largestcontributor to S02 and NO. emissionsin Europe(Nriagu et aL, 1991;Barrie et aL, 1992;Hill, 1997; Ryaboshapkoet aL, 1998)and about 6.7% of Europeanand Eurasianemissions enterArctic air masses(Barrie et aL, 1989).Norilsk has the highest atmosphericemissions of any city in Russia,with an S02 output in 1988 equivalentto abouttwo thirds of the total UK emissions(Shahgedanova and Burt, 1993,1994).The total S02 emissionson the Kola Peninsulaalone exceed the total sum of thosein Finland, Swedenand Norway, contributing 20% of global anthropogenicemissions north of latitude 60" (Tuovinen et aL, 1993; Kashulina, 1997a).While S02 emissionsin Russiadeclined between 1980 and 1988by 12-30%, NO,,emissions from stationarysources increased by 20% (Shahgedanovaand Burt, 1994).At the sametime it shouldbe emphasisedthat vast areasof the RussianArctic appearto remain in a condition closeto pristine (Rovinsky et aL, 1995).

Analysis of ice corestaken from the Greenlandice sheet,has shownthat there were markedincreases in N and S depositionin the northernhemisphere during the last century (e.g. Brimblecombeand Stedman,1982; Neftel et aL, 1985; Rodheand Rood, 1986;Fischer et aL, 1998).For example,LqJ et aL (1992) demonstratedan increasein S depositionof more than 300% sincethe beginningof the industrial revolution and an increasein N depositionof c. 100%since the middle of last century. The major impactsof acid pollution havebeen seen close to emissionsources in industrialisedregions where there havebeen many documentedexamples of environmentaldamage due to acidification and eutrophication(J6nsd6ttir et aL, 1995).The ecological effects of increasedacid depositionloads over remoter regionsof the Arctic remain uncertain(Woodin, 1997).There is concernthat enhancedN depositioncould force ecologicalchange in otherwiseoligotrophic N-limited ecosystems (Chapinand Bledsoe,1992; Nadelhoffer et al., 1992;Tybirk et aL, 2000; Gordon et aL,,200 1). Despiteits remoteness,several processes in the Arctic

5 play a central role in regulating global climate (Weller, 1995),such as the hydrological cycle and albedo(van der Linden, 2002). Hence,any changesin the RussianArctic environmentdue to climate changeor pollution, (e.g. permafrostdegradation or reductionof winter snow cover resulting in an 'albedo-reductionfeedback') not only has local impactson the Arctic, but also has consequencesfor the global climate (Krankina et aL, 1997).-

13. The Pechora region

The Pechoraregion and the Usa river basin, (seeFigures 2.1 and 2.2, Chapter 2) includesthe north and eastof the Komi Republic and a major portion of the Nenets;Autonomous Region. It has abundantnatural resources,both renewable (e.g. timber) and non-renewable(e. g. minerals,coal, oil and gas)(Lausala and Valkonen, 1999).Traditional livelihoods suchas reindeerherding and fishing are important rural economicsectors for the indigenouspopulation of the region (Gimardi, 2002). In terms of the environment,the region is unique in continentalEurope in having extensivelowland tundra with permafrostin the north and large continuoustracts of 'old growth' taiga forest to the south in the pre-PolarUral mountains.The extent of humanimpacts in the Pechoraregion varies from negligible effects in uninhabitedpristine areasto high impactsin relatively denselypopulated industrial regions.

Coal combustionfor electric power generationhas historically beenthe principal sourceOf S02 and heavy metal pollution in the Pechoraand Usa basins.Other sourcesinclude: coal mining, gasand oil extraction,pulp and paperproduction, constructionand oil refineries (Stateof the Environmentof the Komi Republic, 1992-1998).At the sametime, severalauthors have reportedalkaline emissionsin excessof acid output in the vicinity of Vorkuta, due in part, to the operationof a cementfactory (Kuliyev, 1977,1979; Kuliyev and Lobanov, 1979;Getsen et al., 1994;Rusanova, 1995a, b). Coal is produced in the Pechoraregion from five principal deposits.Four of the deposits (Vorkuta, Halmer-Yu, Yunyagaand Vorgashor)produce coking coal, and the

6 fifth, Inta, producescoal suitablefor combustionin heatingand power plants. In all, there are 18 coal-minesin the Komi Republic,the majority being concentratedaround Vorkuta. When coal combustionoccurs in the absenceof any pollution control measures,the resultantunmodified emissionsinclude acidic gases(SO2 and NO. ) and alkaline, metal-rich particulates(Vassilev and Vassileva, 1997;Kizililshtein and Kholodkov, 1999).For example, Shahgedanovaand Burt (1994) presenteddata suggestingthat annualmean atmosphericconcentrations of N02 in Vorkuta are the highestof any town in the RussianArctic. Although coal reservesremain in the region, many coal- mining communitiesare facing mine closuresand growing emigration (Lausala and Valkonen, 1999).Gas flaring also occursat locations 15-50km north of Usinsk, as part of the gasand oil operations,the principal site being Golovnye Soorhuzheniya(Vilcheck and Tishkov, 1997).

According to Lausalaand Valkonen (1999) and Pelley (2001) the Timan- PechoraProvince is the third most important oil-producing region in Russia and is reputedto contain someof the World's richest deposits.The first evidenceof oil depositsin the region was found in the 16th century and oil was producedand refined by primitive methodsas early as 1745.The region attractedmajor interestin the 1930's,with severaldiscoveries of oil near the town of Ukhta and productionand ftirther exploration beganfollowing the secondworld-war. Altogether, 180 oil and gas fields havebeen discovered in the Timan-Pechomprovince, but only 20 havebeen brought into production (Lausalaand Valkonen, 1999).The Komi Republic is land-locked,bordered by the Arkhangelskregion in the west and the NenetsAutonomous region in the north. Its remotenesshas thus far beenresponsible for the limited exploitation of its oil and gasreserves (Cottrell, 2002). The province is reportedin the businesspress to havethe capacityfor considerablegrowth (International Herald Tribune, 4 October2000). Furthermore,the gasreserves of the Barents Seato the north are also of global significance.Thus, while the coal industry in the Usa basin and the larger Pechoraregion is in gradualdecline it seems inevitable that polluting activities suchas gas flaring, and heat and power

7 generationassociated with gashydrate recovery, will proliferate during the coming decades.

Future exploitation of these oil and gas reserves will necessitate improvements and developments of the present transport infrastructure. Current plans include construction of a road between Naryan-Mar and Usinsk by 2010; this will replace the temporary winter road which can only be used for 3-4 months each year and will require an estimated 950,000 tons of construction material. There are also plans for the modernisation of the existing 147 kin inter-field oil pipeline from Haryaga to Usinsk and reconstruction of the Haryaga-Usa pipeline link.

It is possiblethat the Komi region will face considerablechallenges both in terms of socio-economicdevelopment (Kaýalainen and Habeck,submitted) and from global warming, as generalcirculation modelspredict that temperatureincreases over the coming decadeswill be especiallypronounced at high latitudes(Krankina et aL, 1997;Wookey and Robinson, 1997).Briffia et aL (1995) has shownthat the northern Urals in particular have experienceda pronouncedwarming trend (i. e. elevatedsummer temperatures) during the last 100years. Warming will havepositive consequences,such as longer growing seasonsand reducedenergy consumption for heating,but it could also have negativeoutcomes including loss of reindeerpasture in the tundra and infrastructuredamage due to permafrostcollapse. The latter effect may cause rupture of oil pipelinesand therebyincrease the risk of significant environmentalpollution (Vilchek and Tishkov, 1997).Feshbach (1995) and Pelley (2001) estimatethere are on average,two major oil and gaspipeline spills every day. Lossesof oil accountfor up to 7-20 % of the total annual Russianoutput, equatingto 15-20million tonnesof oil lost through spills annually in Russia.A well-publicised recentspill occurrednear Usinsk in September1994, which disgorgedupto 126,000tonnes of oil and contaminated 68 km2 of the surroundingarea, with significant amountsentering the Kolva and Usa rivers (Vilchek and Tishkov, 1997).

8 As elsewherein Russia,the Pechoraregion faceseconomic difficulties in its transition from a centralisedsystem to a westernstyle market economy (Locatelli, 1999).The conditions in the region are specialdue to its very rich renewableand non-renewableresources and its northern location (Lausalaand Valkonen, 1999).Oil and gasproduction is of particular strategicimportance to the region and to the EuropeanUnion, and is expectedto expandsignificantly. By contrast,mining is now in decline due to the poor quality of somecoal depositsand high transportcosts (Gimardi, 2002). The reservesof oil, gas, minerals,and forest resourcesof the region constitutea firm basisfor economicgrowth, and future east-westco-operation; joint commercialactivity is likely to be basedon the exploitation of thesereserves. For examplethe forestry sectorhas considerablepotential for growth, but managementpractices needto safeguardbiodiversity. However, both the booming oil and gassector and the prospectsof closing coal-minesbring about significant risks of environmentalpollution.

1.4. Pollution monitoring in remote regions

The Pechorabasin has alreadybeen identified as a significant sourceof acid emissions(Ottar, 1989;Nenonen, 1991; Vinogradova, 2000) mainly as a result of coal fired power stationsin the towns of Vorkuta, Pechoraand Inta, petrochemicaloperations in Ukhta and a gas-firedpower station in Usinsk. However, prior to the presentwork therehas beenlittle supportingevidence.

Problemsexist when monitoring pollution depositionin remoteregions. T'here are usually few meteorologicalstations that can be usedto monitor air and precipitation chemistry.Air and min show very high temporaland spatial variation in chemicalcomposition (e. g. Reimannet aL, 1999)and therefore require continuoussampling throughout the year. Furthermore,elemental concentrationsin thesemedia are usually low and so samplecontamination is a significant problem. Alternative approachesinclude: (i) analysisof stored

9 water in snow-packor glacial firn and ice, (ii) the analysisof ecological materialsthat accumulatecontaminants (e. g. soils and plant tissues)and (iii) the use of bio-indicators,the physiology and/orthe distribution of which becomemodified by exposureto pollution.

1.5. Pollution mapping based on analyses of ecological materials

1.5.1.Snow-pack chemistry

Analysis of the chemicalcomposition of snow-packhas frequently beenused to provide information on precipitation chemistry,includin g pollution loading (Jaffe et aL, 1993;Shaw et aL, 1993;Udisti et al., 1994;Colin et aL, 1997; Tranter and Jones,200 1). Collecting snow is relatively easyand multi-element analysisof representativesamples of the depthprofile of the snow-packis an expedientmethod of estimatingwet depositionduring the winter season. Snow-packsamples are well suitedto fingerprinting local emissionsources, evenat low samplingdensity and to mapping spatialvariation in pollution deposition(Reimann et aL, 1996).A useful property of snow samplingis that it measuresthe integratedwet and dry fallout of pollutants from the atmosphere during the period of snowpackaccumulation and maintainsnatural preservationof this material (Shaw et aL, 1993).A potential pitfall in the use of snow chemistryto measureion depositionis ion loss during any partial snowmeltthat might occur prior to samplecollection. Johannessenand Henriksen(1978) showedthat when freshly fallen snow was allowed to melt under laboratoryconditions, c. 60-70% of the total storeof N03-, and 50-60% of NIH4+was eluted in the first 30% of meltwater collected.Thus, periodsof partial thaw can result in redistribution of ions within snow-packand, if there is loss of water to surfacerun off, a decreasein ion concentrationsin the remaining snow. Therefore,sampling during the spring,just before thawing occurs,ensures that most of the total solute load is not lost with the first melt (Tranter et aL, 1986,1988). Snow cover in early spring is thereforean accumulationof the previous winter's precipitation, containingnot only solid

10 snow with its solute componentsand co-depositedparticles, but also blown dust of local natural and anthropogenicorigin (Ayrds et aL, 1995).In addition to dissolvedions in snow theremay be a significant quantity of elements associatedwith particulatematter. Quantification of thesetwo fractions can provide a powerful tool for fingerprinting sources(Caritat, et aL, 1998). Moreover,total elementalloadings can be seriouslyunderestimated if analysis of particulates(such as fly ash) is omitted (Reimannet aL, 1996;Gregurek et aL, 1998a).

Numerousstudies of the spatialvariation in rainwaterand snow-pack chemistryhave been used, for example,in the ScottishHighlands (Tranter et aL, 1988);in Alaska (Dayan et aL, 1985;Jaffe and Zukowski, 1993)and on the Kola Peninsula(Jaffe et aL, 1995a;Niskavaara et aL, 1996;Reimann et aL, 1996,1997b; Caritat, et aL, 1998;Gregurek et al., 1998a).Jaffe and Zukowski (1993) found [N03_1in snow-packcollected at 7 sitesdistributed along a transectparallel with the Dalton Highway, northernAlaska to be in the range 160- 688 ng g-1.These values were 1.5 times greaterthan thoseobserved in Greenland,which the authorsattribute to 'arctic front' activity over Alaska. Tranter et al. (1988) usedsnow-pack chemistry to monitor the impact of black snowfhll on stream-waterchemistry in the ScottishHighlands. Iley found that black acidic snowfalls occur under specific meteorologicalconditions and can increase[SO 421 and [N031 in snowpackby an order of magnitude. '

1.5.2. Analysis of accumulators

1.5.2.1. Lichen chemistry

Mat-forming terricolous lichens are important componentsof plant communitiesat high latitudes(Larsen, 1980;Ahti and Oksanen,1990), where they contributeto nutrient cycling and hydrology as well as secondary production (e.g. grazing) (Chapin and Bledsoe, 1992;Longton, 1997).They are prominent in Arctic and alpine zonesas well as in sub-arcticheaths and boreal forests.Habitats with extensiveclosed lichen mats, are mainly found on well

11 drained,moderately sloping groundscharacterised by deepwinter snow cover. In the arctic and boreal zonesthese habitats are called lichen heathsand in the boreal forests,lichen woodland (Longton, 1988).

Lichens are primarily dependanton atmosphericsources of nutrientsand thereforereadily accumulateatmospheric contaminants, such as metalsand radioelements(Nash and Gries, 1995ab; Seaward,2002). In this sensethey are thereforeamongst the most pollution sensitivereceptors in terrestrial ecosystems(Wielgolaski, 1975;Richardson, 1988). The high toleranceof lichensto most metal contaminantstogether with their slow growth are among the main factorsthat make them effective accumulators(Pakarinen et al., 1978; Nieboer and Richardson,198 1; Puckett, 1988;Nash, 1989).Accordingly, lichenshave beenused widely to monitor environmentalquality as a result of industrial activities (e.g. Nimis et al., 1993);examples include fertiliser manufacturingplants (Kauppi, 1976),steel works (Pilegaard,1978), the petrochemicalindustry (Addison and Puckett, 1980;Pakarinen et al., 1983), zinc and nickel foundries(Nash, 1975;Nieboer et aL, 1972)and coal-fired power stations(Olmez et aL, 1985;Garty, 1988;Gonzalez and Pignata,1997). Spatialvariation in the chemicalcomposition of lichenshas beenfrequently usedto map atmosphericdeposits (Fahselt et aL, 1995;Nash and Gries, 1995a, b; Reimannet aL, 1997c,2001; Takala et aL, 1998;Grodzinska. et aL, 1999; Riget et aL, 2000); for example,Grodzinska et aL (1999) usedCladonia stellaris to monitor airbornepollution at 26 sites along transectson the Kola Peninsulaand showedthat elementconcentrations were higher closerto emissionsources. Values of Pb in C stellaris varied from 45.6 Pg g" closeto smeltersin Monchegorskto 1.82 [tg g-1at remote locations.Changes in the physiological statusof lichenshave also beenused to monitor atmospheric pollution gradientson the Kola Peninsula(Tarhanen et aL, 1996).

'Me principal lichen speciesfound in lichen-dominatedground cover in the Arctic are membersof the generaCladonia (sub-genusCladina), Cetraria, Flavocetraria, Alectoria and Stereocaulon.A characteristicfeature of mat-

12 forming lichens is that they grow acropetally(i. e. at their apices)and vertically upwards,while in maturemats the thallus basesdie off. Thus the upper living parts of the maturemats are often supportedphysically by a deeplayer of dead, structurally intact, thallus or necromass(Crittenden, 2000). Crittenden(1989) suggestedthat suchcarpets are largely ombrotrophic('rain-fed'), and showed that Cladonia stellaris captured> 80% of wet-depositedinorganic nitrogen (Nf4+ and NOD. Key macronutrientsfor mat-forming lichens, such as N and P are probably derived largely from atmosphericdeposits (Crittenden and Kershaw, 1978; Crittenden,1983,1996,1998; Kyt6viita, 1993).There is also evidenceto suggestthat N and P are conservedwithin thalli by, amongstother processes,internal recycling (Crittenden, 1989;Ellis et d, 2003). Elevated concentrationsof ions in polluted precipitation therefore,might be expectedto have an impact on lichen growth (Crittendenet aL, 1994)and chemical composition(Kyt6viita and Crittenden, 1994;Hyvddnen and Crittenden, 1998a).

Increasedatmospheric N depositionhas beenrecognised as a potential threat to plant communities(Pitcairn et aL, 1995).Nitrogen pollution is generally positively correlatedwith acid loads becausenitrate is a componentof acid deposition.The N contentof lichen thalli is relatedto N depositionand has beenused in severalpollution monitoring exercises(Bruteig, 1993b;Halonen et aL, 1993; Sochting, 1995).Hyvdhnen (1997) and Hyvannen and Crittenden (I 998b) arguedthat mat-forming lichens are particularly good bioindicatorsof air pollutant loads becausethey typically occur in open situationsintercepting rainfall directly and largely unmodified by vascularplant canopies,which can confoundrelationships between the chemistry of epiphytic lichens and the atmosphere(Fanner et aL, 1991 a, b). They are probably relatively independent of the chemicalinfluence of the substratumowing to accumulationof basal necromasswhich tendsto isolatethe living parts of the thalli from underlying soil (Crittenden, 1991; Ellis et aL, 2003).

13 Hyvarmen and Crittenden (1996) also examined relationships between rainfall acidity and lichen chemistry. Kyt6viita (1993) and Kyt6viita and Crittenden (1994) had earlier conducted controlled experiments on the effects of simulated acid rainfall on the mat-forming lichens Cladonia stellaris and Stereocaulon paschale. Kyt6viita (1993) observed that increased rainfall acidity promoted the migration of divalent cations (Caý+and Me) from the thallus apices downwards within the thalli, but had little affect on Ký concentrations. This W: increased the ratio Ký : Mg2' and C2+ in the thallus apices which she attributed to the different locations of these ions; K' is largely located with protoplasts which forms a major proportion of the thallus. Calcium and M g2+ are located on cell wall exchange sites. Hyvqflnen and Crittenden (1996) demonstrated that the K' : Mg2+ratio in the apices of Cladonia portentosa varied among heathland sites in the British Isles and that this variation was highly correlated with W concentration in rainfall. The authors suggested that this ratio might provide a sensitive chemical marker for rainfall acidity in pollution surveys.'

1.5.2.2.Soil chemistry

In Arctic areas,the topsoil is frozen for at least six monthsof the year (Niskavaaraet aL, 1997).In spring, the still partly frozen soil is subjectedto a sudden,intensive pulse of acidic snow-meltpercolating through the uppermost soil layers;this is a phenomenaobserved even in pristine areas(Reimann et aL, 1996).For exampleReimann et aL (1996) found that the most acidic snow- pack sampleson the Kola Peninsulawere found at backgroundsites in northern Finland (pH 4.3-4.7). In contaminatedareas, such as thosearound the roasting and smelting industrieson the Kola Peninsula,melt-waters may contain additional amountsof acidifying componentsand heavy metalsfrom the accumulationof winter depositionin snowpack(Niskavaara et aL, 1997). Analysis of the underlying soil, can be usedto evaluatelong term accumulation of conservedpollutants (e.g. Boyd et aL, 1997;Reimann et al., 1997a,c, 1998, 2000). Soils act as a major sink for atmosphericdeposits. In particular, the

14 topmost few cm.of the soil profile becomea sensitiveaccumulator in the terrestrialenvironment (Niskavaara et aL, 1997).In addition to the potential receiptof pollutants they are subjectto the eroding effects of rain, wind and frost (Howells, 1995).Depending on the vegetationtype, climatic conditions, soil formation conditionsand extent of anthropogeniceffects, topsoils contain varying amountsof organic and inorganic materials.Soil organic matter is one of the major factors controlling the physical and chemicalproperties of soils including metal binding capacity(Niskavaara et aL, 1997).

In highly polluted areasnear industrial centres,the physical and chemical propertiesof topsoils can becomeradically modified. Soil contaminationdue to alkaline emissionsfrom coal combustionhas been widely reported(e. g. Singh et at, 1995;Larssen et at, 1998,2000a,b; Kizililshtein and Kholodkov, 1999), including at severallocations in Russia(e. g. Rusanova,1995a, b; Hill, 1997; Jalkanenet at, 2000; Haapalaet at, 2001). Depositionof alkaline fly ash particulateselevates both pH and total metal contentof soils (Vassilev and Vassileva, 1997;Reimann et at, 2000; Haapalaet at, 2001). Increasedsoil pH resulting from inputs of alkaline fly ash,may actually reducethe metal ion concentrationin solution despiteincreasing the total metal loading to the soil (Robb and Young, 1999).Such effects are usually most pronouncedclose to emissionsources where particulatefallout is maximal. Conversely,acidic depositionresulting in a progressivedrop in soil pH, will raisethe solubility and rate of leachingof eventhe most strongly bound metal elements(Reimann et at, 1996).

Two approacheshave been used to sampleheavy metal contaminationin soils. Either the uppermost,organic horizon is sampled,or soil is removedto a standarddepth (Reimannet aL, 1997a).Both approacheshave advantagesand disadvantages.A depth-definedsample can be taken anywhere,independent of the soil type or the existenceof an organic layer. In this case,element concentrationsrecorded will be characteristicfor, e.g. 'the uppermost5 cm of soil' throughoutthe samplingarea. However, in podzolic soils in particular

15 problemscan arisewith depth-definedsampling due to inter-site differencesin the depth of the organic horizon and hencethe quantity of mineral material in samples.Heavy metalstend to accumulatein the organic fraction and thus, recordedmetal concentrationsmight be considerablyhigher in samples consistingonly of organic material comparedto thosesamples taken from soils with a very thin organic layer for the sameinputs (Reimannet aL, 1997a). Horizon orientatedsampling, on the other hand,will result in substantial differencesin the thicknessof the final samplestaken, with anthropogenic input accumulatingin the top few cm.of the soil profile. This can confound comparisonsbetween sites that have0-horizons of very different thicknesses (Reimannet aL, 1998).Niskavaara et aL (1996) and Reimannet d (I 997a) useddepth-defined sampling regimes (0-5 cm topsoil layer) for regional mappingof heavy metalson the Kola Peninsula.Analysis of soil samples allows for assessmentof aerial depositionby comparisonof concentrationsper unit area,provided samplingis carried out to sufficient depthto audit all the analyteof interest.Also, assessmentsof aerial inputs of someelements can be usedto compareconcentrations in the mineral phasebetween topsoil and the underlying subsoil.

Numerousinvestigations have usedvariation in soil chemistryto map pollution deposition,particularly in the caseof heavy metals(e. g. Balaganskaya,1997; Kashulina, 1997b;Reimann et aL, 1997a,1998; Haapala et aL, 2001). For example,Reimann et al. (I 997a)collected top-soils at 174 sites from eight catchmentson the Kola Peninsula,constituting an areaof 188 000 km2 and showedthat soils closeto smeltersin Monchegorskand Nikel were enriched with heavy metal concentrationsup to 600 times greaterthan thoseat Finnish backgroundsites (e.g. 2520 comparedto 2.5 mg kg -1 Ni; 16400compared to 745 mg kg -1 Fe). ý

16 1.53. Impacts on communities - lichen biodiversity

Due to their susceptibilityto S02 and someother air pollutants,epiphytic lichenshave been used for somedecades to monitor air pollution (Hawksworth and Rose, 1970;Hawksworth, 1971,1973;Nieboer et aL, 1977;Pirintsos et aL, 1993;van Dobbenand ter Braak, 1999).In this respectthe use of lichens as indicatorsof air pollution has beenextensively reviewed (Ferry et aL, 1973, Hawksworth, 1974,1975; Andersonand Treshow, 1984; Garty, 1993; Henderson,1993; Gries, 1996;Conti and Cecchettib,2001). In boreal forests, localised.decline in abundanceof the epiphytic lichens,Alectoria, Usneaand Bryoria hasbeen attributed to increasingair pollution and acid rain (Helle et aL, 1990;Kauppi and Halonen, 1992;Aamlid and Venn, 1993;Thor, 1998). However, factors other than air pollution can modify epiphytic lichen abundance,such as changesin climate and standage (Kuusinen.et aL, 1990; Hyvannen et al., 1992).

Biodiversity is defined as 'Totality of hereditaryvariation in life forms, across all levels of biological organisationfrom genesand chromosomeswithin individual speciesto the array of speciesthemselves and finally at the highest level to living communitiesof ecosystems,such as forestsand lakes' (Wilson, 1988).Diversity is usually measuredas speciesrichness or the numberof speciesin an areaand varies with spatial scale.Alpha diversity is defined as, 'the number of specieswithin a small areathat is relatively uniform' (Wilson, 1988).

Methodologiesfor assessingdiversity and abundancehave beenreviewed by Will-W olf et al, (2002). Severalstudies of lichen diversity and abundancehave beenundertaken in boreal forests(Gorshkov, 1989a,b; Gorshkovand Lyanguzova,1989; Oksanen et aL, 1990;Armleder et aL, 1992;Aamlid and Venn, 1993;Bruteig, 1993a;Kuusinen, 1994); for example,Bruteig (1993a) assessedepiphytic lichen specieson Pinus sylvestrisat 193 sites in Norway and

17 discoveredthat at sites in the southernparts of the country where air pollution was greater,Bryoria and Usneaspecies were largely absent.

1.6. The aims of the study

Until now there have beenfew detailedstudies or audits of terrestrialpollution loads in the Pechoraregion. Thosethat havebeen conducted were in the immediatevicinity of towns, such as the Bolshezemel'skayatundra aroundthe city of Vorkuta (Getsenet al., 1994,1997; Rusanova,1995a, b). The specific objectivesof the current study were to assessthe extent of acid (or alkali) and metal depositionin the Usa basin and the larger Pechoraregion by mapping spatialvariation in the chemicalcomposition of snow, lichens and top-soil. In addition, lichen biodiversity was investigatedin order to yield further information on air pollution impactsat specific sites.

The principal industrial centres,in the Usa basin are Vorkuta, Inta and Usinsk. The initial investigationsinvolved taking measurmentsalong transectsthrough thesetowns. Subsequentstudies examined industrial siteselsewhere in the Pechorabasin, considered to be potential pollution 'hotspots'. Conditions at theseindustrial siteswere comparedwith nearbyundeveloped 'reference' sites of broadly similar community structure.The dataproduced will provide a baselineagainst which the extent of pollution in the future can be determined.

The specific objectivesare detailedbelow:

1. To assessthe extent of acid, alkaline andN depositionaround Vorkuta, Inta and Usinsk as indicatedby the spatial variation in the chemical compositionof winter snow-packand terricolous mat-forming lichens.

2. To provide information on the distribution and magnitudeof trace metal compositionin snow and soil resulting from fossil fuel combustionand petrochemicalindustrial processeswithin the Usa basin and extendingto the larger Pechoraregion.

18 3. To seekevidence of environmentalimpacts of an expandingpetrochemical industry in the Pechoraregion. This was achievedby quantifying the chemicalstatus of terricolous mat-forming lichens and top-soil samplesand by measuringthe diversity of epigealand epiphytic lichen communitiesin closeproximity to perceivedpollution 'hot spots' and in unpolluted 'reference' sitesof broadly comparablecommunity structure.

4. To ftwther evaluatethe use of terricolous lichens as indicatorsof nitrogen and a'ciddeposition.

5. To assess,as a wider objective of the presentwork, the likely extent to which the Arctic ecosystemresponse to climate forcing in this region might be modified by pollution.

19 CHAPTER 2. MATERIALS AND METHODS

2.1. Study areas and sampling regimes

This study was part of two EuropeanCommission programmes: TUNDRA (ELIsidra,Degradation in the RussianArctic) and SPICE (Sustainable developmentof the Pechoraregion In a ChangingEnvironment and society). Both programmeswere locatedin north-eastEuropean Russia. (see www. urova.fi/home/ýrktinen/tundra and www. urova.fi/home/arktinen/spice).

2.1.1. TUNDRA programme (EUNdra Degradation in the Russian ArCtic)

The study sites are located in the Usa river basin lying betweenlatitudes 64* and 68* N in the Komi Republic, north-eastEuropean Russia. This region has an areaof 93,000kmý. The Usa river is a major tributary of the Pechorariver, which flows into the BarentsSea and is one of the largestrivers in Europe.The region is unique in continentalEurope for having extensivelowland tundra with permafrost,together with an upland area(i. e. the Ural mountains)up to 1750m. a. s. l. (Solovieva et aL, 2002). The Usa basin straddlesthe tree line with forest tundra and taiga in the south,dominated by spruce(Picea obovata) and birch (Betulapubescens)together with pine (Pinus sylvestris) and a small incidenceof larch (Larix sibirica). The taiga zone is further sub-dividedinto northerntaiga and extreme-northerntaiga. The tundra zone encompasses forest-tundrain the south (Arctic tree line) and shrubtundra in the north. The shrubtundra is dominatedby dwarf birch (Betuld nana) found in well drained and slightly elevatedsites. In addition the shrubtundra is characterisedby Vacciniumspp. and Empetrumspp. as well as willow found in depressions.

Transectswere establishedthrough the three principal towns of Vorkuta (67'30'N, 64'05'E; Transect 1), Inta (66*03'N, 60'10'E; Transects2 and 3), and Usinsk (66'01'N, 57*30'E; Transect4). 'Ibe transectswere approximately

20 130km W-E, 240 km S-N (Transects2 and 3 in combination)and 140km SW- NE in length, respectively.It should be noted that, for logistical purposes, transectsthrough Inta were assignedtwo numbers:Transect 2 to the north and Transect3 to the south.

Coal mining is the main industry in both Vorkuta and Inta where there are 7 and 4 working mines,respectively. By contrast,Usinsk has developedin responseto the recentemergence of the gasand oil industries.The Vorkuta region is the largestindustrial centrein the North-Europeantundra. It consists of the main city and more than 10 sub-centreslocated near coal-mines and other industrial units (Virtanen et al., 2002). Atmosphericpollution in the Vorkuta areais mainly causedby emissionsfrom coal combustionat the nearbypower plant, cementfactory, dust from coal-minesand burning of waste rock nearthe coal-mines(Virtanen et aL, 2002). As Vorkuta is the largest industrial centrein the area,the total aerial emissionsare about 8-9 times higher than in Inta and Usinsk. Quantitiesof pollutants emitted by the towns have beensummarised by Solovievaet al. (2002). Coal mining is the main sourceof atmosphericcontamination in the Usa basin (32.7% of total emissions),followed by gas(24.4%) and oil extraction (13.8%), power generation(10.8%) forestry, timber, pulp and paperproduction (3.5%), construction(3.0%) and oil refineries (2.7%). Briefly, annualemissions Of S02 andNO. (106kg) in 1998were, respectively,37 and 7 (Vorkuta), 16 and 1.5 (Inta), and 6 and 2 (Usinsk).

The topographyin the region is relatively smooth.Elevation varies from about 50 m above sealevel (a.s. l. ) in the deepestriver valleys to about250 m a.s. l. on the tops of smoothhills. The Ural mountainslocated east of the Usa,basin have valley floors at 200 m a.s. l., whilst most of the mountainsare 600-900m as. l., with the highestpoints reachingover 1750rn a.s. l. (Virtanen et aL, 2002). The lowest point is 2ma. s.l., while the highest point is 1,895m (Narodnaya mountain). The Timan Ridge, with elevationsof 200-500m a.s. l., runs from the north-westto the south-eastacross the region. To the north of the Timan

21 Ridge, there is the PechoraPlain, and to the souththe Mezen-VychegdaPlain. 'Me climate in the region is mainly continental,although the BarentsSea influencesthe climate in the north. For the towns of Vorkuta, Inta and Usinsk meantemperatures are, respectively,-21, -20 and - 18 *C in January,and 12.4, 13.8and 14.1 *C in July. The long-term meanannual air temperaturesfor the towns are -6.0 (Vorkuta), -4.4 (Inta) and -3.2 'C (Usinsk). The meannumber of days with snow cover for the 3 towns are: 237 (Vorkuta), 217 (Inta) and 213 (Usisnk). Average annualprecipitation in the region is 625 mm, ranging from about 700 mm in the southto 500-550mm in the north and 1,500mm in the northernUrals. Mean annualprecipitation levels for Vorkuta, Inta and Usinsk are 518,473 and 495 mm, respectively(data suppliedby the Institute of Biology, Komi ScienceCentre). The entire transectthrough Vorkuta is located in the permanentpermafrost zone, whilst transectsthrough Inta straddlethe continuousand discontinuouspermafrost zone. The transectthrough Usinsk is locatedin discontinuouspermafrost. In the Vorkuta region the prevailing winds blow from the southwestand south from Septemberto April. Prevailing winter winds blow from the north aroundInta and are generallyvariable around Usinsk. Southwesterlywinds generallyprevail over the entire region (Taskaev, 1997).

Samplingsites (4-6) were selectedalong eachtransect. The sites were distributed at logarithmically increasingdistances from the town centres (Figure 2.1, Table 2.1), althoughthis ideal distribution was modified to meet the needsof other collaboratingresearch groups. At eachsite, three sub-sites were selected,5 00-1000 m apar4at which 6 replicate samplesof ecological materials(see below) were collected at distances10-20 m. apart in open areas subjectto minimal tree canopyeffects (Derome, 1992;Reimann et aL, 1999). Thesewere usually inter-treepositions in open forest, or in open tundra. Most sites were in wildernessareas remote from roads.

Due to the high costsand logistics involved with helicopter charterit was not always possibleto visit all the sites along the transects.During spring 1998,

22 only eight sampling sites were visited along transects 2/3. Four sampling sites were visited along each transect, so that site 2.2 (Lake Tumbulovaty) to the' north and site 3.2 (Mezhgomyye lakes) to the south were the transect extremes. During summer 1998 site 2.4 (Lake Lyz'vad) was not reached, therefore lichen and soil sampling was not possible here. Mean annual air temperature, precipitation data, vegetation type and industrial activity for Vorkuta, Inta. and Usinsk are presented in Table 2.2.

64* N 11 100km

Figure 2.1. Map showing sampling sites on transectsthrough the towns of Vorkuta (V), Inta (1), and Usinsk (U) in the Usa basin,Northeast European Russia.Linked triangles indicate the approximateposition of the treeline across the Usa basin. Land above500 m is also indicated.(Map reproducedfrom P. D. Crittendenwith kind permission).

23 Table 2.1. Summaryof main samplingsites along 4 transects,within the Usa, basin study area.

Site No. Nwne of site Co-ordinates Elevation Distancefrom nearesttown

TransectI 1.1 Lake Padvaty 67'27'N63*05'E 160 45 Ian W of Vorkuta 1.2 Malen'kiy arvozh 67*30'N63*30'E 150 30 km SW of Vorkuta, 1.3 Vorkuta 67*34'N 64'09'E 180 2 Ian NE of Vorkuta IA Lake Ngayatslyakha 67*35'N64"IYE 160 12 km NE of Vorkuta, 1.5 Lake Mutnoye 67*44'N64*52'E 260 40 Ian NE of Vorkuta 1.6 Lake Protochnoye 67*47'N 65*37'E 180 70 Ian NE of Vorkuta

Transect2 2.1 KhosedayuRiver 67"15'N59*37'E 70 130 Ian N of Inta 22 Lake Tumbulovaty 67"07'N591134E 110 110 Ian N of Inta, 2.3 Two Lakes near Adak 66*35'N 59*45'E 75 62 Ian N of Inta, 2.4 Lake Lyz'vad 66" 16'N 60* IYE 52 20 Ian N of Inta 2.5 Lake Swan (Lebedinoye) 66006'N60'15'E 21 7 km N of Inta

Transect3 3.1 Vangyr river 64*59'N59"12'E 270 110 Ian SW of Inta, 3.2 Mezhgomyye lakes 65*15'N59*40'E 510 90 km SSW of Inta, 3.3 Lake Van'kavad 65*59'N59`2TE 60 32 Ian SSW of Inta 3.4 'Fox Lake' 651159'N60"01'E 60 7 km SSW of Inta 3.5 Inta 66003'N60"IO'E 60 2 Ian SSW of Inta

Transect4 4.1 Lake Bosmanvad 65*48'N 57*03'E 40 30 km SW of Usinsk 4.2 Lake Chakty 65"58'N571116'E 50 15 km W of Usinsk 4.3 Usinsk 65*59'N57035'E 60 2 kTnE of Usinsk 4A Lake Kankur'ya, 65"57'N 57*42'E 40 10 Ian NE of Usinsk 4.5 Isaak-Ty/Shar'yu 66*07'N581118'E 50 35 Ian NE of Usinsk 4.6 Adz'vavom 661133'N59*16'E 50 100 km NE of Usinsk

24 Table 2.2. Principal industrial towns within study area.

Town Co-ordinates Mean Annual Principal Principle Precipitation(mm) industrial vegetation (Temperature,*Q* activity types on transects

Vorkuta 67"30'N, 518(-6.0) coal mining open arctic tundra, 64*05'E (7 mines), alpine tundra cementfactory Inta 66"03'N, 473(4.4) coal mining Pine & birch 60*10'E (4 mines) forest, open tundra, alpine & arctic tree-lines Usinsk 66101'N, 495(-3.2) oil and gas Pine & birch 57"30'E extraction forest

* Data suppliedby the Institute of Biology, Komi ScienceCentre

2.1.2. SPICE programme (Sustainable development of the Pechora region In a Changing Environment and society)

'Me Pechoraregion (of which the'Usabasin is a component),includes the north and eastof the Komi Republic and a major portion of the NenetsAutonomous region. It is boundedby the Ural mountainsto the eastand by the Timan range to the west. The areahas extensivenatural resources,both renewable(e. g. forests)and non-renewable(e. g. minerals, coal, oil and gas).In terms of the environment,the region is unique in continentalEurope with extensivelowland tundra and permafrostin the North and the largestcontinuous area of 'old growth' taiga to the south in the Urals. There are a variety of human impactsin the region with relatively uninhabited'pristine' areasand a few densely populatedregions, supported by indigenouseconomies and a few recentstate- inducedindustries with attendantpollution.

Oil and gasproduction has strategicimportance to the region and is expectedto expandsignificantly (Lausalaand Valkonen, 1999;Pelley, 2001). However,

25 somesegments of the coal industry are in decline due to the poor quality of the coal and high transportationcosts (Gimadi, 2002).

Samplingsites were chosento quantify the chemical statusof terricolous mat- forming lichens and top-soil samplesand by measuringlichen biodiversity of epigealand epiphytic lichens in closeproximity to perceivedpollution 'hot spots' and in unpolluted referencesites of broadly comparablecommunity structure.Across the Pechorabasin, 'industrial' sites (e.g. FI j) and unpolluted 'reference' sites (e.g. F2,), comprisedof the following: Ukhta area(F I j), Belaya Kedva river (F2,,), Ortina river (173i),Neruta river (F4,), Svetly Vuktyl (175j),Maly Patok (FQ, Upper Kolva (F7j) and Moreyu river (F8,) (seeFigure 2.2; Table 2.3). Within the tundra zonethe Ortina river site (F3j) andNeruta river site (F4,) were chosento comparethe effects of the 'industrial' petrochemicalcomplex at F3j with the 'reference' site at F4r near to the Pechoradelta. Additional tundra siteswere chosenat Upper Kolva, F7j, with its large oil industrial complex and comparedwith Moreyu river, F8, which is partly protectedfor reindeerherding, and is perceivedas being 'pristine'. Within the taiga zonethe site nearUkhta on the Izhma river at FIj, was chosen due its petrochemicalindustry (oil processingat Ukhta and gasprocessing at nearby Sosnogorsk)and forestry, in order to comparewith Belaya Kedva at site, F2,,,which is pristine. The site at F5j near Svetly Vuktyl was selectedas a possiblepolluted areadue the growing gas industry basedthere. The site at Maly Patok,F6,, was chosenas a suitablecomparison as it is situatedin the protectedYugyd Va national park.

Fieldwork was carried out during the spring of 2000 (F3j and F4,) and 2001 (F I j, F2, F5j, F6,, F7j and F8,) and beganin early Juneat the southem-most sites until mid-July for the northem-most,tundra site at F8,. Each site was visited for approximately6 daysto allow membersof other collaborative groupsto completetheir work.

26 Table 2.3. Summaryof the main samplingsites within the Pechoraregion.

Site Nameof Co-ordinates Type of industry and No. site status of site

Fli lzhma river (near Suz'u 6344'10"N, Petrochemicals (oil and gas), forestry, rivermouth), Ukhta area 5342'57" E, ftagmented lowland taiga

F-2, Belaya Kedva river 64*19'27"N, Pristine lowland taiga 53103'39'E,

(oil F'3i Ortina river, Naijan-Mar 67*55'59" N, Petrochemicals and gas), tundra area 54"02'33" E, delta area

Neruta 68*00'10" N, Reindeer herding, F4, river, pristine tundra, Malozemelsk tundra 5224'16" E, partly protected, coastal

Svetly Vuktyl 63*47'42" N, Gas industry, fragmented lowland F5j river, Vuktyl area 57'32 ' 36 " E, taiga

Maly Patok 64'18'54" N, Pristine taiga in Ural foothills, F6 river r 59 ' 04 ' 40 " E, protected Yugyd Va national park

Kolva river (near the 67*08'22"N, Large oil industrial complex, tundra F'7i Kharayaha river mouth) 5641'41" E,

Ile Moreyu river (near 67*52'51" N, Reindeer herding, pristine tundra, F8, the Syamayu river mouth) 59*43'2 1" E, partly protected, coastal

27 F49 F8o tF7o Vorku Arctic t

arian- ar %0 -- ýn!. - v...6.. tt)

s Inta

V.

13Pechorý 13 *F2 0N Gas o/ He CIS D Oil ------Oil pipeline F1 Gas pipeline

100 km

Figure 2.2. The Pechoraregion in northeasternEuropean Russia, with major towns, industrial areasand natural ecotones.

28 2.2. Collection of ecological materials

2.2.1. Snow

Snow samples were collected between March and April in 1998 and 1999, on each occasion prior to the onset of seasonal snowmelt, as most of the total solute load can be lost from snow profiles with the first melt (Tranter et aL, 1986,1988; Jaffe and Zukowski, 1993). On average, the mean dates for snowmelt commences on 9th, 15th and 26th of April at Inta, Usinsk and Vorkuta, respectively (Institute of Biology, Komi Science Centre Annual Reports, communicated by N. Solovieva). Sampling sites furthest away from towns were reached by helicopters (Mi-8), charted from Komiavia. Skidoos, overland tracked vehicles or skis were also used for travel and transportation. A snow pit was excavated at each collection point using a stainless steel spade, taking care not to disturb or contaminate surface snow at the top of the pit face to be sampled (Figures 2.3.a and 2.3.b). Care was taken to sample at least 500 in away from vehicles or helicopters. Ii.'

(a)

Figure 2.3a. Snow sample collection using a 250 mL capacity low-density polyethylene (LDPE) bottle. Sampling involved repeatedly scraping the mouth of the bottle up the 'cleaned' face of the pit and compressing the loose snow into the sampling bottle.

29 - it

- dbý

(b)

Figure 2.3b. Snow sampling from sballow pits at the tundra site, Lake Protochnoye, 70 km NE of Vorkuta, along Transect 1. (Photos a and b: P. D. Crittenden).

The face of the snow pit to be sampled was scraped downwards with a piece of PTFE sheet (after Tranter et aL, 1986) to prepare a clean surface; snow samples were collected in a 250 mL capacity low density polyethylene (LDPE) bottle. Collection was achieved by repeatedly scraping the mouth of the bottle up the 'cleaned' face of the pit (after Legrand and Delmas, 1985) with the snow being compressed into the bottle using a 35 nun diameter perspex rod. Snow was not collected from the lowermost 20 cm. of the snowpack as a precaution against contamination from underlying surface soil (Shaw el aL, 1993). Samples were maintained frozen both during shipment and in the laboratory prior to analysis. For logistical purposes sample bottles were stored and transported in large alurninium boxes that had been fully insulated with polystyrene. Overnight these boxes were stored outside in the absence of any freezer facilities whilst staying in Russia. On average the overnight bottles, temperatures varied between -10 and -30 'C. The sample PTFE scraper, perspex rod and spade were all previously cleaned by rinsing in 2 hot washes of deionised (DI) water and finally by rinsing in ultra high purity water (Boutron, 1979). Low density polyethylene bottles were chosen for their low

30 cation content and the apparent absence of any leaching or ghost effects evident in collected snow samples (Gjessing, 1989). Powder-free LDPE gloves were wom during snow sampling both in the field and in the laboratory to minimise contamination.

2.2.2. Lichcn sampling

Lichen samples were collected between July and August in 1998 and 1999 for TUNDRA and June and July in 2000 and 2001 for SPICE. At least one species of terricolous mat-forming lichen of the genera Cladonia [C. stellaris (Opiz) Pouzar and Vezda, C. rangiferina or C. arbuscula (Wallr. ) Flot. ] or Flavocetraria [F. cucullata (Bellardi) Kdmefelt and Thell] was collected at sub-sites during the snow-free season, subject to availability (Figure 2.4. ). These species were chosen to provide biomarkers for atmospheric deposition and because of their ubiquity and abundance in forest tundra. At each site three sub-sites were selected, 500-1000 rn apart, at which 6 replicate samples of lichen material were collected at distances 10-20 m apart in open areas subject to minimal tree canopy effects; these were usually inter-tree positions in open or in open Wndm.

Figure 2.4. Lichen sampling using LDPE containers and powder-free LDPE gloves to minimise containination. (Photo: P Kuhry).

31 Again, local Mi-8 helicopters were used to reach the most remote field sites and, when logistics allowed, other sites were reached by small boats and overland tracked vehicles. The majority of sub-sites were then reached on foot. Where sites were located close to towns some sites were accessedby car, although sub-sites were again reached on foot and chosen some distance away from the road to minimise road effects. Approximately 20 krn beyond the northern-most site at Khosedayu river, 2.1, (see Figure 2.1, Table 2.1) on transect 2/3 additional lichen samples were collected along the Upper Kolva river during July 2000 by Dr Peter Kuhry, University of Lapland.

Lichen sampleswere air-dried, either under field conditions or in unheated rooms, sealedin LDPE containersand storedat 4 'C until analysis.Powder- free LDPE gloves were worn when handling lichens both in the field and in the laboratoryto minimise contamination.

2.2.3. Soil

Soil samples were collected between July and August in 1998 and 1999 for TUNDRA and June and July in 2000 and 2001 for SPICE and were collected from the same sub-sites as lichen samples. At each site three sub-sites were selected, 500-1000 rn apart, at which 6 replicate samples were collected at distances 10-20 m apart. The samples were collected 5 rn from the base of trees, usually Betula sp. or Sorbus sp. in open areas subject to minimal tree canopy effects; these were usually inter-tree positions in open forest, or in open tundra. Approximately 20 km beyond the northern most site at Khosedayu river, 2.1, (see Figure 2.1, Table 2.1) on transect 2/3 an additional set of top- soil samples were collected along the Upper Kolva river during July 2000 by Dr. Peter Kuhry. Collection involved excavating organic and mineral topsoil from a 20 x 20 cm plastic quadrat with a stainless steel hand trowel, which was cleaned between samples to avoid cross contamination (Figure 2.5). Soil samples were passed through a4 mrn stainless steel sieve in the field, double- wrapped in polythene bags and, on return to the UK, were stored at -20 'C prior to analysis. The thickness of the surface organic and litter layers were recorded

32 for all quadrats. Because of variation in the depth of the organic layer (0- horizon) it was decided to sample to a standard depth of 5 cm following, for example, Niskavaara et aL (1997) and Reimann et aL (I 997c). Powder-free polythene gloves were used at all times both in the field and in the laboratory to minimise the risk of contamination. Soil was imported into the UK in accordance with protocols established by MAFF (DEFRA) (licence number PHL 18/2351[08/97]).

(a)

(h)

Figure 2.5. (a) Soil sampling below terricolous lichen mats in an open area to minimise tree canopy effects. (b) Equipment used for soil sampling from left to right: double-wrapped polythene bags, plastic quadrat, stainless steel hand trowel, stainless steel sieve with base and stainless steel knife. (Photos: a, P. Kuhry; b, T. R. Walker).

33 2.3. Lichen biodiversity determinations

The purpose of this lichen biodiversity study was to determine differences in the lichen flora and in the percentage cover on trunks of Picea obovata and in selected sample plots in the tundra to explore the extent to which lichens serve as indicators of air purity.

2.3.1. Taiga sampling sites

Nine maturespruce trees (Picea obovata) were selectedbased on accessibility of trunks and representativenature of the standfrom eachforested study site: Ukhta area(F I j), Belaya Kedva river (F2,), Svetly Vuktyl (F5j) and Maly Patok (F6,). Treeswere selectedý: 100 m apart. An estimateof abundanceand cover of eachlichen specieswas madeon trunks and branches,upto a height of 1.7 m. Many studieshave usedestimates of abundanceof epiphytes(McCune, 1990;Halonen et aL, 1991;Aamlid and Venn, 1993).Estimates were made accordingto the scaleused by Kauppi and Halonen (1992): 7= >50%, 6= 26- 50%, 5= 11-25%, 4= 3-10%, 3= poor cover, < 3%, 2= little, many specimens,but not constituting any real cover, I= extremely little, only one or two specimensper trunk (Figure 2.6.a). After sometraining this scaleproved easyand rapid to use.All the macrolichenand crustoselichen specieswere identified in the field accordingto Dobson(1979); Moberg and Holmasen (1982); Goward et aL (1994); McCune and Geiser(1997). Wherethis was not possible,unidentified specimenswere collected and returnedto the Institute of Biology, Komi ScienceCentre, Syktyvkar and identifications madeby Tatyana Prystinaand Olga Lavrinenko.

2.3.2. Tundra sampling sites

Five quadrats (2 x2 m), separated by > 100 m, were placed subjectively in lichen rich sub-sites which were dominated by dwarf birch (Betula nana) at each of the tundra study sites: Ortina river (F3j), Neruta river (F4r), Upper Kolva (F7j) and Moreyu river (F80. The number and percentage cover of

34 epiphytic and epigeal lichen species were scored on Kauppi and Halonen's (1992) 1-7 point scale as above (Figure 2.6.b).

(a)

(b)

Figure 2.6. (a) Biodiversity determination on the trunk and branches of Picea obovata at Maly Patok, F6,. (b) Biodiversity identifications in a Befula nana dominated heath tundra site at Upper Kolva, F7i. (Photos: P. D. Crittenden).

35 2.4. Chemical analysis of snow

Thawed snow samples(110 m.L) were filtered through 0.2 prn cellulose acetate membranefilters (SartoriusAG), which had beenpreviously washedin 3 changesof DI water and not allowed to dry before use (Crittenden, 1983).The first 10 mL of filtrate was allowed to run to wasteand the subsequent100 mL was collected into two 50 mL metal-free,polypropylene centrifuge tubes (Elkay Products,Inc., Shrewsbury,MA, USA).

2.4.1. Anion analysis of snow

Anions (S04 2-,N03- and C I) were detipnnined by means of ion chromatography using a Dionex DX 500 ion chromatograph fitted with a trace anion concentrator column (TAC-LP 1). Confirmatory measurements of N03' were made by HPLC using 5 ttm amino LichrosorbID as separator in a 250 nun long x 4.6 mm. internal diameter column. The mobile phase (0.03 M KH2PO4 at pH 5) flowed at a rate of I mL. min7l and ion detection was by UV absorption at 214 run (Kmtos Spectroflow-0 757 Absorbance Detector) (Crittenden, 1998). 2- Sea salt sulphate was estimated using the SO4 : Ne molar ratio for seawater (0.0607), assuming that all Ne was of marine origin (Piccardi et aL, 200 1).

2.4.2. Determination of pH and excess acidity/alkalinity in snow

Frozensnow sampleswere thawed overnight in a refrigerator and 20 mL aliquots were usedfor determinationof pH and excessacidity or alkalinity. Standardprotocols were usedto measurepH (Tyree, 1981; Covington et al., 1983)and initial pH drift was checkedusing a chart recorderREC80, Radiometer,Copenhagen. Hydrogen ion concentrationwas calculatedfrom pH using the Davies equationto estimatethe proton activity coefficient.

For acidity or alkalinity determinationsa Gran titration methodwas used accordingto the method of Legrandet aL (1982). A researchgrade Orion 81

36 62scelectrode was usedwith a RadiometerpH meter, (PHM82). Titrant delivery was via an autoburette,(Radiometer, ABU80) capableof delivery to an accuracyof ± 0.001 mL. To eliminate samplecontamination from laboratory NH3 and C02, the headspaceof the titration vesselwas continually flushed with N2; carewas taken to avoid bubbling N2 directly into the filtered snowmelt.The samplewas stirred using a Teflon coatedstirring rod built into the titration assembly.A thermostaticallycontrolled water bath (Grant; ± 0.5 *Q was usedto maintain the titration solution at a constaýttemperature (24 *C) by circulating water aroundthe titration vesselin an enclosingcoil of plastic tubing. Test samplesrun without temperaturecontrol showedlittle difference to thosewith temperaturecontrol. All sampleswere storedin a test tube rack within the water bath to ensurethat they had reachedconstant temperature beforethe titration began.Adjustable micropipettes(Finnpipettes and Gilson) and pre-cleanedaccuvettes were used for dispensingsolutions.

The acid titrant (1.00 x 10-3M HCI) was preparedby diluting a sampleof HCI (Analar, FischerChemicals, UK) stock solution with double-DI water. The samewater was usedto wash the electrode,stiffer and the glassmicroburette tip betweeneach sample run. A small quantity of acid titrant was flushed out of the burettebefore eachtitration to avoid dilution from washingthe delivery tip with DI water. The internal filling solution of the electrode(a saturated solution of KCI) was also usedas the ionic strengthadjuster (ISA) to control ionic strengthin all Gran titration samples.Possible contamination from the ISA was checkedby addingvolumes of 0.5,1.0 and 1.5 mL ISA to three DI water blanks. All three blanks showedno difference in total acidity and thus any backgroundacidity in theseblank sampleswas attributedto laboratory DI water and not contaminantin the ISA. The electrodewas calibratedusing pH buffers of 4.00 and 7.00. Calibration was always followed by two blank titrations using DI water to ensurethat the electrodehad stabilisedand remove residualbuffer from the electrodesurface. At the end of eachset of titrations the electrodewas checkedfor drift by re-calibrating.

37 A 20 mL aliquot of thawed, filtered snow sample at 24 'C was pipetted into a sample container and 0.5 mL of ISA (saturated KCI solution) added. The sample container was then placed within the thermostatted water jacket and connected to the titration assembly. An initial pH measurement was taken after the electrode stabilised and temperature equilibrium was reached (usually less than I minute). The temperature of the sample was checked after titration, using a thermometer, and did not vary. An initial volume of titrant (0.00 1M HCI) was added until a pH of 4.75 was reached (unless the sample was already < pH 4.75). At this pH atmospheric C02 no longer contributes significantly to acidity. Following the Gran titration method of Legrand et al. (1982), the pH of the meltwater sample was gradually decreasedby adding around six successive aliquots of dilute acid titrant. An example of which is shown in Table 2.3 for an alkaline sample (sample 3.4.3.6. ) collected at site 3.4 along transect 3, south of Inta. The time interval between two successive additions was between 10- 15 s. A linear regression of the 6 titration data was obtained and extrapolated to zero titrant (i. e. to intercept the 'y'-axis) to determine the value of acidity/alkalinity (Figure 2.7). Approximately 6-10 samples h7l were measured. Determination of the acidity/alkalinity is described in the following section.

2.43. 'Gran plot determination of strong acid concentration in filtered thawed snow

Following Legrand. et al. (1982), the concentration (normality) of strong acid in the sample (Co) was derived from Equation 2.1 (see Table 2.4.; Figure 2.7).

Intercept ) co =Y- (F (2.1) Slope -CVo where: C, = Concentration(Normality) of strong acid in sample V. = Volume of water sampletitrated C= Concentration(Normality) of strong acid in titrant

38 This relationshipis derived from an interpretationof the Nernst equationand the variation in measuredelectrode potential (E) with addition of strongacid. Concentrationof strong acid (CA)at eachtitration point is (Equation2.2):

covo + CV CA -: (2.2) Vo +V where: CA = Concentrationof strong acid during the courseof the titration V= Volume of titrant added

From equation(2.2), the Nernst equationmay be written as (Equation 2.3):

In (10) RT CoVo+CV]. ln(IO)RT E=Ecp+ log log(,v) + Ej (2.3) FL vo+v F where: E= Measuredpotential (mV) E,, = Potential for proton activity of unity - the 'standard' potential Ej = The liquid junction potential I= Activity coefficient for the (H) ion R= Gasconstant T= Thermodynamictemperature F= Faradayconstant

For conveniencewe can define the slopeof the Nernst relation (S) as Equation 2.4): (2.4) In (10) RT F

Dividing Equation2.3 through by S, then removing logs and multiplying through by (Vo + V) gives (Equation2.5):

(EO+Ej )Y(COV (VO+V)10(EIS)=Io( S O+CV) (2.5)

Linear regressiontherefore gives (Equation2.6): (2.6) y=(VO+V)10(EIS); X=V;

Slope io(EO+EJIS)c; r; lo(EO+EJIS)C Vy Y- axis Intercept =00.

39 Measurementsof pH were convertedto values of potential, E (mV), in order to apply Equation2.1. The value of the Nernst slopevaried for eachgranplot, but was approximately58-59 mV per pH unit. (2.7) ln(IO)RT E=Eo+ pH F

We usedthe measuredE values at pH 7 (E = 0) and pH 4 to derive the slope of the Nernst equation.

Table 2.4. Example output from site 3.4 (sample3.4.3.6. )

Cumulative PH E (mV) Total VOL Gran G-Plot C-Plot Titrant (V) measured calculated (V+Vo+Visa) Parameter Slope Intercept added (ml) (ml) (y)

0.873 4.75 131.250 21373 3800.n 8409.44 -3597.409 1.000 4.65 137.083 21.500 4813.25 1.250 4.50 145.833 21.750 6877.95 1-500 4-39 152.250 22.000 8962.37 2.002 4.23 161.583 22.502 13250.16 2.500 4.12 168.000 23.000 17447.28

Sample Nernst Sample ISA Cone. Milli-volts Cone snow acid Identification Slope Volume (Vo) Volume (ml) Titrant (M) At PH 4.00 CO(M) - 1.0 10-3 3436 58.333 20 0.5 x 175 -2.14 x 10-5

Start PH 6.36

40 20000 Gran plot titration data

15000

10000 C= 8409.4xV 2= Rý = 0.990.9999 5000

Co 0- -3597.4 2 3 G-plot intercept' ý, -5000 Volume of Titrant V, (ml)

Figure 2.7. An exampleof a Gran Plot output for site 3.4 (Table 2.4; sample number3.4.3.6. ), showing alkaline snow.

2.4.4. Elemental analysis of snow

Analysis of trace metalswas conductedon acidified liquid samplesby inductively coupledplasma mass spectroscopy (ICP-MS) at the University of, Lancasterby Dr. Hao Zhang. The trace metalsAg, Al, As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sr and Zri were determinedon pooled samples.These were composedof equal aliquots of 166 pL of filtered thawed snow taken from each of the six replicate samplesfrom eachsite to make a combinedsample volume of I mL. Filtered solutionswere acidified with ultrapure HN03 to give 2% HN03 prior to analysisof trace elementsby ICP-MS. Cations(Ne, C2+, K) were determinedby flame emissionspectrometry (FES) with appropriate 1). additionsof CsCl as ionisation suppressant(1000 mg Cs 1:

41 2.4.5. Elemental analysis of suspended solids in snow

Celluloseacetate membrane filters usedto filter the thawed snow sampleswere oven dried at 80 T overnight in glasspetri-dishes and suspendedsolids were determinedgravimetrically. The membranefilters from the Vorkuta and Usinsk transectswere retainedand photographedprior to digestion. Six cellulose acetatemembrane filters from eachsub-site were combinedand digested togetherin 10 mL of conc. HN03 (Aristar, FischerChemicals, UK) (Reimann et al, 1996).The digest was filtered through a WhatmanNo. 42 ashlessfilter and madeup to 50 mL using ultra-pure water giving a final matrix of approximately I% HN03. Elementalanalysis (Al, Ba, Ca, Cd, Cu, K, Mg, Mn, Ni, Pb, Sr and Zn) was undertakenby graphitefurnace atomic absorption spectroscopy(GF-AAS) and flame atomic absorptionspectroscopy (F-AAS); concentrationswere recalculatedin relation to the volume of filtered meltwater to allow direct comparisonwith the data for solute concentrations(Reimanii et aL, 1996).

2.5. Chemical analysis of lichens

2.5.1. Preparation of material

Lichens were rehydratedovernight by exposureto water-saturatedair (over DI water in a dessicator)at 4 'C, then fully saturatedby sprayingtwice with DI water. The rehydratedmaterial was cleanedof extraneousdebris using forceps. The thalli were then cut horizontally (i. e. at right anglesto the main axis of the thallus) at 5,40 and 50 mm from the apex. The horizontal strata0-5 mm (apices)and 40-50 mm (thallus basewith respectto the apex) were retainedfor analysisand oven dried at 80 I'C overnight. The analysesperformed on each speciesis given in Table 3.1 (Chapter3) and Table 5.1 (Chapter5)

42 2.5.2. Total [Cal, [K], [Mg], [Znl and IPbl concentrations in lichen tissue

Approximately 100mg of dried apical tissuewas digestedto drynessin I mL of concentratedHN03 (Aristar, Fisher Chemicals,TJK) at 175 'C in 16 x 1.5 cm digestiontubes. The residuewas dissolvedin 10 mL IM HN03 and appropriatequantities of ionisation suppressantand releasingagent (CSC12, LaC12)added. Concentrations of [Zn]fichenwere determinedon the top 5 mm of apical.thalli for Cladonla stellaris and C rangiferina along transects2/3 through Inta and for C arbusculd along transectI through Vorkuta (see Chapter3). Concentrationsof [Pb]lichenwere determinedon the top 5 mm of apical thalli for Cladonia stellaris and C arbuscula and Flavocetraria cucullata (seeChapter 5). Magnesium,Pb and Zn were determinedby GF- AAS and Ca and K by FES.

2.5.3. Total nitrogen concentration (INIih,. ) in lichen thalli

Total N concentration was measured in both apical (0-5 mm) and basal (40-50 from blade. Total [N]jjhe, mm) tissue. These strata were cut thalli using a razor ý was determined following the Kjeldahl digestion and distillation method of Bremmer and Breitenbeck (1983). Approximately 100 mg of dried apical dried digested in 3 thallus or 300 - 400 mg of basal thallus was mL of concentrated H2S04 (Aristar, Merck UK Ltd) containing 1.0 g K2SO4,0.1 g CUS04.5H20,0.01 & Se and 3 anti-bumping granules. The digestion was performed in 100 mL (30 x3 cm) digestion tubes, heated at 375 'C for 3 hours in an aluminiurn block digestor [Grant Instruments Ltd, Cambridge] (Bremmer, 1965; Bremmer and Breitenbeck, 1983). The cooled digest was diluted with 15 mL of DI water, then allowed to cool to room temperature. The steam distillation apparatus used to collect NH3 from the digest is shown in Figure 2.8.

43 Steam bypass tube I Brace +- team

plwh tubitc

Water out

Stopcock

To waste Distilled water reservoir

Digestion tube containg Water in dilated digest and 10 M NaOH -Needle valve To waste Glass Anti-blumping rods Cramfles Distilledwater Distillate

Electric heating mantle supports

Figure 2.8. Steam distillation apparatus (after Bremmer and Breitenbeck, 1983).

Ammonium N was removed from the kjeldahl digests by steam distillation of

NH3 into boric acid indicator solution and determined by titration using an

autotitrator (665 Dosimat, Metrohm, Switzerland) with 0.01 N 112SO40 mL of

0.0 1N H2SO4 = 0.14 mg of ammonium N). The colour change at the end point

is from green to pink.

2.6. Soil analysis

Frozen soil samples were allowed to thaw overnight at room temperature and a in representative sub-sample (5 - 10 g) was oven dried (105 T) acid washed

44 silica dishes.Samples were ashedin a muffle furnaceat 450 T overnight, allowed to cool in a dessicatorand weighed for loss on ignition (LOI). A sub- sample(1 g) of the soil ashwas digestedin 10 mL of concentratedHN03 (Aristar, Ficher ChemicalsUK). The digest residue(-I mL) was diluted and filtered through WhatmanNo. 42 ashlessfilters then madeup to 100mL using ultra-purewater to give a final matrix of I% HN03. Analysis of Ba, Ca, Cu, K, Mg, Mn, Na, Ni, Pb, Sr and Zn was undertakenusing GF-AAS and F-AAS. Calcium and K were not analysedfor the Usa,basin study describedin Chapter 4. All soil sampleswere subsequentlyincinerated in accordancewith the terms of the MAFF (DEFRA) licence for soil importation (licence number PHL18/2351[08/97].

Soil pH was measuredon moist soil samples,suspended in DI water at a solid solution ratio of approximately I: 2.5 following equilibration for I hour. Drift in pH was recordedto determinewhen equilibrium was reached.

2.7. Elemental deposition rates

Elementalconcentrations in snow (including thoseassociated with particulates) and soil were consideredtogetherin an attemptto explain the soil metal loadingsfound aroundemission sources in relation to current depositionrates. Sitesaffected by depositionwere consideredin relation to pristine sites.The time in yearsrequired to accumulateexcess element concentration in soil (Td) was determinedby equation2.8

(Cd Cp) Sd - X Td -'ý (2.8) Ad where:

Td = Time required to accumulate excess elemental concentration (y)

Cd= Concentrationof elementin soil within depositionarea (g kg").

Cp - Concentration of element in soil at background (pristine) site (g kg-1).

45 Sdý Mass of soil in 5 cm slice in deposition area (kg in-2).

Ad = Current element deposition rate (g m-2 y-1).

This was estimatedby combining measuredelemental concentrations in thawed snow and filter residues(g m-3liquid) then multiplying by the mean annualprecipitation (m y") for eachtown.

This approachassumes that:

the lowest concentrations of elements found in soil (Cp) occur at sites at the transect extremes, furthest away from the emission sources (e.g.

TransectI through Vorkuta - sites 1.1 and 1.6; Transects2/3 through Inta -sites 2.1 and 3.1);

(ii) highestconcentrations (Cd) occur closeto emissionsources (e. g. Vorkuta: sites 1.3 and 1.4, Inta: sites 2.5 and 3.5);

(iii) all historical depositionis containedwithin the top 5 CM Of Soil (Sd);

the meanannual precipitation is the sameat all sites on a transect.

2.8. Statistical methods

Genstatand Minitab,were usedto perform standardstatistical analyses (ANOVA, correlation analysisand linear regression).The extent of pollution at sitesnearest to towns was assessedby comparingchemical data from these siteswith thosefrom sitesat the extremitiesof transectsusing ANOVA with an appropriatecontrast (Chapter 3). Tukey's testswere usedfor pairwise comparisonof lichen biodiversity ANOVA-analysis.

46 CHAPTER 3. REGIONAL VARIATION IN THE CHEMICAL COMPOSITION OF WINTER SNOWPACK AND TERRICOLOUS LICHENS IN RELATION TO SOURCES OF ACID EMISSIONS IN THE USA RIVER BASIN, NORTHEASTERN EUROPEAN RUSSIA

3.1. Introduction

This Chapter reports on the geographical variation in the chemistry of winter snowpack and terricolous mat-forming lichens in the Usa basin, north-east European Russia. The research was a contribution to TUNDRA (TLJNdra Degradation in the Russian Arctic), an interdisciplinary research project examining potential effects of environmental change in the Russian Arctic. As such, a wider objective of the work was to assessthe likely extent to which the response of Arctic ecosystems to 'climate forcing' in this region might be modified by pollution. It also provided an opportunity to further evaluate the use of terricolous lichens as indicators of nitrogen and acid deposition. The objective was to provide information on the distribution and magnitude of acid deposition (and alkaline) resulting from industrial activity in the Usa river basin in the Komi Republic. This region has an area of 93,000 kmý and spans the boreal forest-Arctic tundra ecotone (Figure 2.1). It has already been identified as a significant source of acid emissions (Ottar et aL, 1984; Ottar, 1989; Nenonen, 199 1; Vinogradova, 2000) mainly as a result of coal fired power stations in the towns of Vorkuta and Inta and a gas-fired power station in Usinsk. Transects were established through the three principal towns of Vorkuta (67*30'N, 64*05'E; Transect 1), Inta (66*03'N, 60'10'E; Transects 2 and 3), and Usinsk (66101'N, 57'30'E; Transect 4) (Figure 2.1, Table 2.1).

Reported here is an assessmentof the extent of acid, alkaline and N deposition around Vorkuta, Inta and Usinsk as indicated by the spatial variation in the chemicalcomposition of winter snowpackand terricolous mat-forming lichens. In part, thesedata will serveas a baselineagainst which contaminationthat might result from future industrial developmentof the area be can measured.The variablesmeasured in snowpackwere: anions(SO 429 N03' and C I) by ion chromatographyand HPLC; cations(Ne, Ca2+,K) by

47 flame emissionspectrophotometry (FES); pH following standardprotocols. The variablesmeasured in lichens were: total N, determinedby Kjeldahl. digestionand distillation; cations(Mg+ by F-AAS; Ca2+and Ký by FES); Zn by F-AAS.

The chemistryof snowpackand terricolous lichens was modified locally in the vicinity of the industrial towns, and also on a regional scalewith respectto latitude. The probableunderlying causalfactors are discussed.

3.2. Materials and methods

3.2.1. Study area and sampling regime

The study sites are locatedin the Usa river basin betweenlatitudes 64' and 68' N in the Komi Republic (eastEuropean Russia)(Figure 2.1, Chapter2). Transectswere establishedthrough the three principal towns of Vorkuta, Inta and Usinsk. On eachTransect between 4-6 samplingsites were selectedat roughly logarithmic intervals with respectto the town centres(Figure 2.1, Table 2.1). At eachsite three sub-siteswere again selected,500 - 1000m apart,at which 6 replicate samplesof snow and 6 of lichen (seebelow) were collectedat distances10 - 20 m apart in open areassubject to minimal tree canopyeffects; thesewere usually inter-treepositions in open forest, or in opentundra. Most siteswere in wildernessareas remote from roads.Note that snow sampleswere not collectedat the most extremesites on transects2/3 (i. e. 2.1 and 3.1) and lichens were not collectedat site 2.4.

3.2.2. Snow and lichen sampling

For further details of snow collection methods see Chapter 2. At least one speciesof terricolous mat-forming lichen of the generaCladonia [C. stellaris (Opiz) Pouzar and Vezda, C. rangiferina or C. arbuscula (Wallr. ) Flot. ] or Flavocetraria [F. cucullata (Bellardi) Kdmefelt and Thell] was collected at sub-sites during the snow-free season.These species were chosen to provide

48 biomarkersfor atmosphericdeposition and becauseof their ubiquity and abundancein forest tundra. SeeChapter 2 for details of collection.

3.2.3. Lichen biomarkers for nitrogen and acid deposition

The nitrogen concentration ([N]) in lichens is partially dependent on the amount of income of dry and wet deposited N (Kubin, 1990; Sochting, 1990; Bruteig, 1993b; Hyvannen and Crittenden, 1998a). Hyvarinen and Crittenden (I 998a) demonstrated a strong relationship between N deposition and [N] in the terricolous mat-forming lichen Cladoniaportentosa. Mat-forming lichens include species of Cladonia, Cetraria, Flavocetraria and Alectoria, genera that are widespread and locally abundant in boreal-Arctic heathlands and open woodlands. Such species grow vertically upwards at the apices, and senesce and produce litter (necromass) at their bases (Crittenden, 1991). A gradient of decreasing [N] values exists from the thallus apices towards the bases. Hyvdrinen and Crittenden (1998a) found that [N] in the apical 5mm. of C portentosa ([N]ve,, ) and in a deeper stratum 35 - 50 mm from the apices ([Nlbm) were both significantly positively correlated, and the concentration [N]. [Mbase N deposition. Hyvarinen, ratio p,,,: was negatively correlated, with 1997; Hyvarmen and Crittenden (1996) also showed that the concentration ratio of K+: Me+ in the apices (([W]: [Mej)ýVe. ) of C portentosa was positively correlated with precipitation acidity. Accordingly, concentrations of N, Ký, and divalent cations (Mg2-" and C2") in thallus apices, and [N] in the bases, were measured in lichens sampled in the present work.

Hyvarmenand Crittenden(1998a) consider that coupling betweenthe chemicalcomposition of mat-forming terricolous lichens and that of atmosphericdeposits may be particularly close for three reasons.Mats typically develop in open situationsand interceptprecipitation directly, and hencerelationships between lichen chemistry and atmosphericinputs are not compoundedby nutrient exchangesbetween rainfall (or snow meltwater) and overlying vascularplant canopies(cf. Farmeret aL, 1991 ab; Sochting, 1995). Accumulation, below well-establishedlichen mats,of copiousquantities of structurally intact necromassmay partially isolate living thalli from the

49 chemical influence of the soil beneath (see Crittenden, 1991; Hyvdfinen and Crittenden, 1996). Lichen mats are efficient scavengers of inorganic N and P in precipitation (Crittenden, 1983,1989; Hyvdfinen and Crittenden, 1998b, c) so that mats several cm. deep become very strong sinks for ions such as N03-, 3-. NW, and PO4

3.2.4. Chemical analysis of snow

Full details of snow analysis are presented in Chapter 2 (2.4). Thawed snow samples (I 10 ml) were filtered through 0.2 gm cellulose acetate membrane

filters, which had been previously washed in 3 changes of deionised water and 2-, not allowed to dry before use (Crittenden, 1983). Anions (SO4 NO.3' and C I" were analysedby ion chromatographyand confirmatory measurementsof N03- were madeby HPLC. Cations(Ne, Ca", K+) were determinedby flame emissionspectrometry (FES) with appropriateadditions of CsC1 (1000 mg Cs 1) 1: as ionisation suppressant.Sea salt sulphatewas estimatedusing the SO42: Na+molar ratio for seawater(0.0607) and assumingthat all Ne was of marine origin. Snow meltwaterpH was determinedusing standardprotocols (Tyree, 1981;Covington et aL, 1983).Hydrogen ion concentrationwas calculated from pH using the Davies equationto estimatethe proton activity coefficient. Acidity or alkalinity was measuredby Granplot acid titrations (methodsand datapresented in Chapter2 and Chapter4).

3.2.5. Chemical analysis of lichens

Full details of lichen analysisare presentedin Chapter2 (2.5). Two horizontal stratawere cut with a razor blade from eachthallus: the apical 5 mm (analysed for total N and cations)and the stratumbetween 40 - 50 mm from the apices (analysedfor total N). Magnesiumand Zn was measuredby flame atomic absorptionspectrophotometry (F-AAS); Ca2+and Ký by FES. Zinc was selectedas an additional analytebecause it was one of severaltrace metals found to contaminatesnow and soils locally in the survey region (Walker et aL, 2003). Total nitrogen concentrationwas determinedby Kjeldahl digestion

50 and distillation following the methodsof Bremmer (1965) and Bremmer and Breitenbeck(1983).

3.2.6. Data analysis

Genstatand Minitab were usedto perform standardstatistical analyses (ANOVA, correlationanalysis and linear regression).The extent of pollution at sites nearestto towns was assessedby using ANOVA with an appropriate contrastby comparingchemical data from sites closeto towns with thosefrom sitesat the extremitiesof transects.

3.3. Results

3.3.1. Snow chemistry

The depth of the snow pits rangedbetween 0.4 - 3.0 m and evidenceof significant thawing, such as horizontal ice layers within the profiles, was not observed.However, at most siteson the Vorkuta Transect,and at sites closeto Inta, dark horizontal bandswere observedin many of the snow profiles.

Figure 3.1 ab and c gives the pH and concentrations of N03' and S042- in snow 21snow, samples (subsequently referred to as pHsnow,[N03"Isnow and [S04 respectively, with logical extensions of this fonnat to other ions) collected along the Transects through Vorkuta, Inta and Usinsk (Transects 1,2/3 and 4, respectively). Values recorded at the extremities of the Transects are broadly baseline [N031., [SO similar, suggesting that the pH,,,ow, and 42],. values 1, across the Usa basin were c. 4.9,9.2 and 5.3 pmol 1: respectively. 'Illese

approximate baseline values appear to be representative for each of the three Transects even though data for Transects 2 and 3 (Inta) were collected in the year prior to those for Transects I and 4 (Vorkuta and Usinsk). Note that site 4.6 sampled in 1999, is located near to site 2.3 (approx. 20 km apart) which in 1998, [N03'1,. [SO was sampled and that although )wand 42],,,o,, values at these two sites are broadly comparable, concentrations of both ions are higher

51 at site 4.6. Acidity or alkalinity was also measuredin all snow samplesby Granplot acid titrations and the data are presentedelsewhere (Chapter 4; Walker et al., 2003).

Values [S04 2-]s. in of pHs.., and 0, were markedly elevated the vicinities of Vorkuta and Inta; in each case the differences between the two sites closest to the towns and the two remotest sites were significant at the P<0.001 level (one-way ANOVA)(Figure 3. La and 3. Lb). These perturbations were not detectable beyond a distance of c. 25 km from Inta (Figure 3. Lb) whereas around Vorkuta there was evidence of contamination even at the extremities of the Transect (sites 1.1 and 1.6) providing some evidence of spatially more Vorkuta. Changes in [S04 21 extensive pollution around pHn.,, and snowvalues along these Transects were positively correlated (r = 0.822, P<0.00 1, n= 144; r=0.542, P<0.001, n= 108 [for Inta and Vorkuta, respectively]). By [S04 2-]Snow in contrast, values of pH,,,,,w and were not modified significantly the environs of Usinsk (Figure 3. Lc), and [N03- ]snowwas invariant in the vicinity of any of the three towns. Nitrate concentrations measured by ion chromatography and by HPLC were in very close agreement (r = 0.98, P< 0.001, n= 360) (Figure 3.2).

Concentrationsof organicN were also determinedin a small subsetof snow samplesfrom TransectsI and 4 by J.N. Cape(Centre for Ecology and Hydrology, Edinburgh)using an ANTEK model 8060 N-specific detectorfor HPLC. Molar concentrations of organic N were broadly similar to those of to Vorkuta [organic N], nitrate, except at sites close where n, " values were greater than [N03"Isn. by a factor of 2 or 3 varying spatially in a manner similar to that Of [SO 42]snow values.

52 Sitenumber 1.1 1.2 1.3 1.4 1.5 1.6 7.5 II

7.0 - 6.5 6.0 5.5 5.0 :- 4.5 15

10 =L -f 5

0 25

20

15

10

EA

05 Vorkuta L--jrn 0 0 20 40 60 80 100

Distance(km)

[N031snowq [SO 2-] Figure 3.1.a. Variation in 4 and pH,,,.,, on TransectI during Spring 1999.Plotted'values are means:k I SE (n = 18).

53 Site number

2.2 2.3 2.4 3.4 3.3 3.2 7.5

7.0 6.5 6.0 5.5 5.0 4.5 15

10 - S

S 5

0 I I I I 25

20 .Iinta

15

10 eq 5

50 100 150 200 Distance(km)

Figure 3.1. b. Variation [NOflsnow) [S04 2], Transects 2/3 n.,, and pHsnowon during Spring 1998. Plotted values are means± I SE (n = 18).

54 Site number

4.1 4.2 4.3 4.4 4.5 4.6 7.5 7.0 6.5

6.0 5.5 5.0

4.5 15 I

10 -

5

0 25 sw 1. NE 20 Usmsk

15

10

5

0 0 25 50 75 100 125 Distance(km)

Figure 3.1. Variation in [NO31..,,, [SO 2-]snow Transect 4 c. 4 and pHs,,.w on during Spring 1999. Plotted values are means ±I SE (n = 18).

55 30

S

14 0 20 S E =L S S. v0

0 10 ;4. P-4u

n I 0 10 20 30

HPLC INOAsnow (Pmol L")

Figure 3.2. Agreementbetween [N031silow measured by ion chromatography and HPLC (r = 0.98, P<0.001, n= 360).

More generalinformation on the sensitivity of snow pack chemistry,and the analytical methodsemployed, as tools to map pollution in this region is provided by data for Na and Cl'concentrations (Figure 3.3.ab, c). Mean [Naj,. (measuredby AAS) [C js,, (measuredby ion valuesof O,, and I o,, chromatography)along the Inta.Transects (Figure 3.3.b) are both strongly relatedto latitude, usedhere as an analogueto distancefrom the coast 12 ([Naj,. o,,: r2 = 0.76, P<0.005, n=8; [CII..: = 0.75, P<0.01, n= 8).

56 Site number 1.3 1.4 10

8 Vorkuta

6

4

2

0 0 50 100 L. Z .--3.4 24 1 (b) 2.15 Inta (3.5) 18

12

"0

6 EC5,

0 0 100 200 4.1 4.2 4. J 4.4 4.3 4.0 6

4

2 Usinsk sw NE n IIII 0 so 100

Distance (km)

Figure 3.3. Variation in [Na'Isno, (o) [CI-],,,, (e) Transects 1, (a); and ), on 2/3, (b) and 4, (c). Plotted values are meansl I SE (n = 18).

57 in ], Transect4 Therewas no apparentvariation [C I n,,.,,along the through Usinsk (Figure 3.3.c). Intra-site variation in absolutevalues of [Nal, n,,,,and [C 1 was most marked at the northernmost spring sampling site (2.2) in ([Nal: [C I 1),.. low whereas variation the ratio wwas with values approaching to the sea salt molar ratio of 0.85 (Figures 3.4 and 3.5b).

40

r 0.997

30 -

0 e =L 20 -

4"m 10 - 0@*

0 0 10 20 30 40

ICI-Isnow (ýimol L' I)

Figure 3.4. [Nal.,,. and [Cll,,,., at Lake Tumbulovaty, (site 2.2), the northernmosttundra site on Transect2 during spring 1998.The solid line indicatesthe molar ratio [Naj: [Clj in seasalt (0.85).

Variation in the absoluteconcentrations but stability in the ratio could be explainedby the redistribution of snow by wind at this exposedtundra locality (site 2.2). The ratio was most variable at sites closeto Inta (Figure 3.5b) while in the Vorkuta region there was pronouncedintra and inter site variation in the ratio on the whole length of the Transect(Figure 3.3a and 3.5a) suggesting [Naj.. [C that the w and I ],,,. wvalues were modified by pollution at all sites.

58 Site number 1.2 1.3 1.4 1.5 2.0

1.5

1.0 ------

0.5

0.0 0 20 40 60 80 100 120 2.3 2.4 3.4 3.3 3.2 2.0 I112.1 53 1 .51 (b)

1.5

1.0 ------IIK xZ 0.5

nn 40 80 120 160 200 240 Distance(km)

Figure 3.5. Variation in ([Naj: [Clj),,,,, on TransectI (a) and Transect2/3 (b). Broken lines indicate the molar ratio [Naý]:[Cl] in seasalt (0.85). Plotted valuesare means±I SE (n = 18).

59 Site number

2.1 2.2 2.3 2.4 3.43.3 3.2 3.1 If+

Inta II 1 0 100 200 300 Distance (km)

3.6. 2 3 in [nssSO42], deposition Figurc a. Variation on Transects wid n,,,,, at sitesinfluenced by 'local' pollution effects (9) and at sitesmore remotefrom local pollution effects (o). Plotted valuesare means±I SE (n = 18).

When non-seasalt sulphate(nSSS04 2) was calculatedfor siteson the Inta there fa in [nssS042] transects was someevidence o, southto north trend .w at 'background' sites remotefrom Inta, althoughthis trend was not statistically significant (Figure 3.6.a).

60 Site number

2.2 2.3 3.3 3.2 40 I I I '(b)

30

10 20

I

IA I I Am 68 67 66 65 Latitude (N)

2- Figure 3.6. b. Variation on Transects 2 and 3 in total winter nsSS04 deposition at sites beyond the zone of 'local' pollution. Plotted values are means ±I SE (n = 18).

However, estimatesof winter depositionof nssSO42',calculated as the product of [nssS042],,,, and modelledprecipitation values from van der Linden and Christensen(in press), were negativelyrelated to latitude (Figure 3.6b) (regressionanalysis after I /x2transformation: r2 = 0.91, P<0.05, n= 4). Concentrationsof Ký and Ca2+in Vorkuta snow sampleswere also determined (Figure 3.7) in order to understandthe basisof observedchanges in lichen chemistrynear the town. Both elementswere presentin higher concentrations in snow pack closeto the town.

61 Site number

11211 31 150 141151162.5 E

2.0 41 - 100

1.5 ELI - 1

P-" 140 50 u - 1.0 Vorkuta III10.5 0 0 20 40 60 80 100 120 Distance(km)

Figure 3.7. Variation in [Ca+],,,.,,(e) and (0) on Transect1. Plotted valuesare means±I SE (n = 18).

Table 3.1. Summaryof lichen speciescollected and elementsanalysed on four Transectsin the Usa,basin.

TransectNo. Analysis

[Nlapex [NIbase [Ca 2,1 [K] [Mj2, r-1 [Zi? "']

Cladonia stellaris I+ 2/3 ++++++ 4+

" rangiferina 2/3 -++++ " arbuscula I+++++ Flavocetraria cucullata I+

62 3.3.2. Lichen chemistry

The most completedata setsfor lichen chemistrywere obtainedfor Cladonia stellaris and C rangiferina on the Inta and Usinsk Transects,and for C arbusculd and Flavocetraria cucullata on the Vorkuta Transect(Table 3.1). Mat-forming lichen cover was generallypoor in the Vorkuta region due to heavy grazing and trampling by reindeer;for example,C stellaris was largely absentat most sites.

Nitrogen concentration in the apices ([N]ape,,) of C stellaris decreased northwards Transects 2/3 from a value of 0.57 ± 0.01 mmol 9" at site 3.2 in the South to 0.43 ± 0.01 mmol g" at site 2.1 in the North (Figure 3.8b). The relationship between [N].. and latitude being statistically significant (r2 = 0.68, P<0.01, n= 9). There was no relationship between latitude and either [Nlbase(?ý2 = 0.39, P<0.1, n= 9) orthe ratio Mvex: Mbasc (r2= 0.148, P> 1.0, n= 9) (Figure 3.9). Despite the clear spatial variation in [N]ap,,.,there was little evidence of N contamination ([N03'lsnc)wvalues, see Figure 3. Lb) from the town. Values of [N],,,, for C stellaris collected along transect 4 were higher than those in the Inta region and showed marked inter-site variation that did not accord with any clear spatial trend (Figure 3.8c). Again, where Transects 2 and 4 intersect, near to sites 2.3 and 4.6 (Figure 2.1, Chapter 2), values of [Mape. were in good agreement (0.55 and 0.57 mmol g"', Values [N]. in C. F. Transect I respectively). of pe. arbusculd and cucullata on were positively correlated (rý= 0.863, P< 0.02, n= 6) and are significantly (P < 0.001) elevated in the vicinity of the town (Figure 3.8a) although, as in the Inta area, there was no evidence of a comparable trend in [N031snow(Figure 3.1.a).

63 Site number

1.5 0.7 1.1 1.2 1.31.4

0.6

13 0.5

13 Vorkuta

0.4 0 20 40 60 80 100 120

Z. 1 2.2 2.4 2.5 3.4 3.3 3.2 3.1 0.6 s (b) N

-f-I

0.5

Inta

0.4 50 100 150 200 250

4.1 4.5 4.6 0.8 4.2 4.3 4.4 sw NE

0.7

0.6

Usinsk

05 0 25 50 75 100 125 150

Distance (km)

Figure 3.8. Values of [N],,. in Cladonia arbusculd (m), C stellaris (9) and Havocetraria cucullata (o) collected on Transects; 1, (a), 2/3, (b) and 4, (c). Plotted values are means ±I SE (n. = 18).

64 Sampling sites

2.1 2.2 2.3 2.5 3.4 3.3 3.2 3.1 7 3.5

.0

2 0 50 100 150 200 250 Distance(km)

Figure 3.9. The relationshipbetween distance along Transects2 and 3 (latitude) and the ratio [N]apc.:[NIbase (r = 0.148, P>1.0, n= 9).

Zinc was selectedas an additional analytebecause it was one of severaltrace metalsfound to contaminatesnow and soils locally in the surveyregion (Walker 2003). There localiscd in et aL, was elevationof [Zn2j.., ' C arbusculdaround Vorkuta particularly at sites, 1.3 and 1.4 (Figure 3.1O. a). However in [Zn2+],, in C there was no such elevation pc. stellaris aroundInta, but [ZWj,,,,,, in C. stellaris was strongly relatedto latitude (Figure 3.1O. b)(r2 = 0.77, P<0.005, n= 9). Collections of C rangiferina were incompleteat samplingsites aroundInta (Figure 3.1O. b), and there was no apparent relationshipbetween [Zn2j.. and latitude.

65 0.9

0.8

0.7

0.6 Vorl.kuta +.

0.5 0 20 40 60 80 100 120 140 0.4

...... 0.3

0.2

0.1 L 0 50 100 150 200 250

Distance(km)

21Vex Figure 3.10. Variation in [Zn in Cladonia arbuscula (A) along Transect I (a) and C stellaris (0) and C. rangiferina (0) along Transect2/3 (b). Plotted valuesare means±I SE (n = 18).

66 Variation in [Zr?jaje,, in lichens on TransectsI (Figure 3.1La) and 2/3 (Figure 3.1Lb) was strongly correlatedwith [N]ape,,(C arbuscula on Transect 1: r=0.90, P<0.01, n=6; C stellaris on Transects2/3: r=0.91, P<0.001, n= 9).

0.65 (a) TransectI 0.60 -

0.55 tj 0* 0.50

?S0.45rq

0.40 0.52 0.56 0.60 0.64 0.68 0.72 0.76 C arbuscula [ZnlapexOIMOI 9'1)

0.60 ((b)b) TrTransect ct 2/3 0.56

rol) 0.52

0.48

0.44

0.20 0.24 0.28 0.32 C stellaris [Znlapex (PMOI 9-1)

2+ Figure 3.11. Variation in [Zn ]ape,,in lichens on Transects I (a), and 2/3 (b), with [N]ape.(C arbusculd on Transect 1; C stellaris on Transects 2/3).

67 Figures 3.12a, b shows variation in the concentration of the principal cations

in the apices of C. arbuscula and C stellaris collected on Transects I and 2/3,

respectively. The clearest evidence of perturbations in lichen cation content

again was found in the close environs of Vorkuta. Concentrations of Ca2+ and

K% and values of the ratio in the thallus apices were higher, the [Klq..: ([Ca2+]+[Me+]). significantly and ratio pe. was significantly lower, in C arbusculd growing near to the industrial areas, compared to material from the extremities of the Transect (P < 0.00 1). Values [Kl,,,, [Ca2lw,, [K+],,,,,,:[Mg2+]. highly of and and the ratio p,,,were [C21..,, [Kjsnýw (Table 3.2, Figures positively correlated with pHs,,o,,, and 3.7 and 3.12a).A similar degreeof inter-site variation in lichen cation ratios was evident along Transect2/3 through Inta,but it did not appearto be related to proximity to the town or latitude (Figure 3.12b). C rangiferina was also collectedat six siteson Transect2/3 in addition to C stellaris and chemical analysisrevealed broadly similar inter-site variation in cation concentrations but the covariation between the two species was only significant in the case of [Ca2"']apmQKJ,, P<0.10, [Ca2+].,,: ý,, - r=0.610, n=6; r=0.747, P<0.05, n = 6) (Figure 3.12c).

Table 3.2. Bivariate Pearsoncorrelation coefficients (r) betweenchemical characteristicsof the lichen Cladonia arbuscula and snow collectedat siteson Transect1.

[Kjsnow [Calsnow [SO 42]snow pHsnow

[N],,pe. 0.811***t 0.542* 0.841*** 0.671** [Kllichen 0.637** 0.732*** 0.628** 0.798***

[Ca'llichcn 0.655** 0.914*** 0.851*** 0.908***

[Mg1lichen -0.426 -0.607** -0.415 -0.618** ([Kj: [Mej)ii, 0.480* 0.804*** 0.738*** 0.718*** h,n t Two-tailed P levels are indicated as *<0.05, < 0.01, < 0.002. (n 18).

68 -r" Site numbers 1.1 1.2 1.3 1.4 1.5 1.6 =L 80

60

cr 40

20 00 00 00 gf 111111 0 4.5

- ü 4.0 P 3.5

3.0

2.5 I I I 1.2

0.8

Vorkuta

0.4 0 20 40 60 80 100 120

Distance (km)

Figure 3.12.a. Variation in [C21 (0), [Mgýl (0), [Ký] (V) and ratios [KI: [Mel and ([KI: ([Ca2+]+[Mej)) in Cladonia arbuscula on Transect 1. Plotted values are means ±I SE (n = 18).

69 Site numbers 2.12.2 2.3 3.3 3.2 3.1 Omr. Isu-, =L

60 I JE WRI 40

6- J 20 SIR 00 0 7

6

5

4

3 IIIII

" ce

bo

Inta

50 100 150 200 250 Distance(km)

Figure 3.12. b. Variation in [CW+] (0), [Me+] (0), [W] (V) and ratios

[KI: [Mgýj and ([Kj: ([C2j+[Mgýj)) in Cladonia stellaris on Transect 2/3. Plotted values are means ±I SE (n = 18).

70 Sitenumbers 2.1 2.2 2.3 3.3 3.2 3.1 100 =L 80

+ ýA 6 60 ;fI a I 40

20 00 0 00

r-m _6 %i IIIIII O a V

+ ei bO 5 I a +ý

3 3 U

+

2

ç Inta I 0 50 100 150 200 250 Distance(km)

Figure 3.12. c. Variation in [CWI (9), [Me+] (0), [Ký] (T) and ratios [Kj: [Me+] and ([Kj: ([C2+]+[Mgý+])) in Cladonia rangiferina on Transect 2/3. Plotted valuesare means±I SE (n = 18).

71 3.4. Discussion

3.4.1. Snow pack chemistry

2+ Baseline S04 and N03- concentrations in winter snowpack across the study ', area were c.5 and 9 ttmol I: respectively. Note that the low values (i. e. < 1) 2-])s. of the ratio ([N031 : [SO 4 at remote sites are typical of snowpack (cf Dasch, 1987; Moody and Samson, 1989) and are believed to be due to the low 2- scavenging efficiency of ice (snow crystals) for SO4 compared to N03'- These concentrations are comparable with those reported by Jaffe et aL (1995a) for remote sites on the eastern Kola Peninsula, by Ayrds et aL (1995) for sites in Finnish Lapland (S only) and by Nickus et al. (1998), Winiwarter et aL (1998) and Puxbaum and Tscherwenka (1998) for the Austrian Alps. However, they are higher than at sites in Alaska and Greenland receiving relatively little pollution from lower latitudes (e.g. in the range c. 1.2-4.5 and 1.5-3.0 1: 1for Mflsnow [S04 2-] [e. Osada c. timol and s., respectively g. et aL, 1996; Fischer et aL, 1998]). Sim6es and Zagorodnov (2001) estimated the background [nssS042 ],,,, Svalbard be I I: '. The true value of )won to c. pmol results of studies around high latitude emission sources in Canada (Barrie and Walmsley, 1978; Barrie, 1980) and Russia (Jaffe et aL, 1995a) have shown that only < 2% of total S and N oxide outputs are deposited within 25 krn of the sources. Therefore it is likely that the major part of the emissions from Vorkuta, Inta and Usinsk are dispersed over areas with dimensions very much greater than those of the transects studied here, contributing to the observed baseline [SO 21 [N031snow There is 4 ,ýw and values. evidence that the zone of local pollution around Vorkuta probably extends beyond the extremities of Transect 4 [SO421.. since values of w and pH,., and concentrations of spheroidal carbonaceous particles in surface lake sediments (Solovieva et aL, 2002) were greater at sites 4.1 and 4.6 than at remote sites elsewhere in the study area (e.g. sites 3.1 and 2.1).

In addition to local pollution sourcesin the Usa basin itself, major industrial regionsand emissionsources Of S02 and NO., exist in the Ural industrial

72 zonel 000 km to the south (e.g. Ryaboshapkoet aL, 1998).Furthermore, one of the major trajectoriesalong which polluted air massesfrom WesternEurope move into the Arctic passesover the Usa basin (Rahn, 1982;Polissar et aL. 1999; Sim6esand Zagorodnov,200 1). According to Barrie et aL (1989) and Me et al. (1999a,b) the northwardspollution flux is probably greaterin winter than during summermonths. Accordingly, Ryaboshapkoet aL (1998) have predicteda southto north gradientof decreasingdeposition of pollution- derivedN and S over the Komi Republic.

Analysis of snow and lichens collected from south to north on transects;2/3 provided an opportunity to seek evidence of such a gradient. Snow samples were collected at all sites between 3.2 and 2.2 at the extremes of the transects, which were located 200 km apart, approximately 20% of the distance between site 2.2 and the Ural industrial zone. While these analyses revealed clear in [Nej.,, [CI],,, gradients w and owconsistent with varying proximity to the coast there was little evidence of gradients in concentrations of acid ions. However, there is a latitudinal gradient in precipitation (Taskaev, 1997), a recent climate model (van der Linden and Christensen, in press) yielding annual values of 1334 and 611 nun at sites 3.2 and 2.2, respectively. Total 2- winter deposition of nssS04 were negatively correlated to latitude (Figure 3.6b) but winter deposition of N03-, W and total S042- were not, although winter deposition of H+ and total S042' were significantly greater at site 3.2 than at site 2.2 (P < 0.05, one-way ANOVA followed by Tukey's test, data not presented). However, aS to N gradient in [N],,,,. in C. stellaris is consistent with a concomitant gradient of decreasing total N deposition of total N. Note that total winter deposition of Na+ and C l'increases northwards despite the counter gradient in precipitation (e. g. relationship between winter Ne deposition and latitude: r2 = 0.52, P=0.042, n= 8) and that transects 1 and 4 der are not orientated along precipitation gradients according to van Linden and Christensen's (in press) modelled data.

Elevated[SO 42 values in closeproximity to Vorkuta and Inta were associatedwith other changesin snow quality, probably resulting from the depositionof coal ash, including higher pH, and concentrationsof Ký, C2'

73 (Figures 3.1. ab and 3.7), trace metals, particulates and alkalinity (Walker et aL, 2003). The link with coal ash is supported by (i) the absence of comparable contamination at sites close to Usinsk where power generation is gas-fired, (ii) the absence of concomitant elevations in [N03"Isno"values at all sites although the cluster of high values around Inta does not preclude some contamination at this site, and (iii) layers of black particulate matter visible in snow pits at sites close to Inta. and quite widely around Vorkuta. A cement factory in Vorkuta contributes significantly to the snow Ca2+load (Kuliyev, 1977,1979; Kuliyev and Lobanov, 1979; Getsen et al., 1994; Rusanova, 1995a; Walker et al., 2003). Similarly, Reimann et al. (1996) noted that the highest snowpack pH and [SO 421values recorded on the Kola Peninsula occurred close to emission sources, including mining sites, where dust is strongly believed to contaminate snow. Maximum values of [SO 42]snow recorded in this study were comparable with the maximum values recorded on the Kola Peninsula and in northern Finland by Jaffe et aL (I 995a); Ayrds et aL (1995); Reimann et al. (1996) and Caritat et aL (1998), and were only greater than background by a factor of about c. 4. The lengths of the transects were generally sufficient to characterize zones of local pollution around the towns I [SO421, high although on transect nw values remained comparatively at site 1.6,60 krn downwind of Vorkuta (Figure 3. La). Measurements of spheroidal carbonaceousparticles made by Solovieva et aL (2002) in surface sediments of lakes on the same Transects as those studied here corroborate a wider extent of particulate fallout around Vorkuta. This class of particle, which is an emission product of coal combustion, was present at sites 1.1 and 1.6 at higher concentrations than at any of the other remote sites examined in the study area (e.g. sites 3.2 and 2.2).

3.4.2. Lichen chemistry

Ibcre are markedregional gradientsin lichen nitrogen concentrationin the Usa basin suggestingthat there are concomitantgradients in N deposition.On the 240 km.south to north transectsthrough Inta (transects2 and 3), valuesof [N] . in Cladonia stellaris decreasefrom 0.57 ± 0.01 mmol g"' at site 3.2, to 0.43 ± 0.01 mmol g" at site 2.1, a proportional changec. 25%. While we

74 considerthat a gradientin N load is the most likely explanationfor variation in [N].,, (seeHyvarmen and Crittenden, 1998a),other causalfactors cannot be ruled out, thallus growth rate in particular. Higher growth ratesmight be expectedin warmer and moister climatesat lower latitudeswhere greater dilution lower [N]. is growth would the value of p.., a predictedtrend that contrary to that observed.Data on NHý+and organicN concentrationsin snow pack and summerrainfall chemistryare requiredin order to ftu-therassess the trendsin lichen N concentration.

Elevated [N]aje. in C arbuscula, and to a lesser extent in Flavocetraria cucullata, in the Vorkuta area suggest elevated N deposition due to local industrial Variation in [N],, in C pollution. pe" arbuscula correlates well with 2-],., other pollution signals in snow qSO 4 pHs,,.,,) and metal contamination in soil (Walker et aL, 2003) as well as lichen thalli; for example, values of [N]ape. [Zn 21, in C and apex arbusculd were strongly positively correlated along this transect (r = 0.90, P= <0.01, n= 6). As on the other transects, [N]. [N03'lsnow-Concentrations N pe.was not correlated with of organic were also determined in a small subset of snow samples from transects I and 4 by J.N. Cape (Centre for Ecology and Hydrology, Edinburgh) using an ANTEK 8060 IIPLC total N analyser. Molar concentrations of organic N were broadly similar to those of nitrate, except at sites close to Vorkuta where [organic Nlsn. [N031,,,. by factor 2 3 w values were greater than w a of or varying in [SO 2-] Thus higher deposition spatially a manner similar to that of 4 .. a rate of organic N at sites close to Vorkuta might have contributed to elevated [N]ap,..in this area. In addition, the possibility cannot be excluded that impaired lichen growth at sites close to Vorkuta, perhaps due to phytotoxic air pollutants, might result in higher tissue N concentration.

Pollution emissionsfrom Inta and Usinsk are considerablylower than from Vorkuta. This is the most likely explanation for the absence of a clear response in [N],, in lichens pc,, close to Inta and Usinsk. However, even on transects 2/3 4 higher and some of the [N], q,,, values were recorded in close proximity to the towns raising the possibility that the effects of N pollution here are close to detection limits. A lack [N031. Vorkuta but of elevated o,, around elevated

75 [N]. in lichens be by in [N031soil pe.values may explained variation elevated which may be governed by local site characteristics (Kashulina et aL, 1998). It should be emphasized that the data for snowpack chemistry provides data for a single winter period, whereas [N]am values probably provide an indication of N deposition integrated over a period of at least I-2y. Furthermore, the above interpretations are made in the absence of commensurate data on [NH41snow-

Terricolousmat-forming lichens are ubiquitous throughoutthe Subarcticand the presentresults are consistentwith thoseof Sochting(1990) and Hyvarinen and Crittenden(1998a) in suggestingthat they provide a useful reporterfor N found [N]. in C. deposition.Hyvdrinen and Crittenden(1998a) that P,,, portentosa covariedwith N depositionbut not [N1p,.iPitwion- Thus, in the in presentstudy the lack of covariation between[NO31sn(, w and [N]ýP,,, C. stellaris, C arbuscula and F. cucullata doesnot vitiate a relationshipbetween NaN. N deposition. Values [N]. in C C and of p.., arbuscula and stellaris collected in the Usa basin varied between 0.4 - 0.7 mmol g". These values can be 0.5 1.0 g" for [N]. in C compared with the range of - mmol i)e,, portentosa recorded in the British Isles at sites subject to a range of annual wet-deposited 1 N loads varying from 71 - 1007 mol N ha7l yf (NIW + N03) (11yvdrinen and Crittenden, 1998a). The difference between these concentration ranges may reflect a physiological difference between species but more likely reflects higher N deposition rates in industrial Europe. In Hyvarinen and Crittenden's (1998a) survey of C. portentosa in the British Isles, [Nlb.. (for the same thallus stratum as analysed in the present study) was found to fall in the range

0.1 - 0.5 mmol g"'. This can be compared to [Mbasevalues for C stellaris on Hyvarinen Crittenden found Transect 2/3 of 0.1 - 0.2 mmol gý'. and (I 998a) between [N]. N deposition that the relationship Ie. and annual total was significant but that [Nlbasewas an even stronger correlate. It is not known why [Mbwe should correlate well with N deposition in one region and [N].,,,,, to be apparently more responsive in another; here again, a species difference cannot be ruled out. It is also possible that [N].,, is a more coherent indicator of N deposition in highly oligotrophic regions while [Nlbasecorrelates better in regions with higher N loads.

76 Hyvarmen Crittenden (1996) found ([K]: [Mg]). in and that the ratio of p,,,, the heathland lichen C. portentosa was a good index of [Hj in precipitation in the British Isles while the ratio ([K]: ([Mg] + [Ca])),,,,, was not. However, in the present study, ([K]: [Mgl)w,, values in C arbuscula were higher in the vicinity of Vorkuta but in this case it was apparently a response to deposition of alkaline ash. This change in lichen chemistry was associated with elevated concentrations in snow of a range of anions and cations, including heavy metals (Walker et aL, 2003), probably as a result of coal ash deposition. Thus in this region the ([K]: [Mg]).. marker appears to have responded to elevated K deposition while the ratio ([K]: ([Mg] + [Ca]))"j)exhas probably responded to emissions of Ca-rich particulates from coal burning at the power station and nearby cement factory (Figure 3.7)(cf. Jalkanen et al, 2000). These findings demonstrate that these indirect lichen indices for acid deposition can be seriously confounded by enhanced deposition of alkali and alkaline-earth from Neither ([K]: [Mg]),, ([K]: ([Mg] cations pollution sources. Pýxnor + [Ca]))w. in C stellaris were higher at the southernmost sites on Transect 2/3 than at northernmost sites, suggesting that latitudinal differences in mean precipitation acidity, if any, were insufficient to modify lichen chemistry.

There was localised elevation of [Zr? japý,, in C arbuscula around Vorkuta [Znýjý, in C Inta, latitude. and pe. stellaris around was strongly related to However, lowest concentrations of [Zn2jw. were comparable with other studies in pristine locations (Table 3.3) whilst elevated concentrations around

Vorkuta are as high as concentrations found in Cladonia species around coal mining towns and zinc smelters. According to Folkeson and Andersson-

Bringmark (1988) [Zn]aie measured in C rangiferina sampled 6-7 km away ,, from foundries in Gusun, Sweden were 55-75 gg g" whilst the first sign of reduction of cover of C rangiferina was observed when the [Zn]ve,, was 500 pg g". Folkeson and Andersson-Bringmark (1988) suggested that a [Zn],,,,,, limit of 600 tig g" indicated the apparent threshold concentration for survival.

The [Zn]ap,,, observed in this study fall far below the threshold likely to cause damage to the lichen species sampled, even around the Vorkuta industrial complex where elevated concentrations were observed.

77 Table 3.3. Comparisonsof [Zn]aj.. ([tg g") from high latitude industrial and pristine areas.

Location Species [Znl (pg 9") Study

Inta. (Transects 2/3) C rangiferina 15-34 This study C stellaris 9-32 Vorkuta (Transect 1) C arbuscula 16-55

Southern Finland C stellaris 38 Lounamaa(1965)

Delaware Gap, USA Cladonia sp. 61-80 Nash (1975) (zinc smelter)

SE Ohio,'USA Cladonia sp. 2742 Lawrey and Rudolf (1975) (coal M.min g)

Northwest Territories, Cladonia sp. 7-55 Puckett( 1978) Canada Cladonia sp. 16-25 Puckettand Finegan(1980)

Sudbury,Ontario, Canada Cladonia sp. 25-11 Glooschenkoet al., (1981) (85-940 Ian from smelter)

Bellsund.area, Spitzbergen Cladonla sp. 29-39 J6zwik(1990)

High Point Park, New C. rangiferina 7-16 Glennetal, (1991) Jersey,USA

Ontario, Canada,Uranium C. Miltis 13-22 Fahseltet al., (1995) mines (0.5-30 Ian)

3.5. Conclusions

Presentedhere is evidenceof pollution gradientsacross the Usa basin on two geographicalscales. The first is a latitudinal gradient in N and S deposition probably resulting from northward-movingair-masses originating from industrial regionsof the Urals and WesternEurope (Rahn, 1982;Ryaboshapko et aL, 1998)but with somecontribution from more widely dispersedemissions from local sources.The secondis local gradientin alkalisation extendingto 25-40 km aroundthe coal-buming centresof Vorkuta and Inta.

78 Baselineconcentrations of N03"in snowpackobserved in this study were c. 1, 9.2 ýLmol1: and [nssSO42-]. valueson Transects2/3 were between4.0 - 5.2 pmol L". Using as a multiplier total annualprecipitation values at each site modelled by van der Linden and Christensen(in press) yields annual depositionsin the rangesof 56 - 123mot N ha7ly-1 and 29 - 65 mot nssSha7l y-1.These values can be comparedto publishedestimates of critical loads of and S for Subarcticand Arctic ecosystemsbearing in mind that nitrate depositionmight be lower than total N deposition by a factor of at leasttwo. ' Homung et aL (1995) proposedthat the critical load for N in Arctic and alpine heathlandswas in the range375 - 1071mot N ha7ly" while, on the basisof N fertilization experimentson Svalbard,Gordon et aL (2001) suggestedthat the critical load value is likely to be towards the lower end of this range.Bashkin et al. (1995) producedcritical load mapsfor N and S over northern Siberia where the most sensitiveecosystems have critical load values<50 mot ha7lY' for both N and S but with many areaswith valuesin the range 51 - 100 mot ha7 1Y'. Bashkin (1997) producedcritical loads mapsfor EuropeanRussia suggestingthat c. 50% of Subarcticand Arctic areashave critical loads for N in the range0- 200 mot ha7ly-1. While for S, only 2% of the region had a critical load in the 0- 200 mot ha7lf1 range,and 31% of the region had values 1. of 200 - 500 mot ha7lf Lien et al. (1993) reportsthat the most sensitive surfacewaters on Svalbardhave a critical load for nssSof between59 - 309 mot ha7ly-1. Clearly there is still uncertaintyabout critical load valuesbut currentknowledge suggests that N depositionover the Usa basin could already exceedthe critical load in someecosystems.

There is now compelling evidencethat tundra vegetationin the vicinity of Vorkuta hasbecome modified due to alkaline dust pollution. Vegetation classificationand mapping studiesusing satellite data suggestthat the affected areais between600 - 900 km2 and is characterisedby an increasedabundance of willow and reducedabundance of dwarf birch and other dwarf shrubs (Virtanen et aL, 2002). Within this affectedregion a high impact zone is recognizedin the immediatevicinity of the town and industrial complexes covering 150- 200 kni2; here lichens are largely absentand mossesand grasseshave a greaterabundance. The causalagency may be complex

79 interactionsbetween alkalisation, eutrophication, phytotoxic gases(e. g. S02) and heavy metal deposition(Walker et aL, 2003). In addition, depositionof black particulatesin snow will acceleratespring snow melt due to reduction in albedo(average freezing point depressiondue to salts was <0.00I *C in all cases);evidence for such an effect again comesfrom satellite images (Virtanen et aL, 2002). Earlier spring thaw could have both positive and negativeeffects (e.g. longer growing seasonand increasedexposure to frost, respectively).However, it is interestingto note that thesevegetation changes in the Vorkuta areaare similar to thoseobserved to occur in responseto N enrichment(Paal et aL, 1997).Data for [N] in lichen thalli and organicN concentrationsin snow lend ftirther supportto an N enrichmenthypothesis. Emissionsfrom Vorkuta (currently 37 x 106kg S02) have probably declined markedly sincethe 1980swhen annualcoal production peakedat 20 x 106 tomics (Virtanen et aL, 2002). The resultsof a stratigraphicalanalysis of carbonaceousparticles in two lake bottom sedimentsin two lakesin the Vortuka region corroboratesthis historical trend suggestingthat maximum emissionsof combustionproducts were probably reachedseveral decades ago, sincewhen output has declined(Solovieva et aL, 2002). It is not known to what extent the modified vegetationis a relic of a former and more severe pollution climate in this region. Suchobvious impactsof local dust pollution were not evident aroundInta (T. Virtanen,pers. com.) probably because(i) emissionsfrom this sourceare considerablyless than from Vortuka and (ii) Inta is in the forest-tundrazone where impactsmay be less apparentfrom satellite data.

80 CHAPTER 4. ANTHROPOGENIC METAL ENRICHMENT OF SNOW AND SOIL IN NORTH-EASTERN EUROPEAN RUSSIA

4.1. Introduction

This Chapterreports the trace metal compositionof winter snowpack,snow- melt filter residuesand top-soil samplesin the Usa Basin, north-eastEuropean Russia.'Me researchwas a contribution to TUNDRA (TUNdra Degradationin the RussianArctic). 'Me study areahas a total surfacearea of 93,000 km2. Ile region has been subjectto a rangeof industrial impacts,producing variation in land use from pristine uninhabitedareas to denselypopulated areas of industrialisationincluding oil and gasfields, coal and ore mining. The objective of the study was to provide information on the distribution and magnitudeof trace metal compositionin snow and soil resulting from fossil fuel combustionand petrochemicalindustrial processeswithin the Usa Basin.

Previouspollution studiesin the region have beenconducted in the immediate vicinity of towns such as in the Bolshezemel'skaya.tundra aroundVorkuta. (Kuliyev, 1977,1979; Kuliyev and Lobanov, 1979; Getsenet al., 1994; Rusanova,1995a, b). Heavy metal pollution within the Usa basin is associated with power generation(coal combustion),cement production, coal mining, gas and oil extraction, forestry,pulp and paperproduction, constructionand oil refineries(State of the environmentof the Komi Republic, 1992-1998).The region has alreadybeen identified as a significant sourceof acid and alkaline emissions(Ottar, 1989;Nenonen, 1991; Getsen et aL, 1994;Rusanova., 1995a, b; Vinogradova,2000), mainly as a result of coal fired power stationsin Vorkuta and Inta and a gas-firedpower station in Usinsk.

The variablesmeasured were, snow, which was analysedfor Ag, Al, As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sr and Zn using ICP-MS (Ca and K by F-AAS for Vorkuta only), pH and acidity/alkalinity. Filter residueswere analysedfor: Al, Ba, Ca, Cd, Cu, K, Mg, Mn, Ni, Pb, Sr and Zn using F-AAS and GF-AAS; top-soil sampleswere analysedfor Ba, Cu, Mg, Mn, Na, Ni, Pb, Sr, Zn using

81 F-AAS. Ile analysisof the chemicalcomposition of snow provides useful information on aerosolchemistry and long-rangedistribution patternsof anthropogenicsubstances emitted into the atmosphere(Tranter et aL, 1986, 1988;Jaffe and Zukowski, 1993; Shawet aL, 1993;Colin et aL, 1997). Concentrationsof dissolvedelements in melted and filtered snow may be used to estimatedeposition during winter. However, total depositioncan be seriouslyunderestimated if particulateswithin the snow are omitted and so analysisof filter residueswas included in this study (Reimannet aL, 1996; Gregureket aL, 1998a).Analysis of the underlying soil can be usedto evaluate long term accumulationof conservedpollutants (Boyd et aL, 1997;Niskavaara et al., 1997;Reimann et aL, 1997ab, 1998,2000).

The resultspresented here indicate elevatedconcentrations of elements associatedwith alkaline combustionash aroundthe coal mining towns of Vorkuta,and Inta. There is little evidenceof depositionaround the gasand oil town of Usinsk. Atmospheric depositionin the vicinity of Vorkuta, and to a lesserextent Inta, addedsignificantly to the soil contaminantloading as a result of ash fallout. Acid depositionwas associatedwith pristine areas whereasalkaline combustionash near to emissionsources more than compensatedfor the acidity causedby S02. The probableunderlying causal factors are discussed.

4.2. Materials and methods

4.2.1. Study area and sampling regime

For a more detaileddescription of the study areaand samplingregimes see Chapter2 (2.1.1; Figure 2.1; Table 2.1). Study siteswere located in the Usa river basin betweenlatitudes 64' and 68' N in the Komi Republic, north-east EuropeanRussia. Four transectsthrough suspectedpoint sourceswere undertakento assessthe distribution of pollutants from coal mining and burning in Vorkuta and Inta (Figure 4.1) and from oil and gasextraction and use in Usinsk. Thus, transectswere establishedthrough the three principal

82 towns of Vorkuta (67'30'N, 64'05'E; Transect 1), Inta (66'03'N, 60'10'E; Transect 2 and 3) and Usinsk (66'0 1'N, 57'30'E; Transect 4) (see Figure 2.1; Tables 2.1 and 2.2).

4.2.2. Snow sampling

For further details of snow collection methods see Chapter 2 (2.2.1 ).

(a)

ýN

(b)

Figure 4.1. (a) Coal combustion at Inta and (b) Vorkuta. (Photos: T. R. Walker).

83 4.23. Soil sampling

Soil sampleswere collectedbetween July and August in 1998and 1999 from a 20 x 20 cm,quadrat with a stainlesssteel hand trowel to a standarddepth of 5 cm (Niskavaara,et aL, 1997;Reimann et aL, 1997a).Powder-free polythene gloveswere usedat all times to minimise the risk of contamination.See Chapter2 (2.2.3) for further details on soil collection.

Approximately 20 krn beyondthe northernmost site at Khosedayuriver, 2.1, (seeFigure 2.1, Table 2.1) on transect2/3 an additional set of top-soil swnples were collectedalong the Upper Kolva river during July 2000.

4.2.4. Chemical analysis of snow

For ftirther details on the chemicalanalysis of snow seeChapter 2 (2.4). Analysis of trace metals: Ag, Al, As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sr and Zn were conductedon acidified liquid samplesby inductively coupledplasma massspectroscopy (ICP-MS) at the University of Lancasterby Dr Hao Zhang. Cations(Na+, Ca2+, K) were determinedby flame emissionspectrometry (FES) with appropriateadditions of CsCI as ionisation suppressant(1000 mg Cs I;, ).

4.2.5. Elemental analysis of suspendedsolids in snow

Details of elementalanalysis of suspendedsolids in snow are given in Chapter 2 (2.4.5). Celluloseacetate membrane filters usedto filter the snow-melt sampleswere oven dried at 80 T overnight in glasspetri-dishes and suspendedsolids were determinedgravimetrically. Six cellulose acetate membranefilters from eachsite were digestedand elementalanalysis of Al, Ba, Ca, Cd, Cu, K, Mg, Mn, Ni, Pb, Sr and Zn was undertakenby GF-AAS and F-AAS. Concentrationswere recalculatedin relation to the volume of filtered meltwaterto allow direct comparisonwith the solution data (Reimann

84 et aL, 1996).Net acidity or alkalinity was determinedby granplot acid titrations following the methodof Legrandet al. (1982), seeChapter 2 (2.4.2).

4.2.6. Soil analysis

Details of soil analysisare given in Chapter2 (2.6). Analysis of Ba, Cu, Mg, Mn, Na, Ni, Pb, Sr and Zn was undertakenusing GF-AAS and F-AAS. Soil pH was measuredon moist soil samples,suspended in DI water at a solid: solution ratio of I: 2.5 following equilibration for I hour. All soil samples were subsequentlyincinerated in accordancewith the terms of the MAFF (DEFRA) licence for soil importation.

4.2.7. Elemental concentrations in snow and soil

Elementalconcentrations in snow (including suspendedsolids) and soil were consideredtogether in an attemptto explain the large concentrationsfound aroundthe cities in relation to current depositionrates (see Chapter 2,2.7; Equation 2.8).

43. Results and discussion

4.3.1. Acidity and alkalinity in filtered snow-melt

Resultsof Granplot titrations shown in Figure 4.2 illustrate pronounced alkalinity associatedwith ashdeposition around Vorkuta. This was also reflectedin the snow pH measurements(data shown in Chapter3). Alkalinity 1; valueswere greatestat site 1.4 (mean= 0.139 meq 1: ± 0.015). Only sites 1.1 and 1.6 at the transectextremes showed net acidity. By contrast,net acidity was recordedat all locationson the Usinsk transect.For the Inta transects(2/3) alkaline ashdeposition around the city (sites; 2.4,2.5,3.5,3.4) effectively neutralisedany local acidity and the backgroundacidity shown in pristine 1). snow (approximately-0.0 1 meq 1:

85 0.16

0.12

0.08

*0 0.04

0.00 ...... 00*. Ici :0U ...... 4p ...... 0 "0 ...... -0.04

E- AR Iu -A 00 120 -80 -40 0 40 80 120 Sampling sites showing distancealong transects(km)

Figure 4.2. Values of granplot acid titrations determinedfor filtered snow- melt samplestaken along transects,through the industrial towns of Vorkuta (V), (running W- E), Inta (e), (running N- S) and Usinsk (o), (running SW - NE) during spring 1998and 1999.Plotted valuesare means± SE (n = 18).

43.2. Elemental analysis of filtered snow-melt (Figures 43. a. and 4.3.b. )

No evidenceof previous snow-meltwas observedin the snow profiles; characteristichorizontal ice layerswere absent(Barrie and Walmsley, 1978; Shawet aL, 1993).Along transectsthrough Vorkuta and Inta snow collectedat

86 sites closestto the towns containedelevated concentrations of As, Ba, Mn and Sr. In addition elevatedconcentrations of Ca and K in snow were found aroundVorkuta (Figure 4.3.a), which may suggestthat combustionash was the source(Reimann et aL, 1996).Arsenic concentrationswere greatestat the urban sites aroundVorkuta (sites, 1.3 and 1.4) and lower, respectively,in Inta and Usinsk and concentrationsof the trace metals Cd, Cu, Ni, Pb and Zn were uniformly low at all sites (Figure 4.3.b). However, the absenceof a pronouncedurban peak in solution concentrationmay have beena result of adsorptionon alkaline ash.In addition, concentrationsof Ba, Co, Cu, Sr and Zn were slightly greaterin Inta than aroundVorkuta, possibly becausethe town's coal-fired power plant was closer to thosesampling sites. At the most southerlysite on the Inta transect(site, 3.2) unusually large concentrationsof Cu, Pb and Zn occurredin the vicinity of the Polar Ural Mountains,perhaps suggestinga local geogenicsource or possibly even long-rangetransport from lower latitudes.Close to Usinsk (site, 4.3) there was minor elevationof Pb concentrations,compared to thoseof backgroundvalues, but other metalswere found at backgroundconcentrations around the town. Along all transectsCo concentrationswere uniformly low (< 0.10 pg 1: 1) (Figure 4.3.b). For Ag (data not shown),Al and Cr urban peakswere not observed;concentrations ranged from 0.17 - 0.39,3.3 - 18.3and 0.03 - 0.3 [LgU1 respectively.

433. Suspendedsolids in snow

At most sites on the Vorkuta transect,and at sites close to Inta, dark horizontal bandswere observedin many of the snow profiles, probably the result of ash and soot depositionfrom coal combustionduring periods of snow-fall. This was also evident when snow-meltwas filtered through cellulose acetatefilters (Figures4.4. a, b).

87 25 Al i 20

15

lo

5 12 f1 u --ID Qu -zýe. 0 -Y- 0 0 op 111 al 150 Fca11111

7500 100

5000

50 2500

0

Mn w 6

4 4

2 2 13 00 13 00 A n -100 . 50 0 50 100 -100 -50 0 50 100

Sampling sites showing distance along transects (km)

Figure 4.3.a. Concentrationsof metal elementsin filtered snow-melt, representingthe principal soil and ash derived components,from transects Vorkuta (V) Inta (e), Usinsk (o), during 1998 1999. through , and spring and Trace elementswere measuredby lCP-MS; concentrationsof Ca and K were measuredby F-AAS along the Vorkuta transectonly. Plotted valuesare means ± SE (n = 3).

88 1.6 -As 0.4

1.2 0.3

0.8 0.2

0.4 0.1 101N. 0.0 0.0 Y.U-. eyI 0.09 0.4 -W -Cr

0.3 0.06

to 0.2

0.03 0.1

n nn AA

3 15

10

5

1.6 15

1.2 10 0.8

5 0.4

AA A -100 -50 0 50 100 -100 -50 0 50 too Sampling sites showing distance along transects(km)

Figure 43. b. Concentrationsof metal elements,representing industrial trace elements,in filtered snow-melt from transectsthrough Vorkuta (Y), Inta (e), and Usinsk (o), during spring 1998and 1999.Trace elementswere measured by ICP-MS. Plotted valuesare means± SE (n = 3).

89 VORKUTA (Transect 1)

".;

11 12 13 14 1 15 16

(a)

USINSK (Transed 4)

41 42 43 44 45 46

(b)

Figure 4.4. Suspended solids collected on 2.5 cm diameter cellulose acetate filters after filtration of I 10 mL of thawed snow samples collected along transects through Vorkuta (a) and Usinsk (b). (Photos: T. R. Walker).

Figure 4.5 shows the concentration of suspended solids collected on cellulose acetate filters following filtration of thawed snow. The trend along each transect strongly suggests a substantial contribution from coal combustion in Inta and Vorkuta, as the highest concentrations are found around the towns. In

90 most casesthe three sites (eachwith six aggregatedsub-sites) at eachtransect location gavequite small standarderrors.

The quantitiesof solids depositedin the Vorkuta areafrom 1992to 1998 were between5-8 times greaterthan for Inta, where, in turn, depositionwas approximately3 times greaterthan for Usinsk. The meanvalue of solids emitted from Vorkuta between1992 to 1998 was estimatedat 84,000t (Stateof the Environmentof the Komi Republic, 1992-1998).

43.4. Elemental analysis of particulates in snow

In the immediatevicinity of Vorkuta and Inta there were elevated concentrationsof the major combustionash constituents: Al, Ba, Ca, K, Mg and Sr (Figure 4.6). Urban plumes for Cu, Ni, Pb and Zn are evident from analysisof snow-borneparticulates around Vorkuta and Inta. For Cd there was no urban peak,but values for the Inta trmsect were uniformly greaterin comparisonwith the Vorkuta or Usinsk data.The cationic compositionof the suspendedsolids was dominatedby Ca (Figure 4'.6). If it were assumedthat the Ca is presentas CaCO3this would constituteapproximately 12 % of the suspendedsolids aroundVorkuta. Sodium was not measuredin suspended solids but it is likely that most of the Na presentwas in the solution phase, given the solubility of Na salts and the large ratio of solution to particulatesin the thawed snow. The entire transectthrough Usinsk generallyreflected backgroundconcentrations similar to thoseobserved in pristine areasat both endsof the Inta and Vorkuta transects.

Concentrationsof ions associatedwith particulatesand thosein free solution were strongly related in snow collectedon the Vorkuta transecte. g. Ca (r2 0.97), Sr (r2 = 0.97), Mn (r,2 = 0.91) and Ba (r2 = 0.86). Combining the data for filter residuesand snow meltwatergives the total concentrationof these elementswithin the snow (Reimannet aL, 1996; Gregureket aL, 1998b).The concentrationratio betweenelements in particulatesand in the solution phase of thawedsnow showedthat the majority of the major constituentsof

91 combustionash were in particulateform. Mean solid : solution ratios for total concentration(mg 1: 1)of Ca, Ba, Sr and Al were 12,17,10 and 9 respectively. This confirms that estimatesof depositionfrom filtered thawed snow alone, can seriouslyunderestimate deposition rates by up to 90 % for certain elements where there is significant particulatepollution (ALyrdset aL, 1995;Reimann et aL, 1996).

50 J\LS 40

30

20

A, lu 0 0 50 loo 150 200 2,' 0 0.50 wE 40 Iri 0 iu (A Ici u 20 10 10 Vorkuta

4.4 0 0 50 sw NE 40

30

20 -7Uýsýin:sk 10

0. IIIIII 0 25 50 75 100 125 150 Distance along transects (km)

Figure 4.5. Concentrationof suspendedsolids in filtered thawed snow samplestaken along transectsduring spring 1998and 1999.Plotted valuesare meansI SE (n = 3).

92 250 - 90 - 2500 Al Ba 200 - 2000 60 - 150 - 1500

100 - 1000 30 - 50 - 500 13 13 M, 0 0 0 3 200 =L Cd Cu I. ý Ad. 2 50 - 2 00 DO - 0 0# f1-0 50 - 101 10 ol I -- 0 120 6 V - Cl. Mg W Mi Ni 2 90 - 4-

60 '0

d)8 , o 30 02-0 00 ol 901111111 ol 111111ý U 1.5 - 50 - 15 - w Pb Sr Zn /; 40 - 1.0 10 0* 30 - -L

'0 20 -0 A,

1 oo 11 p111ýo111111-1 0.0 111110 100 9,eý v -75 -50 -25 0 25 50 75 100 -75 -50 -25 0 25 50 75 100 -75 -50 -25 0 25 50 75 100 Sampling sites showing distance along transects (km)

Figure 4.6. Concentrationsof metal elementswithin filter residuesfrom snow samplestaken along transectsthrough Vorkuta.(v), Inta (e), and Usinsk (o), during spring 1998and 1999.Plotted values are meansI SE (n = 3). Note: elementconcentrations are expressedas pg 1: 1 snowmelt.

93 4.3.5. Soil analysis

from The depth of the surface organic layer each quadrat varied between 0.5 - >5 cm (Figure 4.7).

Figure 4.7. Soil profile under pine-dominated lichen woodland at Shar'yu (site, 4.5; Figure 2.1). Note the shallow organic horizon (0-5 cm) and development of a bleached Ea horizon characteristic of podzol formation. (Photo: T. R. Walker).

Elevated soil pH, (mean pH 6.83; ± 0.08) was found only in the Vorkuta area at site 1.3 (Figure 4.8), possibly a result of local deposition of alkaline ash material from coal combustion and a cement factory. In mineral soil (0 -5 cm depth) Rusanova (1995a) measured pH values of 7.2 within the town, whereas the pH fell to 4.8 at 15 kin SW of the town limits; these figures compare favourably with the present data. Soil pH along transects through Inta and

Usinsk were uniformly low. For transects 2/3 through Inta the lowest soil pl I was recorded at the peatland site 3.3, (mean ptl 3.5 1; ± 0.06) and the highest values were recorded at site 3.5 (mean pH 4.40; ± 0.09). Oksanen el al. (200 1 measured pH values in the range, 3.8-5.0 at sites on the peat plateau along the Rogovaya river, a tributary of the Usa.river. Along transect 4 through Usinsk, pH values varied between 3.90; ± 0.05 at site 4.1 and 4.93; ± 0.07 at site 4.3 similar to values recorded at the extremes ofthe Vorkuta transect.

94 For the lesscommon soil constituentswhich are found in combustionash (e. g. Ba and Sr) there was clear evidenceof increasedloading close to Vorkuta which compareswell with anotherstudy of top soil closeto combustionash emissions(Vassilev and Vassileva, 1997).Mean concentrationsof Ba and Sr in soil ash(n = 18) were 2780 pg g-1(± 129) and 131 pg g" (± 6.1), respectively,at site 1.3 (seeFig. 4.9). By contrast,concentrations for the backgroundsite at the easternend of the transect(site 1.6) were 309 pg g-1 22) and 22.6 gg g" (± 1.9) respectively.There may also be soil enrichmentof Ni, Zn and Cu aroundVorkuta. but the scatterin the data makesthis conclusion difficult to sustain.According to Singh et aL (1995) elevatedsoil concentrationsof Mn, Cu, Pb and Ni in soils can be found closeto coal-fired power stations.There was no suchenrichment around Inta, possibly due to the reducedquantities of solids emitted in Inta comparedto Vorkuta.(State of the environmentof the Komi Republic, 1992-1998).

The spatial extent of the local alkalisation of top-soil at sites aroundVorkuta corresPondswith vegetationchanges evident in satellite imageswhich have beenconfirmed by groundplot field observations(Virtanen et aL, 2002). Similar observationswere madeon the Kola Peninsulawhere alkaline ash enrichmentof the local areacaused changes to the natural vegetation (Buznikov et aL, 1995;Reirnann et aL, 2000). -

The variation in top-soil pH showsthe effects of the emissionsources of Vorkuta and Inta; the most acidic sampleswere collectedat the extremitiesof the transects.'Me higher soil pH valuesaround Vorkuta correlatewell with the Ca concentrationsin snow and particulates.This indicatesan important role for ashinput from coal combustionand cementdust from the nearbycement factory in regulating snow and soil pH. Potentially, a reduction in fly ashand

95 7

C)I?

4 ii 0 0 11111 150 -100 -50 0 50 too 150 Samplingsites showing distancesalong transects(km)

Figure 4.8. Measurementsof pH in top-soil samples(0-5 cm) taken along transectsthrough Vorkuta (v), Inta,(e), and Usinsk (o), during summer 1998 and 1999,Plotted valuesare means± SE (n = 18). cementdust emissionscould meansolubilization of accumulatedheavy metals due to a progressivedrop in soil pH (Reimannet aL, 1996;Haapala et aL, 2001). Robb and Young (1999) found that large additionsof calcareous,metal- rich, fly ashto acidic soils increasedthe soil pH, to the extent that the metal ion concentrationin the soil solution was reduceddespite the increasedtotal metal loading to the soil from the ash.Approximately 20 krn beyondthe northem-mostsite at Khosedayuriver, 2.1, (seeFigure 2.1, Table 2.1) on transect2/3 an additional set of top-soil sampleswere collectedalong the Upper Kolva river. Mean pH at this site was 4.26 (± 0.06, n= 6), which compareswell with pH valuesfound elsewherealong the transectextremes of transect2/3. Analysis of additional soil samplescollected from the Upper Kolva during summer2000, are presentedin Table 4.2. Mean concentrations of Ba, Cu, Mg, Pb, Sr and Zn in soil ashcompare favorably with those concentrationsrecorded for the sameelements along the entire 2/3 transect.As this was the northernmost site along transect2/3 elevatedlevels of Na and Ni were probably due to marine inputs

96 3000 - 10 - 3000 Ba Cu Mg

2000 2000 - 6-

1000 1000 66 - 2-fii 4f ffo 0a 11 *cp 011 00 101 11 op ni QIo-II OQ nt I-- I ol 01 -- 1600 - 300 - 25 - Mn Na Ni 20 - 1200 - 0-1 200 60 15 - 800 - 10 - 100 ed 400 IV -$ Cý 5 0 (A t, oot 1 1010 1 1()0? 111 o -%LOWýý oI 35 - 150 - Cd Pb Sr 60 -Zn 30 - 50 25 - - 100 - 40 - 20 - 30 15 - 50 - 20 10 - tp - 5- 10 00,0 co cm 01 11111 10110 11110tIIII -i 0 50 loo 150 -150 -100 -50 0 50 100 150 . 100 -50 0 50 100 150 -100 -50

Sampling sites showing distancealong transects(km)

Figure 4.9. Concentrationsof metallic elementswithin soil ashtaken along transectsthrough Vorkuta,(v), Inta (9), and Usinsk (o), during summer 1998 and 1999.Plotted valuesare means± SE (n = 18).

97 from the BarentsSea. Concentrations of Ca, Cd and K (n = 6) were 171.9tig g" 1 (± 18.9), 0.09 [tg Eý'(± 0.02) and 1325.5pg g" (± 175.6),respectively, and could not be comparedto other sites along transectsas theseelements were not previously analysed(see Table 4.1).

Table 4.1. Concentrationsof metal elementswithin soil ashtaken at the Upper Kolva.

Element Elemental concentrations in ± SE analysed soil ash (pg (n = 6) Ba 27.59 2.62 Ca 171.87 18.87 Cd 0.09 0.02 Cu 11.84 1.29 K 1325.50 175.51 Mg 1592.55 3,13.83 Na 199.78 36.14 Ni 102.68 30.67 Pb 35.20 1.21 Sr 1.59 0.30 Zn 39.66 1.25

43.6. Comparison of deposition rates with excess soil loading (Equation 4.1)

Tables4.2. a and 4.2.b show the estimatedtimes required for the accumulation of elements,in excessof pristine sites,at the current measuredrates of element depositionin snow. For both major and minor elementsTd (equation4.1) was considemblyin excessof the life spanof the city of Vorkuta, suggesting current ratesof metal depositionin precipitation (Ad) cannotexplain the apparentaccumulation in soil. For examplethe valuesof Td for the trace

98 elementsCu andNi were 304 and 342 y respectively;for the alkali earth elementsBa and Sr Tdwas 3250 and 154 y (Table 4.2.a and Table 4.2.b). The discrepancybetween the duration of industrial developmentin the region and the amountof time requiredto accumulateapparent excess soil metal loadings from currentdeposition rates may arise for a number of reasons.

Firstly, there has beena substantialdecline in coal mining in Vorkuta, since the peak of activity in the 1960sand 1970s.The 13 coal-minesoperating in 1990were reducedto just sevenby 1999(State of the environmentof the Komi Republic, 1992-1998).Coal production at the largestmine, Vorgashorskaya,fell by 40% between1991 and 1999,from nearly 21 X 106 tonnesto 13 x 106tonnes (State of the environmentof the Komi Republic, 1992-1998).This trend is consistentwith data on spheroidalcarbonaceous particles (SCPs,only producedfrom high temperaturecombustion) found in lake sedimentprofiles. Lake sedimentprofiles showedthat a peak in SCP's was found at 1.5 cm below the sedimentsurface and suggestthat SCP depositionrates has sincebeen in sharpdecline (Solovieva et aL, 2002). Secondly,Vorkuta has a total population of around200 000 inhabitantshoused mostly within concretemulti-storey flats. Urban developmenton this scale within the tundra ecosystemrequires a great deal of constructionactivity, which would import considerablequantities of cementdust and other particles, resulting in elevateddeposition of alkali-earth elements(Arslan and Boybay, 1990;Jalkanen et aL, 2000). It is thereforelikely that elementalconcentrations in soils within 20-30 km of Vorkuta do not reflect current depositionrates but are a historical legacyof greaterconstruction and industrial activity in the recentpast.

99 -0 r. 10 v

Gn -, r C,4 00 C) en CN kn

P .2

sl .-I 0 a CD CD b c) (D b

cli r-: 06 C-i -4 cli Ici (U 0 C> Cý C) C) W) t- ell 01,00 CD I r- 42N Itr C> 1ý0 C) 10 10 oo IR ý E (140ý o C'I 6 'o Cli Cli CD C-406 c; - c; c; C;: 6 c) c,

u C) C) 0 IRT C14 C) C) en Ei IR Oý "t "I C) Cý C) C) 0

Cl 110cý c)-4 C) C)tn C)00 1ý0 110m "S c) C5 Cl C) %: C'I 4 -66c; 14 0M --4 C5 C; C; .4-. 1 ý 0, -. ,

10 - 10 2 --, -n wl ý Wý --r -t rn m en m rlý el,, rn en en m en en lu - C) C) CD CD C> C) CD CD C) (D C> C> C> CD CD +C5 -4 2 0. 0 g in tn ý.o %.0 t t- >ý ON C'ý C14 C14 - ON Cr) = C) It Rt 0 Sý Cý Cý Co ej

4.4 m --, 0 ' t 4 - p c) en t- en Cý CD en til t- en CD Cý m c4 V) v5 ý tý 'R (=! -, tý -1 '1 'IR w! ý,ý -: --: ýR IR "-: 2. I t W-)T T TMC 4 'T t M cn I- IT to MMIn I --II CX5It'- Itn C)'4C t'- C)1 J: It'- W)It C>NT t'% r4 -IT C-i In .0 9 cr In %0 VI 10 -e W, ro) M ell en N en r4l IRt en Itr fn en 4) 'o-, 0 C5 C) C) Cl C) C) C5 C) 40 C) b C) Cl >b 9x >1 x xxxx9x xxxxxx . 00 Wl %0 Wl ON IT C'4 t- t- wl M en C> -i I: Cli (L) -4 u %0 Clq 'T t- U- I Ci C'i "i ý.i C'iCý -4 C'i 93 Aý ýo V) cq kn V) --t Cq mm kn -tt cn tn "t .t en en 44 .0 "U vi cl; 44 C-i C4 q -i '! 1- En 5 -0 ýf

U cn uto9.4 0 C14

ei *Z- 0

.M00 2= Cc 0 b-i ci (L) e - "o 0 (L)

0 C) ON ON ýt C) C14 en r- 0 C) It 00 tfl 00 OIN C) kn en a) 52 P .2

.09 IT T 17 .- > C) CD Cý C) C) (D Q CD -4ý -. C)4 4 4 . 0 -. v" -4 1" -4 _-4 -. -. rn -+-(4 C) Itt t- ýo 00 00 C14 kn W Cý l-; 116 -i Cý

C> ON C) %-0 ON 1-0 to Cý %,--4o 00--1 Nr- r- C> m W-) C) (I iqM en 00 C) -ci !ý

ON CD en CA Q W) r4 wl C14 oo-, c; Cý C; u0 c; c;

"0 cle t- tno 110 4nc> r c> 01)c., a., 1"C: ) -4-,t 4 00 en-, 'IT in -4 C, 00 .. 4 en -4 8 C; cs c; 0 ji 0 u

= "Ci - 1.1 . .2, "o n ýý ýr 't -* -t m en -ýr --t --t 't en en -* .t en en mm C5 Cý cl Cý C> C) C5 cl C5 C) C) C) Cý C, C) C5 40 C) ,;: -. 4 1-4 .42 ý4 "-4 -4 -4 1.4 -4 -4

" ci m ýo ýo cn en ir- t- enma c) 00 00 0000 -t 4 :t 4:r r- ý,- Cý Cý Cý Cý r-: rz r4 Cl e,; 'i -1:

4-4 o (C)a-ý f- en -0 ON t- m (D c) en lr- rn El IR olý ., t',: t, Iq OR .., t*,: IC! en Cý t, 0 -I in -! ý -I -I en *: -I tw C:) r C4 t tn tri t- ri t- tn c) r- - t- tn It en IT 'It M IT It q, M Ci It 11, IT , ci * *z:0 9 (L) wl m C) C) CD C> C> C) C> C> c6cz, CD 6 bb 6 C) C) C) -4 1-4 1-4 --4 V-4 1-4 v" V-4 -4 -4 " -, 2 "-1 V-4 " -4 1-4 >4 >4 x, >4 >4 x x >4 xxx >4 xx >4 >4 >4 x , r4 "C 0 ýo "D en cl r- en en cn C) ýo 00 "D 00 C> "t W) -t t- rn Ji -; Cý 'i .4 Ci -4 cl vi t--zJi r4 ,6 ci 44 c4

2

., ý N ") IT It N en IT qT en fn IRt qt .0 010 Ci -1:en ": q -4:ýq en en tl: W)--t Ci en(n V) q -1: 0 "0

CL, 0 It vi C14

0

.M02 In the Vorkuta region the prevailing winds blow from the southwestand south from Septemberto April (Virtanen et aL, 2002). In accordancewith the prevailing winter winds aroundVorkuta, the areawith the greatestconcentrations of elementswithin snow and soil was aroundat sites 1.3 and 1.4 which were located north-eastof the main emissionsources. It is clear that the sites most affectedby pollution in the Vorkuta region are found aroundthe main emissionsources, i. e. the cementfactory and the power plant (Kuliyev, 1977,1979; Kuliyev and Lobanov, 1978;Getsen et aL, 1994; Solovievael al., 2002; Virtanen et aL, 2002).

4.4. Conclusions

Resultsshow considerablelocal alkalisation in both the top-soil and snow-pack aroundVorkuta; in the vicinity of Inta alkalisationwas only apparentin the snow- pack. Deposition of coal ash aroundboth towns is mainly responsible,with possiblecontributions from a cementfactory locatedin Vorkuta and historical inputs from the major constructionphase of the city. Near pristine areaslocated more than 30 km from Vorkuta and Inta appearto be unaffectedby ashdeposition and are characterisedby acidity in both snow-packand top-soils. Sites along the entire transectthrough the town of Usinsk, which is suppliedby a gas-firedpower station,were nearpristine.

Tbere were elevatedconcentrations of Al, Ba, Ca, K, Mg and Sr in suspended solids and snow-packaround Vorkuta and Inta. Most of the depositionof elements commonly associatedwith combustionash, occurredin particulateform. There was evidencethat the concentrationsof soluble Pb, Cu and Zn in snow-packwere reducedaround Vorkuta, due to adsorptiononto alkaline ashparticles.

Extremely high elementalconcentrations of Ba and Sr in top-soils aroundVorkuta could not be explainedby current depositionrates. This discrepancymay be the result of greater coal mining and construction activity in previous decades.

102 CHAPTER 5. POLLUTION IMPACTS DUE TO THE OIL AND GAS INDUSTRIES IN THE PECHORA BASIN

5.1. Introduction

Reportedhere are the resultsof an investigationseeking evidence of environmentalimpact in the vicinity of a booming petrochemicalindustry in the Pechoraregion. This was achievedby quantifying the chemical statusof terricolousmat-forming lichens and top-soil, and by measuringalpha (a) biodiversity of epigealand epiphytic lichens in closeproximity to both putative pollution 'hot spots' and unpolluted 'reference' sites with a broadly comparablecommunity structures.The probableunderlying causalfactors are discussed.

The Pechoraregion, which includesthe north and eastof the Komi republic and a major portion of the Nenetsautonomous region, facesconsiderable challengesboth in terms of socio-economicdevelopment and environmental conditions(Lausala and Valkonen, 1999).The region is rich in non-renewable resources(e. g. minerals,coal, oil and gas),but the exploitation of coal is in decline due to its poor quality and high transportationcosts (Gimardi, 2002). In recentdecades the oil and gas industrieshave boomed and are expectedto expandfurther, bringing about significant risks of environmentalpollution.

Previously,the findings of the TUNDRA programmein the Usa basin, found evidenceof pollution on two geographicalscales. These were local emissions from coal combustionin Vorkuta and Inta, and long-rangetransport of pollutants from lower latitudes in Europeand industrial regions of the Urals. The work in this Chapterformed part of the SPICE project (Sustainable developmentof the Pechoraregion In a ChangingEnvironment and society) which then looked at the environmentalimpact of emergingindustries over a larger areaof the Pechorabasin. This investigationof potential terrestrial pollution was complimentedby work carried out by other groupswithin the

103 project. This included studieson aquaticpollution basedon analysisof surface watersand lake sediments,other indicators of biodiversity, including, avifauna, fish, invertebratesand cyanobacteria,and the geneticvariability of sprucein tundra forest islands.Partners within SPICEwere also examiningthe economy and society of the region by investigatingsocio-economic development, social perceptionof, and stakeholderinvolvement in the stateof the environmentand economiclosses of infrastructuredue to permafrostcollapse. The impactsof global changeformed an additional componentof the programme.These ecologicalassessments were undertakenat eight samplingsites, four of which were selectedclose to industrial 'hot spots' ('industrial' sites,FI i, F5i, F3i and 177i),and four were remotefrom industrial activity ('reference' sites,F2,, F6,, F4,,and F8, ) (Figure 2.2, Table 2.2). Details of samplingsites, sampling regimesand subsequentchemical analysis are given in Chapter2.

The variablesmeasured in lichens were: total N, determinedby Kjeldahl digestionand distillation following the methodof Bremmer and Breitenbeck (1983); major cations(Me+ by F-AAS; Ca2+and Ký by FES) and Pb by GF- AAS. In addition, lichen abundanceand speciesdiversity was determinedon epigealsin the tundra and epiphytesin the taiga. The variablesmeasured in top-soil included elementalanalysis of. - Ba, Ca, Cu, K, Mg, Mn, Na, Ni, Pb, Sr and Zn, undertakenusing GF-AAS and F-AAS and soil p1l which was measuredfollowing standardprotocols (seeChapter 2).

5.2. Statistical analysis

Unlessotherwise indicated, significant differencesbetween sites were determinedby one-way-ANOVA followed by Tukey's test (n = 18).

104 5.3. Results

5.3.1. Lichen material collected

Terricolous mat-forming lichens in the generaCladonla [Cladonia arbuscula or C stellaris] or Flavocetraria [F. cucullata] were widespreadand locally abundantin the Pechorabasin. At least one specieswas collected at eachsite (Table 5.1). Cover was generallypoor in the tundra due to grazing and trampling effects of reindeer,except for site F7i. The most completedata set for lichen chemistrywas obtainedfor C arbuscula,which was collected at all sites in this study. However, only small thalli were found in the tundra, due to heavy grazing and it was only possibleto measureN in the apical 5 mm. Flavocetraria cucullata was collectedof sufficient length to measure[N] at different strata.

Table 5.1. Terricolous speciesof Cladonia and Flavocetraria sampledacross the Pechorabasin at 'industrial' sites(e. g. Fli) and unpolluted 'reference' sites (e.g. F2,), together with elemental analyses performed (n = 18).

Tmnsect Species sampled Mapicei [Nlbase [Pbl [Ca 2+1 [K+] [Mg2+] _ Fli Cladonia arbuscula + + + + + lzhma river C stellaris + + + + + F2, C arbuscula + + + + + Kedva river C stellaris + + + + + F3j C arbuscula + + ý + Ortina river Flavocetraria cucullata + + + + + F4, C arbuscula + + + + Neruta river F. cucullata + + + + + F5j C arbuscula + + + + + Svetly Vulctyl F6,, C arbuscula + + + + + Malay Patok C stellaris + + + + + F7j C arbuscula + + + + + Upper Kolva, F. cucullata + ++ + + + F8, C arbuscula + + + + + Mareyu river F. cucullata + ++ + + +

+, analysis perfonned; -, no analysis

105 53.2. Total [Ca"j, ITC], [Mle'l and [Ph] in lichen tissue

Figure 5.1 showsvariation in the concentrationand concentrationratios of cationsin the apicesof Cladonia arbuscula, C stellaris and Flavoceiraria cucullata. There were somemarked and significant differencesbetween comparable'industrial' and.'reference' sites,e. g. site F7j comparedto site F8, in both C arbusculdand F. cucullata, and site F5j comparedto site F6, in C arbuscula.However, there was no consistentrelatioship betweendifferences in the cation valuesand proximity to perceivedpollution sources.There was however,strong covariation in lichen chemistry amongthe three species (Figure 5.2.a-e), suggestingthat differencesamong sites were due to different environmentalcircunistances as opposedto random variation with the data. Overall, potassiumconcentrations were generallyhigher in F cucullata than C arbusculd at all tundra sites.

Lead was selectedas an additional analytebecause it was one of severaltrace metalsfound to contaminatesnow and soils locally in the tundra aroundthe Vorkuta industrial complex (Chapter4). Whilst absoluteconcentrations are low in all speciesthere may be localised elevationof [Pb]api..,in C arbusculd and F. cucullata at site F7j (0.098 4: 0.008 and 0.143 ± 0.015 [tmol g", respectively) where concentrationswere 3-4 times greaterthan at site F8, (0.025 ± 0.004 and 0.04 ± 0.005 pmol g-1,respectively for C arbusculd and F. cucullata) (Figure 5.3). There between[Pb],, in C was a strongrelationship pi. arbuscula and concentrationsof Pb in soil ash ([Pb]. il h) (r2 = 0.834, n= 6).

106 Cladonia U. tiavocerraria 120 arbuscula stetiaris cucuitat. 7 (b) 100

4! ý 80 0 13 60 0 40 C4 20

0 ve3 (c) (d) 8 0

0 6 -. I eN +! 01 0 4 0

0 =L 2 0 0 5 ý if) cicu 0 4 1 cliC* +3 !,0 2 S + " o

0 'li F2r M F6r Mi Rr Pi F8 Fli F2r M F6r M F4r Pi F8 Taiga Tundra Taiga Tundra Sites Sites

Figure 5.1. Variation in [Ca2+],, (o, [Mg2+], (v, [Ký]. (w, pj. 0), pj,, 3 v) and pi,,, (a, b) [Ký] [Mg2+]api. (c, d) [W] ([Ca2+] + [Mj2+])8P, o) and the ratios : and : M (e, f) in Cladonia arbuscula, C stellarls and Flavocetraria cucullata. Filled

and open symbols indicate 'industrial' and 'reference' sites, respectively.

Plotted values are means ±1 SE, (n = 18).

107 (a) [Ca2+]. Pi,, (c) [KI. 0 P. e 12 20 =L 90 Z

10 16 80 4u 9 0 4E u ru

7n 4 zz 89 10 11 12 14 16 40 50 60 70

Concentrationin Cladonlaarbuscula (pmol g')

0

5 .2.

4

2.5 3.0 3.5 4.0 4.5 5.0 1.5 2.0 2.5 3.0 3.5

Molar ratio in Cladonia arbuscula

Figure 5.2. Relationshipsbetween Cladonia arbusculd and Flavocetraria cucullata in cation concentrationsand molar ratios at tundra sampling sites: (a) [C2j, i,,. (r = 0.988,P<0.01, n= 4); (b) [Mgý+]apj.,(r = 0.876, P<0.05, n= 4); (c) [Kjapi. (r 0.877,P<0.05, 4); (d) ([W]: [Mg2+]). = n= pj.. (r = 0.992, P<0.005, 4); (e) ([Kj: ([Ca2j [Mg2j))vj. n= + ý(r = 0.992, P<0.005,n= 4). Plotted valuesare means,(n = 18).

108 0.12 c

0.10 c

0.08

0.06 ab

0.04 d 0.02

0.00 n.d. n.d. Fli F2r F5i F6r FN Rr M F8r S Cladonia arbuscula ýo 0.16 a

0.12

0.08 c ab 0.04 A] [ n.d. n.d n.d 0.00 _I Fli F2r FSi F6r F3i Rr M F8r C stellaris F. cucullata Taiga sites Tundra sites

Figure 53. Mean concentrationsof lead in lichen apices.(a) Cladonia arbuscula; (b) C stellaris and Flavocetraria cucullata. Filled and open columns indicate 'industrial' and 'reference' sites,respectively. Plotted values are means±I SE, (n = 18); n d. = not determined.Significant differenceswere determinedby one-way-ANOVA followed by Tukey's test, sitesattributed with the sameletters were not significant and sites with different letters were significantly different at the P<0.05 level.

109 5.3.3. Total nitrogen concentration in lichen thalli

Values [N],, in Cladonia from 0.39± 0.03 g" (n of pi., arbusculd varied mmol 18) at site F3j in the tundra, to 0.60 ± 0.07 mmol g7l (n = 18) at site F5i in the taiga (Figure 5.4.a). Values were significantly higher at taiga than at tundra little [N],, in C sites (P < 0.001). There was evidence of elevated pi. arbuscula at 'industrial' sites with the exception of site F7j which had the highest values for the tundra sites and significantly greater than the value for site F8, Nitrogen concentration in basal strata of C arbuscula was not measured becausethalli were generally of insufficient length.

Total N in the apicesof C stellaris was measuredat three taiga sites (Figure 5.4.b) and found to be similar at each.Values rangedfrom 0.62 mmol g" (± 0.02) at site F2, to 0.65 mmol g" (± 0.01) at site F6, and were in the same rangeas thoserecorded at similar latitudesin the Usa,basin (Chapter3).

Values of total N in the apical (0 -5 mm) and basalstrata (35 - 40 mm) of F. in highest [N], cucullata are shown Figure 5.5.a. While the value of ýpj,,,was recordedat site F7i, the lowest value was also recordedat an industrial site in [N]ý, [NIbasein F (F3i). There were significant differences pj. and cucullata between'industrial' and 'reference' sites,but thesedid not provide any coherentevidence of pollution. Again the highest value of [N1bMwas recorded at F4, whilst the lowest value was recordedat site Pi. Values of concentrations and ratios were in the sameranges as thoserecorded in F. cucullata at similar latitudes in the Usa basin (Chapter3). There was a moderatedegree of C. in [N],, (r2 covariancebetween F. cucullata and arbuscula pic,,,values 0.692, n= 4). The ratio of [NIvi. : [NIbasein F cucullata was significantly higher at site F7j than at the other tundra sites (Figure 5.5.b).

110 (a)

0.6

0.4

0.2

0.0 Fli F2r F5i F6r FM F4r M F8r (b) Tundra a sites 0.6 z 0.4

0.2

d. 0.0 n. Fli F2r M F6r Taiga sites

Figure 5.4. Mean [N]. in Cladonia (a) C values of pi,., arbuscula and stellaris (b). Filled and open columns indicate 'industrial' and 'reference' sites respectively. Plotted values are means ±I SE (n = 18); n. d = not determined. Significant differences were determined by one-way-ANOVA followed by Tukey's test; values asigned the same letter were not significantly different at the P<0.05 level.

III 0.5

0.4

0.3

0.2 bd

0.1

0.0

(b) in b

F3i F4r M F8r Tundra samplingi sites

Figure 5.5.i Nitrogen concentration in Flavocetraria cucullata. (a), values of [N],, (0-0.5 > 0.4 [NIbasc (3.5-4 < 0.2 pi,,, cm, values mmol gý) and cm, values (b), [N]apjc, Mbe. Filled mmol gý). the molar ratio ý: and open columns indicate 'industrial' and 'reference' sites, respectively. Plotted values are means ±I SE (n = 18). Columns with the same letters are not significantly different P<0.001 level ([N]apic, the [N]. [N1base) P< at the and ratio pj,,,: or 0.05 level ([Nlbase)-

112 5.3.4. Soil analysis

The depth of the surface organic layer in sample quadrats varied between 0.5 and >5 cm. Top-soil pH (0-5 cm) at all sites was uniformly low, with mean values ranging from 4.03 (± 0.02), at site F7j (Kolva) to 4.88 (± 0.11) at site F2, (Kedva) (Figure 5.6). Generally, top-soils at tundra sites had lower p1l values than those at taiga sites. The lowest recorded mean top-soil p1l (0-5 cm) was 4.03 (± 0.02), at site F7j; this value was significantly lower than the value of 4.48 (:L 0.09) at site F8,, (one-way-ANOVA, followed by Tukey's test P< 0.001, n= 18).

Concentrationsof metal elementsin soil ashwere generally low at all sites in the study (Figure 5.6). Values for severalelements (Ba, Ca, K, Mg, Na, Pb and Zn) varied markedly betweensites. However, only Ba, Ca and possibly Ni, were elevatedat an industrial site: concentrationsof theseelements were significantly greaterat site F7jthan at site F8,, (one-way-ANOVA, followed by Tukey's test; P<0.001, n= 18). Mean concentrationsof Ba, Ca and Ni in soil- ash were 459 (193), 4225 (± 1074)and 43 pg g" (:L 3.1), respectively,at site F7j, whereas,background concentrations for the 'reference' site F8, were 41 4.6), 138 (± 16) and 21 pg g" (± 3.3), respectively.Figure 5.7 showsthat concentrationsof Ba and Ca in soil-ash,were highly positively correlated, whereasconcentrations of Cu and Pb were only weakly correlated,perhaps as a result of a single outlying datapoint. Sodium occurredin high concentrations at sitesF3i and F4,, probably due to the close proximity of thesesites to the Barentscoast, resulting. in marine inputs from sea-spray.

113 Taicra Tundra Taiga Tundra 5.2 - 600 - PH Ba 4.8 400

0' 4.4 200

4.0 13 0 Ca K 1200 4000

2000 600

11 9 0 41b 1 1 1 0 1T7 0 Cu 9 . Cd 0.4

6 0.3

0.2 3 0.1

=L 0 0.0 Mg Na 1 1 300 . 400 200 700 100

0 * 1 1 0 0 Ni Pb 0 60 0. .1i t . 30

Ei 40 15 20

0 0 Zn 6 30

4 20

2 10

A A Fli F2r M F6r FM F4 rM F8r F11 F2r M F6r F3iF4 rM F8r

Sampling site locations

Figure 5.6. Values of pH in top-soil (0-5 cm) and concentrationsof metallic elementsin soil ash. Filled and open symbolsindicate 'industrial' and 'reference' sites,respectively. Plotted valuesare means:LI SE (n = 18).

114 5000 F7 4000

I-N

3000

F5 2000

1000

A 100 200 300 400 500

[BaL. (P9 9-1) il h

30 (b) . 25 .

20

15

10

5 " "

n I II I 2345 67

ICUlsoil (1199'1) ash

Figure 5.7. Elementalcorrelations in top-soil ash samples(0-5 cm): (a) [Ba] and [Ca] (r = 0.997,P<0.001, n= 8), and (b) [Cu] and [Pb] (r = 0.748, P> 0.01, n= 8).

115 5.3.5. Lichen biodiversity

The abundanceand diversity of lichens differed significantly betweensites (Figure 5.8). Among the taiga sitesdifferences were small, with 'reference' sites having the lower values.Complete listings of epiphytic lichen species assessedon the trunks and branchesof Picea obovataup to a height of 1.7 m are given in Appendices1.1 - 1.4. The first record of Ramalina obtusatain the Komi Republic was madeat the Izhma river site (F I j) during June2001 (T. Prystinapers. com.).

Among the tundra sites,F7j had a markedly lower abundanceand diversity of epigealsand lower abundanceof epiphytes.Complete listings of epigeal lichen speciesand epiphytic lichen speciesrecorded on Betuld nana in eachplot are given in Appendices1.5 - 1.12.The effect of reindeergrazing and trampling were markedto severeat sites F3j, F4, and F8,, with F8r perhapssuffering the worst effectsbased on my own personalobservations (see Figure 5.11).

Mean abundanceof epigeal speciesat sites F7jand site F8, are comparedin Figure 5.9 for the-purposeof highlighting specieswith markedly different abundancevalues. Alectoria nigricans, A. ochroleuca,Bryocaulon divergens and Sphaerophorusglobosus were commonat site F8, but were poorly representedat site F7j. With the exceptionof Alectoria ochroleuca,these specieswere also well representedat F4,, althoughthis site was not chosenas a comparable'reference' site for F7j. Similarly, meanabundance of epiphytic speciesat sites F8, and F7j are comparedin Figure 5.10. Cetraria nigricans and Ochrolechiaftigida were commonat F8, but were poorly representedat F7j. Ochrolechiafrigida was also commonat F4,.

116 (a) Epiphytes in taiga a 4u ac liv b 30 30

11 11 20 20 a@ b ab MTM cd

10 10

Fli F2r M F6r

(b) Epigeals in tundra 60 C b 50 b 50

40 40 aa Z: 30 30

20 ab aI 20 E- 10 10

F3i F4r F8r

(c) Epiphytes in tundra

a aa 20 20

c b

10 b 10 a

n 0 F3i F4r F7i F8r Sites

Figure 5.8. Mean valuesof total abundance(left hand column) and total numberof lichen species(right hand column) at eachsampling site. Filled and open columns indicate 'industrial' and 'reference' sitesrespectively. Plotted , valuesare means±I SE (n = 5-9). Significant differenceswere determinedby one-way-ANOVA followed by Tukey's test; within eachmeasured attribute sites with the sameletters were not significantly different and siteswith different letters were significantly different at the P<0.05 level.

117 6 Car

5

Fn Cra

Cg Fc F1 Ca .0 Cst

Sp Cu Ccr I Cbo Ps Sa Pm Cocs Cb 0 Cc orrv

01234

Abundanceat site F8,

Figure 5.9. Comparisonsof meancover abundanceof epigeal lichen species betweensites F7j and F8,,.Species denoted as: (An),Alectoria nigricans; (Ao),A. ochroleuca;(Bd), Bryocaulon divergens;(Fn), Flavocetraria nivalis; (Fc),F. cucullata; (Fi), Cetraria islandica; (ca), Cladonia amaurocraea;(car), C. arbuscula; (Cb), C. bellidiflora; (Cbo), C borealis; (cc), C. chlorophaea; (ccr), C crispata; (cg), C gracilis; (co), C coniocraea, (ccr), C cornuta; (cra), C rangiferina; (cst), C stellaris; (cs), C subfurcala; (cu), C uncialis; (ie), kmadophila ericetorum; (of), Ochrolechiafrigida; (pm), Pelligera malacea; (ps), P. scabrosa; (sg), Sphaerophorus globosus; (sa), Stereocaulon alpinum; (sp), S. paschale; (Tv), Thamnolia vermicularis; (o), Cetraria nigricans, Cladonia cervicornis, Peltigera neckeri,Perlusaria correloides; (A), Cladonia pleurota, C sulphuring, Hypogymniaphysodes,Pertusariapanygra. Circled speciesdenotes those present at site F8, but were absentor rare at site F7j. Estimateswere madeusing the abundancescale of Kauppi and Halonen (1992): 7= >50%, 6 = 26-50%, 5= 11-25%,4 = 3-10%, 3= poor cover, < 3%, 2= little, many specimens,but not constituting any real cover, I= extremely little, only one or two specimens.

118 Ts 3

Pa r- : 14 Ph Hp VP

PS

.01 La Pd Mo An of Bs 0 r BdFi BfAOPCPCD Am

01234

Abundanceat site F8,

Figure 5.10. Comparisons of mean cover abundance of epiphytic lichen species between sites F7j and F8,. Species denoted as: (An),Alecloria nigricans; (Ao),A. ochroleuca; (Arn),Cetraria nigricans; (Bd), Bryocaulon divergens; (Bf), Bryoriafuscescens; (Hp),Hypogymnia physodes; (R), H. lubulosa; (La), Lecanora argentata; (mo),Melanelia olivacea; (of), Ochrolechiafrigida; (Ps), Parmelia sulcata; (Pa),Parmeliopsis ambýgua; (Ph), P. hyperopta; (Pc), Pertusaria coraffina; (Pco),P. coccodes; (Pd),P. dactylina; (Ts), Tuckermanopsis sepincola; (vp), Vulpicidapinastri. Circled species denotes those present at site F8, but were absent or rare at site F7j. Estimates were made using the abundance scale of Kauppi and Halonen (1992): 7= >5 0%, 6= 26- 3%, little, 50%, 5= 11-25%, 4= 3-10%, 3= poor cover, < 2= many specimens, but not constituting any real cover, I= extremely little, only one or two specimens.

119 5.4. Discussion

5.4.1. Chemical impacts on lichens and top-soil

The objective of the programmeof chemicalanalysis of lichens was to perturbationsin lichen chemistry at 'industrial' sitesthat might be causedby In increasesin [W1: [Me+1,, air pollution. particular, the ratios pi. and deposition [Kj: ([C2j+[Mgýj). pj. ý were soughtas evidenceof acid and increased N deposition(see [N],,pjýý values were soughtas evidenceof Chapter 3).

In general variation in lichen chemistry was either small or, if large, unrelated to industrial acitivity; for example the ratio [KIVg2lapices in C arbuscula varied across all eight sites by a factor of 1.9 and in F cucullata amongst the four tundra sites by a factor of 1.8. Hyvarinen and Crittenden (1996) found that [Kj: [Mej,, in C by factor 4 the ratio pj,;ý portentosa varied a of c. amongst sites in the British Isles. In the present work the strong covariation in the chemical indices between species suggeststhat these differences in cation contents reflected inter-site differences in environmental circumstances, as opposed to random variation. However, there were examples of both high and low ratios at both 'industrial' and 'reference' sites suggesting that air pollution was not a factor contributing significantly to variation.

Amongst tundra sites, values of [N]vi.. were greatest at site F7j and the value [N]. Nbase in F higher here of pje,: cucullata was sigiiif icantly than at other sites. Hyvarmen and Crittenden, (I 998a), demonstrated a strong relationship between N deposition and [N] in the mat-forming terricolous lichen Cladonia portentosa. Their study of the common heathland lichen C portenlosa in the British Isles, found [N] in 5 ([N]. ) in that the apical min of thalli pi,, and a deeper stratum 35-50 mm from the apices ([Nlbasc)were both significantly positively correlated, and the concentration ratio [N]apica: [Nlb&sewas negatively correlated, with N deposition. Since Ilywirinen and Crittenden (I 998a) found [N]. [Nlb&w be the concentration ratio pj,,,: to negatively

120 correlatedwith N depositionin C portentosa,the higher value of the ratio at site F7j is difficult to interpret; it may reflect a subtle physiological perturbation or simply randomvariation. Hyvarmen and Crittenden(1998a) reported that in by factor 1.9 in British [N]. pi. C portentosa varied a of among sites the Isles and Sochting(1990) found [N] in unspecifiedstrata of Cladonia sp. (sub- speciesCladina) to vary by a factor of 3.4 among severalEuropean sites. In the by factors presentstudy, [N]api.. varied of 1.1- 1.2 within biomes and 1.3 - 1.5 acrossall sites.

Coherentevidence of pollution was also generally absentin the soil metal concentrationdata acrossmost sites.Elemental concentrations within soil ash were generallylow. Exceptionswere markedelevations by Ba and Ca, and a small elevation in Ni, at site F7j. Contaminationof Ba and Ca might arise from dust blown from gravel roadsor building work where cementis handled. Concentrationsof Ba in soil ashtaken from sites closeto Vorkuta,were six times greaterthan thosemeasured at site F7j (seeChapter 4). Other apparent include high [Pb],, low chemicalanomalies at site F7j pi. and soil p1l.

Nitrogen concentrationin C arbuscula, C stellaris and F. cucullata at most siteswere typical of backgroundlevels at comparablesites in the Usa basin (Chapter3). For examplevalues of [N]vi. in C arbuscula and F. cucullata at tundra siteswere between0.4 - 0.5 mmol g" which comparesfavourably with backgroundsites at the extremesof the transectthrough Vorkuta. In C stellaris in valuesof [N]apimat site 176,were similar to values of [N]"pj,;e, this speciesat sites 3.2 and 3.1 at the southernextreme of the transectthrough Inta, e.g. 0.5 - 0.6 mmol g". Values of [Nlapicesin C arbusculd varied little within eachof the tundra and taiga locations,but were consistentlylower in the tundra. This reflects the trend observedin C stellaris collectedalong the south to north (Transects2/3) in Usa basin [NI. decreased transects the where pi. with increasinglatitude and decreasingannual winter precipitation (Chapter3). There are no data for N depositionaround site 177j,but gas flaring was observed at the industrial complex. Jaffe et al. (I 995b) reportedsignificant NO.,

121 emissionsfrom gasflaring operationsat PrudhoeBay and accordingly elevated valuesof [N]vice,in C arbuscula,and F cucullata, at F7i might result from local NO. emissionsdue to wastegas combustion at this site.

Kyt6viita (1993) observedthat exposureof the mat-forming lichens C stellaris and Stereocaulonpaschaleto simulatedacid rain resultedin significant [Ký]. reductionsin both [Ca2jpj,, ýand [Mgý']apj,,,s while pjce,remained unchanged.Kyt6viita (1993) suggestedthat the ratio ([W]: ([Ca2j+[Mgýj))apjce,in lichens might prove a sensitiveindex of acid exposure.Hyvarmen and Crittenden(1996) showedthat ([KI: [Mg1+])'PjMin C portentosa in the British Isles was positively correlatedwith precipitation acidity, while ([K+]: ([c2+]+[me+]))apj. was not. Around the city of Vorkuta, I found ([Ký]: [Mgý+])apjcý,to be elevatedin C arbusculd, while ([K1: ([Ca2j+[Mgýj))api. to be reduced.These trends were interpretedas responsesto alkaline ash deposition(see Chapter 3). In the Pechoraregion F7j lower F8, in both C ([Kj: ([Ca2j+[Mgýj)),, pjcesat site was than at arbusculdand F. cucullata. Thus, at site 177j,the marker ratio Ca-rich ([Kj: ([Ca2j+[Mej)). pj. might haveresponded to emissionsof particulatesfrom constructionactivities. Potassiumconcentrations were higher in F cucullata than C. arbusculaat tundra sites,comparing favourably with data from pristine sites in the Usa basin (seeChapter 3).

Lead concentrationsin the apicesof C arbusculd, C stellarls and R cucullata were low and comparefavourably with values recordedin terricolous mat- forming lichens at unpollutedtundra sites in the Usa basin (T. Prystina,pers. com.). They are below concentrationsmeasured at backgroundsites elsewhere in the Arctic (Puckett, 1978;Nash and Gries, 1995a;Riget et al., 2000; [Pb],, Bargagli and Mikhailova, 2002). However, slightly elevated pj,,. and [Pb],. il h valueswere recordedat site 177j.It is noteworthy that Garty et aL (1998) found elevatedconcentrations of Pb in Ramalina lacera at a site close to an oil combustionplant.

122 The meanpH values of top-soil in this study were all uniformly low and were comparablewith valuesreported at pristine sites in the Usa basin (Rusanova, 1995a;Chapter 4). At most sitesmetal concentrationsin soil-ashwere typical of thosefound at pristine sitesin the RussianArctic, measuredby Walker et aL (2003) in the Usa basin and Alexeeva-Popovaet aL (1995) on the Chukotka peninsula.One exceptionwas Na, where concentrationswere elevatedat sites, F3i and F4,, possibly as a result of marine inputs from the Barentscoast as sea- spray. Concentrationsof Ba, Ca and Ni in top-soil were highest at F7i, but Ba measuredat this locality was still lower than elevatedconcentrations measured at sitesclose to Vorkuta and Inta in the Usa basin (Chapter4). Elevated concentrationsof Ni in the vicinity of site F7i were probably the result of fuel oil combustionand gasflaring, which occursaround the Kolva site, (Vilcheck and Tishkov, 1997).In a study by Genoni et aL (2060), elevatedconcentrations of Ni were found in soil and mosssamples taken close to oil-fired power plants. It is likely that soils from site F7i, and those at other sites in this study, havenot beensignificantly modified and remain close to pristine, although previous studieshave documentedcontamination of soils from oil spills in the area(Rusanova, 1995b). It is doubtfid that soils at thesesites have beensubject to an oil spill.

5.4.2. Lichen biodiversity

There was no evidenceof deleteriousindustrial impactson epiphytic lichens at taiga siteswhile valuesof lichen abundanceand a-diversity were lower at industrial sites in the tundra,most notably at site 177j.However, interpretation of thesedata must take into considerationthe potential confoundingeffects of other man-madedisturbances such as forestry aroundthe industrial sites producing younger,more open forestsand reindeerhusbandry. Since little data exist on the pollution sensitivity of epigeal lichens, and the tundra sites were subjectto reindeergrazing, greateremphasis was placedon data for epiphytic speciesfor which more information exists on pollution sensitivity. In addition, it should be noted that the cover abundancescale used in this work was

123 subjectiveand non linear, potentially over emphasisingthe importanceof specieswith low abundancescores.

The abundanceand a-diversity of lichens varied significantly betweensites. Among taiga sites differenceswere small, with 'reference' sites having the lower values.Site F7i, appearedto be lessdisturbed by reindeer.This might be becauseroads and pipelinesrestrict the movementof reindeerherds, or because reindeerherdsmen avoid industrial siteswhere the occurrenceof discarded debris on the tundra can injure animals (0. Harbeckpers. com.). The epigeal lichens here formed much deepermats, and hencegreater biomass but comprisedfewer species(Figure 5.1lb). By contrast,sites 173i,F4, and F8, had more epigealspecies, and hencegreater diversity, but low biomassdue to heavy grazing and trampling by reindeer(Figure 5.11a). Crittenden(2000) gives a detailedreview of lichen growth and the impacts of trampling and grazingby reindeer.In the shrubtundra eastof Vorkuta mat-forming lichens were largely eliminated from the ground cover, as Crittenden(2000) found C arbusculd at most sitesbut usually only in trace quantities,possibly due a combinationof efficient grazing as well as trampling. Manseau.et aL (1996) also reporteddamage to epigeallichen communitiesin tundra usedby migratory caribou in northern Quebecand Moser et aL (1979) madesimilar observationsat Anaktuvuk Passin the Alaskan tundra.'Me problem of lichen cover depletion dueto reindeeris widespreadin the Russiantundra (Ahti and 6ksanen, 1990;Vilchek and Tishkov, 1997;Forbes, 1999;Klein, 2000).

124 -Awl* .--- -

(a)

(b)

Figure 5.11. Reindeer impacted terrain at Mareyu River (F8, ) (a), in contrast to the lichen rich ground cover in tundra at upper Kolva River (F7i) adjacent to the oil recovery site (b). (Photos: P. D. Crittenden).

125 It is not known why there were more epiphytic speciesat site FIi than at the 'reference' site F2,, or why the sum of abundanceof epiphyteswas significantly higher at site F5j comparedwith site F6, All are lowland taiga sites,but FIi is situatedat a distanceof approximately 10 kni from petrochemicaloperations, principally oil processing,located aroundUkhta (Komi's third largesttown) and the nearby gasprocessing operations in Sosnogorsk.Site FIi is also affectedby forestry, which has left the taiga in this areafragmented, with forest standsof different ages.Svetly Vuktyl (F5j) is almost exclusively characterisedby its gasextraction industry which accounts for more than 95% of all industrial production in the area,and a small timber industry (Gimadi, 2002). However, lichens in the generaUsnea and Bryoria (seebelow) were presentat this site, and site FIi, presumablycurrently unaffectedby emissionsfrom the local oil and gas industries.If potential sourcesof pollution exist here,there may be a time lag before eventhe most sensitivespecies begin to decrease,possibly over severaldecades. These speciesare known to be pollution sensitive(Hawksworth and Rose, 1970; Kuusinenet aL, 1990; Oksanenet aL, 1990;Aamlid and Venn, 1993;Pirintsos et aL, 1993;van Dobbenand ter Braak, 1999).For exampleKauppi and Halonen(1992) found that the most S02 responsiveepiphytic lichens around Oulu, northern Finland were, Plastimatia glauca and Usneafflipenduld, togetherwith Bryoriafuscescensand B. capillarls. Kuusinenel al. (1990) and Hyvarmenet aL (1992) found that thesespecies also tendedto favour older forest stands.

Factorsother than air pollution affecting epiphytic lichen abundanceinclude climate and standage (Kuusinenet al., 1990;11yvdrinen et aL, 1992).Site F5i comprisesfragmented lowland taiga, whereassite F6, is pristine old growth taiga, protectedin the Yugyd Va national park in the foothills of the pre-Polar Ural mountains.Furthermore, the annualprecipitation in the Urals is higher than in lowland taiga (Christensenand Kuhry, 2000; van der Linden and Christensen,in press). The standage of the forest at F6, is greaterthan parts of the fragmentedforest of F5j (T. Virtanen,pers. com.). Trees of similar size

126 were selected to restrict samplingto lichen communitiesat broadly comparablesuccessional stages (Stone, 1989).11yvarinen et aL (1992) found that Bryorlafuscescenswas commonin all types of stand,whilst speciessuch as,A capillaris prefer older or denserstands. Both B. capillaris and R fuscescenswere abundantat site F5i. Accordingly, differencesin lichen abundancebetween the two sitescould be due to regional variation in precipitation and impactsof forestry. I

Epigeal lichen F8, F4,, but IF-IP species which were present at sites and were absent or poorly representedat site F7i, included speciesthat are known to be pollution-sensitiveaccording to McCune and Geiser(1997) and Gilbert (2000) viz. A lectoria nigricans, Bryocaulondivergens and Sphaerophorusglobosus.

5.5. Summary and the broader context

Data presentedhere for lichen and soil chemistry,and for lichen diversity suggestthat the effects of pollution at the industrial sites examinedwere generallybelow detectionlimits. An exceptionis site F7i where a suite of minor shifts in environmentalchemistry and lichen abundancemight be an early signatureof industrial activity.

Other aspectsof environmentalchemistry (Table 5.2), and componentsof biodiversity (Table 5.3) were examinedat the sameeight locationsby other collaboratingresearch groups in the SPICEprogramme. Data on environmental chemistry (Table 5.2), provide additional evidencethat emissionsat 177ican be detectedin the environment.These include polycyclic aromatic hydrocarbons, Hg and As in lake sediments.Several signals were noted at Mi but mostly could be explainedby global or natural sources.Table 5.3 summariscsthe resultsof a rangeof biodiversity assessmentswhich again identifles site F7i as the most putatively impactedlocation.

127 00C4 V--4

A 9Z4 -Z Q. 'ý Q4 Q. rq -Z ýi , r3 j..r ±2i 9:4 wi ed > Qci =ce > > t:: g 7u ce 93 -g (9 r_ g . .2 0 Gn u2

(J Z

:D i

Cd oq Z e ' ro + d,d a 9 :i u2

0 9 0 FA-4 t 1 ý + ý-3 e e 9 wo . - - 0 + ,-0 0 &) -6ý ZJ 1 4)-010 :i, r. + -0 v0 + 9 e lý ci 8 + CD ID , r. t:. u .2

> + + eý > Z+

"0 0ý0 -0 ý ýo -, iz Gn a AKw4 td giCd ei (dgi to53 e 9 0 Ei gi d - 1 . , 0 2 Ci ca cd = ý a c e 9 ý A :31 Z+ . . . :i :10 9 10-0 10-, ti ci0 v

> -A tý Ui gl .0 u; J du JL, >> 0 ;Z e u el -i - * l , -6.- iz 'zý eS : Z as

> 150

m t4 [A 0 44 -4 4. W 04 10.4 914 pq A4 04 44 9w 09 c5

ÖD

0+

lz+ 0

"Ci

0 ZU ,Ki i 2A ýf liVý

0 JM

9 11 n ..to

c 0 1:1 A .0 0 ýira, . 9 ýr .9 > .0 ZS :a t2 Ra's e -2 .0, > o. . 0 VCt .0 g A 0 o o (9 10 E-4 ? 1 + C4 CHAPTER 6. CONCLUSIONS

This work aimed to assessthe extent of acid and alkaline and metal deposition initially in the Usa basin and then subsequentlyextending more widely over the Pechoraregion. The extent of contaminationwas assessedby mapping spatial variation in the chemicalcomposition of snow, lichens and top-soil. In addition, differencesin lichen biodiversity were soughtbetween industrial and backgroundsites in order to yield information on air pollution impacts.

The major findings of the chemicalanalyses of terrestrial ecological materials collected in this study,provided evidencethat large areasof the Usa and Pechorabasins remain in a condition closeto 'pristine' (Chapters3 and 4). Even when new industrial sites were comparedalongside non-industrialised referencesites, there appearedto be little difference in the measuredvariables in both this study and thoseby other groupsworking within the SPICE programme.Any contaminationthat was found was largely confined to local sites,whereas, at sites remotefrom towns there was little supportingevidence of pollution; for example,around Vorkuta meanconcentrations of Ba and Sr in soil ashwere 2.78 x 103pg g-1and 1.31xI 0ý pg g", respectively.By contrast, concentrationsfor the backgroundsite were 3.09 x 102pg g*1and 22.6 pg g" respectively.This becomesparticularly apparentwhen levels of contamination in the Pechoraregion are comparedwith thosereported by Reimannet aL (2000) on the Kola Peninsula.Here, Ba and Sr in soil were 1.13 x 105Pg g4 and 2.68 x 105pg g-1respectively at sites close to Monchegorsk.The backgroundvalues of measuredvariables in this study were broadly comparablewith thosereported by Alexeeva-Popovaet aL (1995) from the ChukotkaPeninsula and by Rovinsky et aL (1995) in the Ust-Lena reserve, both considereduncontaminated areas of the RussianArctic. From a chemical standpointmuch of the Usa and Pechoraregion remainslargely unmodified by pollution and reflects backgroundconditions and concentrations,which further emphasisesthe needfor environmentalprotection where future industrial exploitation is likely.

130 Over the Usa basin pollution gradientswere found on two geographicalscales. The first was a latitudinal gradientin the depositionof nitrogen (N) and by decline in [N]. in sulphur (S), indicated a northwards pi. mat-forming lichens and winter depositionof nsSS042-. This probably results from long- rangetransport from outsidethe region by northward-movingair masses originating from industrial regionsof the Urals and WesternEurope (e. g. Rahn, 1982;Ryaboshapko et aL, 1998).Ryaboshapko et aL (1998) usedNO., emissiondata to model depositionloads over Russia.They predicteda gradient of N depositionover the Komi Republic varying very broadly from 500 to 200 in [N],, here for Cladonia mg N m-2y-1. The gradient pj,,, reported stellaris on the Inta transectsis consistentwith, althoughnot proof of, such a deposition gradient.There may also be somecontribution from more widely dispersed emissionsfrom local sources;for example,Shahgedanova and Burt (1994) suggestedthat the annualmean atmospheric concentrations of N02 in Vorkuta are the highest of any town in theRussianArctic. The secondgradient is due to depositionof alkaline and metal-rich particulatesextending to 25-40 km aroundthe coal-burningcentres of Vorkuta and Inta with associatedchanges in vegetationcover (Virtanen, et aL, 2002), lake chemistry (Solovievaet aL, 2002) and soil metal loading (Chapter4).

Definitive evidenceof increasedN and S depositionrates over Arctic regions has come from the stratigraphicanalysis of ice corestaken from the Greenland 2- ice sheet;for example,N03' and SO4 concentrationsin surfacefirn are twice as great as thosein ice depositedprior to the industrial revolution (e.g. Brimblecombeand Stedman,1982; Neftel et aL, 1985; Rodheand Rood, 1986; Fischeret aL, 1998).The baseline[N03.1snow values observed in the present 1, [nssS042] surveywere c.9.2 [Lmol1: and snowvalues on transects2/3 were between4.0-5.2 timol Ul. Using as a multiplier total annualprecipitation valuesat eachsite modelled by van der Linden and Christensen(in press) yields annualdepositions in the rangesof 56-123 mol N ha7ly"' and 29-65 mol nssSha7l y". Thesevalues can be comparedto publishedestimates of critical

131 loads for N and S in Subarcticand Arctic ecosystemsbearing in mind that N03' depositionmight be lower than total N depositionby a factor of at least two. Hornung et aL (1995) proposedthat the critical load for N in Arctic and alpine heathlandswas in the range375-1071 mol N ha7ly" while, on the basisof N fertilization experimentson Svalbard,Gordon et aL (2001) suggestedthat the critical load value is likely to be towardsthe lower end of this range.Bashkin et aL (1995) producedcritical load mapsfor N and S over northern Siberia where the most sensitiveecosystems have critical load values<50 mol ha7lY' for both N and S but with many areaswith values in the range 51-100 mol ha7l f 1.Bashkin (1997) producedcritical loads mapsfor EuropeanRussia suggestingthat c. 50% of Subarcticand Arctic areashave critical loads for N in the range0-200 mo'l ha7ly"'. While for S, only 2% of the region had a critical load in the 0-200 mol ha7lf1 range,and 31% of the region had valuesof 200- 500 mol ha7lY". Lien et al. (1993) reportedthat the most sensitivesurface waterson Svalbardhave a critical load for nssSof between59-309 mol ha7lf 1.

The ecological effects of low acid depositionloads in the Arctic remain uncertain,but there is concernthat enhancedN depositionin particular could force ecological changein otherwiseoligotrophic N-limited ecosystems (Chapin and Bledsoe, 1992;Nadelhoffer et aL, 1992;Robinson and Wookey, 1997;Nasholm et aL, 1998;Tybirk et aL, 2000). The most pronouncedimpacts of 'acidification' have beenseen closer to emissionsources in industrialised regionswhere therehave beenmany documentedexamples of environmental damagedue to acidification and eutrophication(J6nsd6ttir et aL, 1995; Woodin, 1997;Gordon et aL, 2001). Increasesin N depositionin the Arctic may be particularly critical becausethere may be both direct and indirect effects (Walker et aL, 2001). Direct effects could changespecies composition and soil function, and indirect effects due to acidification, where this could significantly increaseN concentrationsin surfacerunoff waters,as soils and vegetationlose their buffering capacityover time (Williams et aL, 1998). Clearly there is still uncertaintyabout critical load valuesbut current knowledgesuggests that N depositionover the Usa basin could alreadyexceed

132 the critical load in someecosystems. Predicted ecological changedue to N pollution is in the samedirection as climate forcing e.g. it will promote expansionof shrubgrowth in tundra (e.g. Paal et aL, 1997)and a possible reduction in terricolous lichen biomassin high-latitude ecosystemsdue to competitive exclusion (Cornelissenet al., 2001).

There is discussionin the literature as to whetherN pollution is already increasingthe productivity of boreal forests(Nadelhoffer et aL, 1999). D'Arrigo et al. (1987) and Myneni et aL (1997) observedan increaseat high northernlatitudes in the normaliseddifference vegetation index (NDVI), which is strongly correlatedwith photosyntheticcanopies (i. e. leaf areaindex). Increasedgrowth of boreal coniferousforests would contribute to feedbacksto global warming due to increasedC storage(negative feedback) and reduced regional albedo(positive feedback)(Brooks et aL, 1997).Greenhouse gas inducedglobal warming is predictedto be most pronouncedat high latitudes (Keeling, 1996).This is possibly evidencedby markedincreases in the late winter and early spring temperaturesduring the last 100years in Siberia reportedby Briffa et aL (1995). IPCC (2001) predicts a 6-10 *C warming over the next 50-100 yearsin this region, with consequencesfor infrastructure damagedue to permafrostmelting and collapse(N. Karstkarelpers. com.). Damageto permafrostmight also increasedue to the use of vehicleson tundra, and constructionof roads,buildings and other installations.Therefore, extensiveoil, gasand mining operationsin the Arctic could potentially result in local effects on biodiversity and ecosystemfunctioning. Although, these disturbancesmight be small, their impactscan be far reachingbecause of the considerablelength of roadsand pipeline systemsassociated with them (Walker et aL, 1987).

Around Vorkuta there was pronouncedlocal pollution associatedwith alkaline particulatesand metal depositionand probably phytotoxic gases(e. g. NO.,and S02). This is the result of coal combustionwhich commencedon a large scale in the 1930's and is evident from increasedsoil metal loadings(Chapter 4), the

133 chemistryof lake sediments(Solovieva et aL, 2002) and changesin tundra vegetation (Virtanen, et aL, 2002).

Annual coal productionpeaked here at 20 x 106tonnes several decades ago and there was a commensurateincrease in coal combustion(Virtanen et aL, 2002). This suggestionis consistentwith the stratigraphiesof spheroidalcarbonaceous particle (SCP) concentrationsin lake sedimentsin the Vorkuta region described by Solovievaet aL (2002) which showedpronounced concentration maxima at a depthof c.5 cm below the sedimentsurface. The high soil metal loadings found locally aroundVorkuta provide supportingevidence for sucha historical changein Vorkuta's pollution climate becausethe quantitiesof metalspresent are too greatto be explainedby current depositionrates (Chapter 4). Sulphur dioxide emissionsfrom Vorkuta,(currently 37 x. 106kg) also declined markedly sincethe 1980s.

There is now compelling evidencethat pollution has causedlarge scale ecologicalchange in the vicinity of Vorkuta. Vegetationclassification studies by Virtanen et aL (2002), using satellite data and ground truthing plots, concludedthat there is an increasedabundance of willow and reduced abundanceof dwarf birch and other shrubsin tundra surroundingthe city. Two impactedzones were recognised(Figure 6.1), defined as a 'polluted zone' (150-200km2) and a 'slight pollution or disturbancezone' (600-900km2 ). In the most severelyimpacted zone, lichens appearto have beenlargely replaced by mossesand grasseswhich were relatively abundant(Virtanen et aL, 2002).

134 "

" Fr . '. I... _ J4 :

Field plots (dSIUFbWCO Class)

Ilk Non-knpact*d

I ofsttffbtd

Mkw, Ill pobAin

0 Major poluNon

"Raboad

Polluted Disturbed Tall shrub tundra Willows complex Low shrub tundra L_j I-Khea tundra Meadow Wetlands Bare sod. rock Water Field Urban

(a), Figure 6.1. Landsat image classification for the whole Vorkuta region (b). Reproduced trom Virtanen classification around the main emission sources the et aL (2002) with kind permission of authors.

135 The causalagent(s) may be one or a combinationof different componentsof the pollution climate (i. e. alkalisation,heavy metal deposition,eutrophication and phytotoxic gases)(see Chapter 4). Virtanen et aL (2002) considerthat alkalisation due to particulatedeposition is the most likely primary causeof the vegetationchange. In addition, the depositionand accumulationof black particulateson the surfaceof snowpackaccelerates spring snow-melt due to a reduction in albedo.Note that advancedsnowmelt is unlikely to have been causedby freezing point depressiondue to pollutants sincethis was estimated to be very small, (<0.001 'C in all cases).Evidence for such an effect comes from satellite images,showing snow free areasaround Vorkuta and snow coveredtundra in remoterregions in June(Virtanen et aL, 2002). Earlier spring thaw could haveboth positive and negativeeffects (e.g. longer growing season and increasedexposure to frost, respectively).However, the changesin vegetationaround Vorkuta are similar to thoseobserved by Paal et aL (1997), who reporteda shift in the Norwegian alpine Betuld nana community in responseto elevatedN deposition.Nitrogen pollution in the Vorkuta areawas evidencedby higher values of [N]Iichenand [organic N]snow(data not presented) suggestingthat fertilisation could indeedhave contributedto the 'Vorkuta effect'. It is not known to what extent the modified vegetationis a relic of a former and more severepollution climate in this region.

higher The soil pH valuesaround Vorkuta correlatewell with [Ca]...... and concentrationsof particulatesin snow. This indicatesan important role for ash input from coal combustionand cementdust in regulating snow and soil pI I. Potentially, a reduction in fly ash and cementdust emissions,with a resultant progressivedrop in pH, could meansolubilization of accumulatedheavy metals(Reimann et aL, 1996;Haapala et aL, 2001). Increasedheavy metal concentrationsin solution would have wider implications, due to leaching into surfacerun-off water and other aquaticenvironments. Robb and Young (1999) found that large additionsof calcareous,metal-rich, fly ashto acidic soils increasedsoil pH to the extent that metal ion concentrationsin the soil solution were reduceddespite an increasedtotal metal loading to the soil from the ash.

136 Sucha scenariois possibleif the decline in the Vorkuta coal industry continues.

Chemicalcontamination around Inta was similar in type to that at Vorkuta, but on a smaller spatial scale.Near pristine areaswere locatedc. 20 kni from the centreof Inta, where there was little evidenceof ash depositionand where both snow-packand top-soils were characterisedby acidity. However, unlike Vorkuta, there was no evidenceof vegetationchanges, possibly because(i) emissionsfrom this sourceare considerablysmaller than thosefrom Vortuka (Stateof the environmentof the Komi Republic, 1992-98)and (ii) Inta is in the forest-tundrazone where impactsmay be lessapparent from satellite data.At the smaller industrial sitessubsequently examined in the SPICEprogramme chemicalcontamination and modification to lichen communitieswere barely detectable.A small pollution signaturewas detected,however, at the Upper Kolva River site (177i)where oil and gasoperations produce gas flares. Here, a suite of minor shifts in environmentalchemistry and lichen abundance(which are in broad agreement)were recorded.These included marked elevationsof [Ca], from dust blown from [Bal,. il and oilpossibly arising gravel roadsor building work where cementis handled.However, [Ba],. il valuesat site 177i constitutedonly 17% of thoserecorded around Vorkuta. Other apparent chemicalanomalies at site 177iincluded high [Pb]lihýnand low soil pH values. In other characteristics,soils at F7i and at the other industrial sites examinedin SPICE (Fli, Bi and F5i) were closeto pristine. Although Rusanova(1995b) documentedcontamination of soils from oil spills in the area,it is unlikely that sites examinedin the presentprogramme have beenaffected by spills. All sites along the transectthrough the town of Usinsk, which is suppliedby a gas-fired power station,were near pristine, showing backgroundconcentrations of the majority of metalsand anionsmeasured.

An additional objective of this study was to producea benchmarksurvey of chemical contaminationin the Pechoraregion, againstwhich effects of future developmentscan be assessed.Oil and gasreserves in the Timan-Pechoraoil

137 province (currently the third most important oil producing region in Russia), are of global significanceand havethe capacityfor considerablegrowth (Lausalaand Valkonen, 1999;Pelley, 2001). Whilst the coal industry in the region is in gradualdecline (Gimardi, 2002), it seemsinevitable that activities such as gas flaring, and heat and power generationassociated with gashydrate recovery,will proliferate during the coming decades.These activities have the potential to increaseatmospheric emissions, including thoseof NO,, which would contributeto backgroundN deposition(Woodin, 1997) and eutrophication(Tybirk et al., 2000).

Gas flaring is likely to increase at the Upper Kolva River industrial complex and increase NO., emissions. Gas flaring is undertaken at oil and gas production facilities where there is no market for excess or waste gas and also for reasons of safety to avoid excessive pressure build up during temporary shutdowns. The importance of this activity as a source of NOx is illustrated by the fact that, gas flaring at offshore platforms around the British Isles combusted 2.4 million m3 of gas and emitted c.4% of the total UK NOx emissions (Environment Agency, 1998). Also, flaring at the oil and gas operations at Prudhoe Bay, Alaska, has been estimated to emit annually between c. 12 x 103tonnes NO,, and c. 14 x 103tonnes C114(Jaffe et aL, 1995b). Jaffe et aL (I 995b) reported that, given appropriate wind directions at Point Barrow, Alaska, elevated concentrations of NO,, could be detected for up to 48h in air massesarriving from the oil development at Prudhoe Bay, located 300 km to the east. Improved technology and gas re-injection should be considered as an alternative to flaring.

Oil and gasrecovery is associatedwith other environmentalrisks in addition to air pollution. Local impactsinclude an increasedfrequency of oil spills. For exampleit has beenestimated that 7-20% of extractedoil is lost annually through accidentson oil pipelines in Russia(e. g. Vilchck and Tishkov, 1997). Improved technologiesand maintenancewill be necessaryto reducethis loss (Pelley, 2001). Future oil and gasexploitation in this region could utilise

138 remote sensingtechniques such as thoseused on the Kola Peninsulaby Rigina et aL (1999), where it would be possibleto assessbiodivcrsity and ecosystem sensitivity to oil spills.

Oil and gas industriesare not the only activities that are poised for development.Those proposed include a pulp and paper factory, a coal-burning power plant in Inta, an oil and titanium complex, an aluminium plant in Pechora,a seaterminal in Na:ijan-Mar, a manganesemine, expansionof eco- tourism in the Yugad-VaNational Park and new tundra oil and gas fields. Oil and gasproducts in the region will supply the energyfor a plannedrefinery near Ukhta to producealumina using bauxite mined from the recently discoveredTiman bauxite deposit (Cottrell, 2002). An aluminium plant proposedto be built at Pechorawill require electricity for the electrolytic process.If hydroelectricpower is usedto operatethe plant then this will result in minimal regional pollution. If, however,a gasdriven power station is built then it will contributeto regionalNO. emissions.Aluminium refining also brings about new toxicity problems,such as fluoride contamination.An aluminium plant on the island of Anglesey (UK) has causedsevere damage to lichen communitieswithin a radius of 10 km (Perkins, 1992).Therefore, a restriction on reindeergrazing may be necessarywithin a local areaaround the new plant in Pechora.Fluoride pollution also reducestimber quality making it structurally weakerand less suitablefor use in constructionand pulping. However, it shouldbe emphasisedthat inadequatepollution control measures could result in spatially more extensivepollution. The region thereforefaces considerablechallenges both in terms of socio-economicdevelopment and with it, the addedrisks of environmentalpollution.

Another objective of the current research was to further evaluate the use of chemical markers in terricolous lichens as indicators of nitrogen and acid deposition. Hyvltrinen and Crittenden (1998a) observed that N concentration (most notably, [Nlbase)in Cladoniaportenlosa in British heathlands was positively correlated with N deposition. In the Pechora region there were

139 markedvariation in [N]li,,hc,. which correlatedwith either measuredor putative pollution gradients.In this caseit was valuesof [N]. pjC,',' that showedthe strongestspatial relationships(e. g. with latitude). The lack of responseof [N]Vj"', at industrial sites examinedin the SPICEprogramme (see Figures 5.4 and 5.5a, Chapter5) was consistentwith other pollution indicators examined both in this presentwork and in that of collaboratinggroups (seeTables 5.2 and 5.3, Chapter5). Theseresults demonstrate the potential of mat-forming lichens as coherentindicators of N deposition(Hyvdrinen and Crittenden, 1998a).Ratios of [K+] to divalent cationsin the apicesof mat-forming lichens, proposedby Hyvarmen and Crittenden(1996) to indicate precipitation acidity, showedpronounced responses to the pollution climate of Vorkuta. However, thesewere interpretedas effects of enhanceddeposition of cationsand not a responseto acidity. Clearly, measurementsof cation ratios when usedto seek evidenceof acid precipitation must be interpretedwith caution. Elsewherein the Pechoraregion, remote from the confoundinginfluence of particulate deposition,there were no spatialpatterns evident consistentwith gradientsin acid deposition.

It is noteworthy that the searchfor pollution impactsusing lichen abundanceas an indicator was also confoundedin the tundra, in this casedue to de- vegetationby heavy reindeergrazing (seeFigure 5.11, Chapter5). The tundra regionsexamined in both the TUNDRA and SPICEprogrammes are known to be busy 'thoroughfares' for reindeerherds (0. Harbeck,pers. com.). Oksanen et al. (1995) suggestthat the combinedecological effects of reindeergrazing and air borne pollution causesdegradation of terricolous lichen pasture,which may influence soil temperature,moisture, microbial nutrient cycling, and frost hardinessof plant roots.

Data presentedhere for snow, lichen and soil chemistry, and for lichen diversity suggestthat the effects of pollution at many sites examinedwere generallynear to or below detectionlimits. Exceptionswere Vorkuta and to a lesserextent Inta and the Upper Kolva site (F7j). The semi-pristinenature of

140 much of the Pechorabasin suggestedby data documentedin this thesis,will meanthat increasedpollution loads should be readily detectedwith a high degreeof sensitivity, due to favourablesignal to noise ratios. Therefore,future re-assessmentsof chemicalcontamination will be highly desirablesince, as is clearly demonstratedby the 'Vorkuta effect', where changesin vegetation becomevisible only after profound damagehas alreadyoccurred. Accordingly, the resultsin this thesiswill help with future monitoring in the region and provides essentialbaseline data, against which future deteriorationcan be compared.

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168 ACKNONMEDGEMENTS

I would like to thank Dr PeterD. Crittendenand Dr Scott D. Young for their tirelesshelp and supervision.I would also like to thank Dr PeterKuhry (Arctic Centre,University of Lapland) for co-ordinatingboth the TUNDRA and SPICE projects and useful discussions.I am particularly indebtedto my family for their overwhelmingsupport during the last four years.Special thanks are also extended to my lab and coffee colleagues,Gareth J. Murtagh, Nicola Case,Amelia P. I Junt, Carl J. Ashcroft, ChristopherJ. Ellis and FabianA. Seymourfor their friendship and support.Thanks also to DeboraIglesias-Rodriguez for constructivereading of this thesis.

I am especiallyindebted to Dr Hao Zhang(Lancaster University) for performing ICP-MS analysesand to Dr. J. N. Capefor organic N determinationson snow- melt samples.I would like to thank all of my Russiancolleagues at the Institute of Biology - Komi ScienceCentre (IB-KSC), Syktyvkar for their friendship, generosityand hospitality. Specialthanks to Tarmo,Virtanen, Kari Mikkola and Ari Nikula from the Finnish ForestResearch Institute and to Elena Patovafrom IB-KSC for providing me with the satellite image of Vorkuta. I also wish to thank all of the partnersof the TUNDRA and SPICEprojects for their companionshipin the field and who provided help with logistics and fieldwork especially;Vasily Ponomarev,Boris Kondratenok,Tatyana Prystina, Olga Lavrinenko, Anatoly

Taskaev,Inna Rapota(Institute of Biology - Komi ScienceCentre). I would also like to thank the rest of my many colleaguesfrom TUNDRA and SPICE; Viv Jones,Nadia Solovieva,Otto Habeck,Pieffe-Andr6 Forest,Osmo Ratti, Timo, Koalainen, Sandravan der Linden, Margriet Huisink, Nanka Karstkarel,Juha Heikkinen, Vladimir Dauvalter,Seija Kultii, Matti Eronen,Pirita Oksanen,Jens Christensen.Special thanks are extendedfor help with F-AAS and GF-AAS analysis,which was kindly provided by Dr. Andy M. Tye and John Corrie.

This investigationwas a componentof the TUNDRA and SPICE projects. TUNDRA was supportedby the Envirorunentand Climate Programmeof the

169 EuropeanCommission (contract number: ENV4-CT97-0522) and SPICE was supportedby the INCO-COPERNICUS2 Programmeof the 5"' Frameworkof the EuropeanCommission (Contract number: ICA2-CT-2000-10018).

170 APPENDICES

171 Appendix 1.1. Epiphytic lichen speciesand their cover abundancerecorded on Picea obovataat site FIi (Izhma river).

Species Fl, Izhma river 1 2 3 4 5 6 7 mean (se) Epiphytes .8 Bryoria capillaris 2 5 4 3 4 2 5 4 3.6 B. furcellata * 2 2 0 1 1 1 1 0 1.0 R fuscescens 6 4 4 3 3 5 5 6 4.5 R fremontii * 0 0 1 0 0 0 0 0 0.1 A nadvornikiana 0 1 0 0 0 1 0 0 0.3 Evernia mesomorpha 3 1 1 3 3 1 1 1 1.8 E. prunastri 0 0 0 1 1 0 0 0 0.3 Hypogymniabitteri 0 0 0 0 0 2 1 1 0.5 H. physodes 4 6 4 6 5 4 4 3 4.5 H. tubulosa 3 2 2 1 1 3 2 2 2.0 Imshaugia aleurites I 1 0 0 0 0 1 0 0.4 Melanelia exasperatula 0 0 1 2 0 1 0 0 0.5 M. olivacea 2 1 2 2 3 2 0 1 1.6 Parmelia sulcata 3 4 3 1 1 4 3 3 2.8 Parmeliopsisambigua 2 1 1 0 0 1 1 2 1.0 P. hyperopta 2 0 1 1 1 0 1 2 1.0 Platismatia glauca 2 2 0 0 0 2 1 1 1.0 Ramalina dilacerata 1 2 2 3 0 1 1 1 1.4 R obtusatat 0 0 0 1 0 0 0 0 0.1 R roesleri 0 0 0 2 1 0 0 0 0.4 P, thrausta 0 1 1 1 0 0 2 1 0.8 Tuckermanopsis 0 3 3 2 0 3 2 1 1.8 chlorophylla T sepincola 3 0 0 0 0 0 0 0 0.4 Usneafilipendula 3 3 2 3 4 3 3 3 3.0 U. glabrescens 0 0 0 0 0 0 0 1 0.1 U. lapponica * 0 0 0 1 3 0 1 2 0.9 U subfloridana 2 2 2 1 5 2 0 2 2.0 Vulpicidapinastri 2 1 1 1 1 1 1 0 1.0 Sum of abundance 43 42 35 39 37 39 36 37 38.5 (1.00) Number of species 17 18 17 20 15 18 18 18 17.6 (0.50)

t First record of this speciesin the Komi Republic * Epiphytic specieswhich are pollution sensitive accordingto Hawksworth and Rose(1970).

172 Appendix 1.2. Epiphytic lichen speciesand their cover abundancerecorded on Picea obovataat site F2, (Bclaya Kedva river).

Species F2, Bela ya Kedva river 1 2 3 4 5 6 7 8 9 mean (se) Epiphytes Alectoria sarmentosa 0 0 0 0 1 0 0 0 0 0.1 Bryorla capillaris 2 1 1 0 3 6 3 1 5 2.4 R fuscescens * 2 2 4 5 1 6 3 3 2 3.1 R nadvornikiana 0 0 0 0 0 0 1 1 2 0.4 B. simplicior * 1 2 0 0 0 0 0 0 0 0.3 Evernia mesomorpha 1 0 1 0 1 1 2 0 1 0.8 Hypogymnia bitted 0 0 0 1 1 0 0 2 0 0.4 H. physodes 6 6 6 5 4 5 5 4 3 4.9 H. lubulosa 2 2 3 2 2 4 4 2 1 2.4 Melanelia exasperatula 0 0 0 0 1 0 0 0 0 0.1 M ollvacea 4 5 4 2 3 3 3 0 3 3.0 Parmelia sulcata 3 4 4 3 3 4 4 5 4 3.8 Parmeliopsis ambigua 0 0 1 1 0 0 2 1 1 0.7 P. hYP eropta 0 0 0 1 0 0 0 1 1 0.3 Physcia aipolia 0 1 0 0 0 0 0 0 0 0.1 Platismatia glauca 0 0 0 1 0 0 1 0 0 0.2 Ramalina dilacerata 5 5 4 2 3 2 2 0 1 2.7 R roesleri I I 1 0 1 1 1 1 1 0.9 R. thrausta 0 0 0 1 1 0 0 0 0 0.2 Tuckermanopsis I 1 1 2 2 2 2 2 2 1.7 chlorophylla T sepincold 0 0 0 0 1 0 0 0 0 0.1 Usneafilipendula 0 0 0 2 1 4 5 5 3 2.2 U. glabrescens 0 0 0 0 0 0 2 5 0 0.8 U lapponica * 2 1 3 1 0 0 3 0 0 1.1 U. subfloridana 0 1 2 3 2 4 5 2 4 2.6 Vulpicida pinastri 1 1 1 1 2 2 1 1 1 1.2 Sum of abundance 31 33 36 33 33 44 49 36 35 36.7 (1.98) Number of species 13 14 14 16 19 13 18 15 16 15.3 (0.71)

* Epiphytic specieswhich are pollution sensitive accordingto Hawksworth and Rose(1970).

173 Appendix 1.3. Epiphytic lichen speciesand their cover abundancerecorded on Picea obovataat site F5i (Svetly Vuktyl river).

Species F5j Svetly Vukt yl river 1 2 3 4 5 6 7 8 9 mean (se) Epiphytes Bryoria capillaris 5 4 4 6 3 2 4 3 2 3.7 A furcellata 0 0 2 0 1 2 1 0 1 0.8 B. fuscescens 5 5 4 3 4 6 3 4 3 4.1 R nadvornikiana 2 2 2 3 2 0 0 1 1 1.4 Evernia mesomorpha 0 0 0 1 0 1 1 2 2 0.8 Hypogymniabitted 0 1 0 0 0 0 1 1 0 0.3 H. physodes 4 3 3 5 4 4 4 4 5 4.0 H. tubulosa 2 0 1 4 0 3 1 2 3 1.9 Imshaugiaaleurites 0 0 0 1 0 0 0 0 0 0.1 Melanelia 0 0 0 2 0 0 1 1 0.7 exasperatula .2 M olivacea 2 0 3 3 2 3 4 4 4 2.8 Parmella sulcata 3 2 3 4 2 3 3 3 4 3.0 Parmeliopsisambigua 1 0 1 2 0 1 0 2 2 1.0 P. hyperopta 1 0 1 2 0 0 0 2 2 0.9 Platismatia glauca 0 0 2 1 0 1 1 1 1 0.8 Ramalina dilacerata 1 1 1 3 0 2 3 3 2 1.8 P, roesled 0 0 0 0 0 0 1 1 0 0.2 P, thrausta 1 2 2 0 0 1 0 1 0 0.8 Tuckermanopsis 3 1 0 2 3 3 3 2 2 2.1 chlorophylla Usneafilipendula 4 6 4 4 6 5 3 4 2 4.2 U. glabrescens 0 2 3 2 2 4 2 2 4 2.3 U. lapponica 1 0 0 1 0 0 1 2 2 0.8 U. scabrata * 0 0 0 0 1 0 0 0 0 0.1 U. subfloridana 4 2 4 4 2 4 4 5 4 3.7 Vulpicida pinastri 1 0 1 2 0 1 2 2 3 1.3 Sum of abundance 40 31 41 55 32 46 45 52 50 43.6 (2.79) Number of species 16 12 17 20 12 17 19 22 20 17.2 (1.16)

* Epiphytic specieswhich are pollution sensitiveaccording to Hawksworth and Rose(1970).

174 Appendix 1.4. Epiphytic lichen speciesand their cover abundancerecorded on Picea obovataat site F6, (Maly Patok river).

Species F6, Maly Patok river 1 2 3 4 5 6 7 8 9 mean (se) Epiphytes Alecloria sarmentosa 0 0 0 0 0 0 0 1 0 0.1 Bryoria capillaris 0 0 2 3 2 3 3 3 2 2.0 B. furcellata 1 0 2 2 0 0 0 0 0 0.6 B. fuscescens 2 2 2 2 2 0 0 0 0 1.1 R nadvornikiana 0 0 1 3 0 2 0 0 0 0.7 Evernia divaricata 2 3 3 0 0 0 2 2 0 1.3 E. mesomorpha I 1 0 0 0 0 0 0 0 0.2 Hypogymnia bitteri I 1 0 0 2 1 1 0 0 0.7 H. physodes 5 4 5 5 3 4 3 4 4 4.1 H. tubulosa 4 3 4 4 3 4 3 3 3 3.4 Melanelia olivacea 1 2 2 3 2 2 2 2 2 2.0 Parmelia sulcata 2 2 2 2 2 2 2 2 2 2.0 Parmeliopsis ambigua 3 3 2 2 2 4 2 2 2 2.4 P. hyperopta 3 2 2 2 2 3 2 3 3 2.4 Platismatia glauca 1 2 2 2 1 2 0 2 1 1.4 Ramalina dilacerata 1 0 0 0 0 0 0 0 0 0.1 Tuckermanopsis 2 2 2 2 2 2 2 2 2 2.0 chlorophylla Usneafilipendula 2 2 2 2 0 1 3 2 1 1.7 U. lapponica 0 1 2 0 0 0 2 0 0 0.6 U. scabrata * 2 2 0 3 2 0 0 0 0 1.0 U. subfloridana 0 0 0 0 2 2 0 2 2 0.9 Vulpicidapinastri 3 2 2 2 2 2 2 2 2 2.1 Sum of abundance 36 34 37 39 29 34 29 32 26 32.9 (1.42) Number of species 17 16 16 15 19 14 13 14 12 15.1 (0.72)

* Epiphytic specieswhich are pollution sensitiveaccording to Ilawksworth and Rose(1970).

175 Appendix 1.5. Epigeal lichen speciesand their cover abundancerecorded in plots at site F3j (Ortina river).

Species F3j Ortina river 1 23 4 5 mean (se) Epigeal Alectoria nigricans 3 20 2 0 1.4 A. ochroleuca* I 10 0 0 0.4 Bryocaulondivergens 3 00 2 0 1.0 Cetraria islandica 1 16 4 2 2.8 Cladonia amaurocraea 0 2 0 1 1 0.8 C arbuscula 4 3 6 5 5 4.6 C. bellidiflora 1 0 1 1 0 0.6 C. cervicornis 0 1 0 0 0 0.2 C. coccifera 1 0 0 1 1 0.6 C crispata 1 1 0 0 0 0.4 C.furcata 0 0 0 0 1 0.2 C. gracilis 1 1 3 3 3 2.2 C. pleurota 0 0 2 0 0 0.4 C. rangiferinalstygia 1 1 5 3 4 2.8 C. stellaris 1 0 1 0 0 0.4 C. subfurcata 2 0 0 0 1 0.6 C. sulphurina 0 0 1 0 0 0.2 C. uncialls 1 2 3 1 3 2.0 Havocetraria nivalis 5 7 2 5 5 4.8 F. cucullata 2 2 1 2 2 1.8 F. nigricans 0 2 0 0 0 0.4 Ochrolechlaandrogyna 0 1 0 0 0 0.2 0. frigida 1 0 1 1 2 1.0 Peltigera scabrosa * 1 0 0 0 0 0.2 Sphaerophorusglobosus 1 1 0 2 0 0.8 Stereocaulonalpinum 1 0 0 0 0 0.2 S.paschale * 3 3 0 0 2 1.6 Thamnoliavermicularis 2 2 0 1 0 1.0 Sum of abundance 37 33 32 34 32 33.6 (0.93) Number of spicies 21 17 12 15 13 15.6 (1.60)

* Epigeal species which are pollution sensitive according to McCune and Geiser(1997) and Gilbert (2000).

176 Appendix 1.6. Epigeal lichen speciesand their cover abundancerecorded in plots at site F4,,(Neruta river).

Species F4,,Neruta 1 2 3 4 5 mean (sc) Epigcal Alectoria nigricans 3 3 3 2 2 2.6 A. ochroleuca * 0 2 0 0 2 0.8 Bryocaulon divergens 2 2 0 0 1 1.0 Cetraria islandica 3 3 3 4 3 3.2 Cladonia amaurocraea 0 2 0 3 0 1.0 C arbuscula 5 5 5 5 6 5.2 C bellidiflora 1 0 0 1 0 0.4 C chlorophaea 2 0 0 0 0 0.4 C coccifera 1 2 1 1 2 1.4 C cornula 2 0 0 0 0 0.4 C crispata 1 0 2 2 0 1.0 C furcata 0 1 0 0 0 0.2 C gracilis 3 2 3 3 4 3.0 C macrophylla 0 0 0 0 1 0.2 C rangiferinalstygia 4 4 4 4 4 4.0 C. stellaris 2 1 1 1 1 1.2 C. subfurcata 0 1 0 0 0 0.2 C uncialis 3 3 3 4 5 3.6 Flavocetraria nivalis 5 6 7 6 7 6.2 F. cucullata 4 3 3 3 4 3.4 Nephromaarcticum 2 0 2 2 2 1.6 Ochrolechiafrigida 1 0 0 1 0 0.4 Peltigera scabrosa * 1 0 2 1 2 1.2 Sphaerophorusglobosus 3 2 2 0 0 1.4 Stereocaulonalpinum 0 0 3 3 0 1.2 S.paschale * 4 2 4 3 4 3.4 Thamnoliavermicularis 2 3 1 2 2 2.0 Sum of abundance 54 47 49 51 52 50.6 (1.21) Number of species 21 18 17 19 17 18.4 (0.75)

* Epigeal specieswhich are pollution sensitiveaccording to McCune and Geiser (1997) and Gilbcrt (2000).

177 Appendix 1.7. Epigeal lichen speciesand their cover abundancerccordcd in plots at site F7j (Kolva river).

Species F7j Kolva river 1 2 3 4 5 mean (se) Epigeal Alectoria nigricans 1 0 0 0 0 0.2 Cetraria islandica 2 2 3 3 2 2.4 Cladonia amaurocraea 2 2 2 2 3 2.2 C arbusculd 4 5 7 7 7 6.0 C bellidiflora 1 0 0 0 0 0.2 C borealis 0 1 0 1 2 0.8 C conlocraea 0 1 0 0 0 '0.2 C cornuta 0 0 1 0 0 0.2 C crispata 1 0 1 2 1 1.0 C gracilis 3 3 2 3 2 2.6 C rangiferinalstygia 3 4 3 4 5 3.8 C stellaris 0 2 4 2 1 1.8 C subfurcata 0 0 1 0 0 0.2 C uncialis 2 2 2 0 0 1.2 Flavocetraria nivalis 6 5 3 3 3 4.0 F. cucullata 3 2 2 3 2 2.4 kmadophila ericetorum 0 1 0 0 0 0.2 Peltigera malacea 2 0 0 0 0 0.4 P. scabrosa * 2 0 0 0 0 0.4 Sphaerophorus globosus 2 0 0 0 0 0.4 Stereocaulon alpinum 2 0 0 0 0 0.4 S. paschale * 6 0 0 0 0 1.2 Sum of abundance 42 30 31 30 28 32.2 (2.50T Number of species 16 12 12 10 10 12 (1.10)

* Epigeal specieswhich are pollution sensitiveaccording to McCune and Geiser(1997) and Gilbert (2000).

178 Appendix 1.8. Epigeal lichen speciesand their cover abundancerccordcd in plots at site F8,,(Mareyu river).

Species F8, Mare yu river 1 2 3 4 5 mean (se) Epigeal Alectoria nigricans 2 3 2 2 4 2.6 A. ochroleuca * 2 3 2 1 3 2.2 Bryocaulon divergens 2 3 2 1 3 2.2 Cetraria islandica 2 3 3 3 2 2.6 Cladonia amaurocraea 2 2 2 2 2 2.0 C arbusculd 3 4 3 4 4 3.6 C bellidiflora 1 2 1 2 1 1.4 C borealis 1 1 2 2 2 1.6 C cervicornis 0 0 0 1 0 0.2 C. chlorophaea 0 2 1 1 2 1.2 C crispata 0 0 0 0 2 0.4 C. gracilis 2 2 2 2 2 2.0 C pleurota 0 2 0 0 0 0.4 C rangiferinalstygia 2 2 2 2 2 2.0 C stellaris 1 2 0 2 2 1.4 C sulphurina 0 2 0 0 0 0.4 C uncialis 2 2 4 3 2 2.6 Flavocetraria nivalis 4 4 3 5 5 4.2 F. cucullata 2 3 2 2 2 2.2 F. nigricans 0 1 0 0 0 0.2 Hypogymniaphysodes 2 0 0 0 0 0.4 kmadophila ericetorum 1 0 0 0 0 0.2 Ochrolechiafrigida 0 2 2 1 2 1.4 P. malacea 0 0 3 0 0 0.6 Peltigera neckeri 0 1 0 0 0 0.2 Pertusaria coccodes 0 0 0 0 1 0.2 P. panygra 0 1 0 1 0 0.4 Sphaerophorusglobosus 2 2 2 2 2 2.0 Stereocaulonalpinum 1 0 1 0 0 0.4 S.paschale * 3 2 3 0 1 1.8 Thamnoliavermicularis 2 2 1 0 2 1.4 Sum of abundance 39 53 43 39 48 44.4 (2.71) Number of species 20 24 20 19 21 20.8 (0.86)

* Epigeal specieswhich are pollution sensitiveaccording' to McCune and Geiser (1997) and Gilbert (2000).

179 Appendix 1.9. Epiphytic lichen speciesand their cover abundancerccorded growing on Betula nana in plots at site F3j (Ortina river).

Species F3j Ortina river 1 2 3 4 5 mean (se) Epiphytes Cetraria nigricans 0 1 0 0 0 0.2 Hypogymniaphysodes 4 5 4 2 1 3.2 Lecanora argentata I 1 0 0 0 0.4 Melanelia olivacea 5 2 2 0 0 1.8 Ochrolechiaftigida 0 3 2 5 5 3.0 Parmeliopsisambigua 3 3 3 3 5 3.4 P. hyperopta 0 2 3 3 5 2.6 Pertusaria dactylina 0 3 0 0 0 0.6 Tuckermanopsissepincola 1 4 1 4 4 2.8 Vulpicidapinastri I I I I 1 1.0 Sum of abundance 15 25 16 18 21 19 (1.82) Number of species 6 10 7 6 6 7 (0.77)

Appendix 1.10.Epiphytic lichen speciesand their cover abundancerecorded growing on Betula nana in plots at site F4, (Neruta river).

Species R, Neruta river 1 2 3 4 5 mean (se) Epiphytes Hypo,gymniaphysodes 1 5 1 0 1 1.6 Ochrolechlaftigida 4 5 5 1 5 4.0 Parmeliopsisambigua 3 4 4 3 4 3.6 P. hYP eropta 3 4 4 3 4 3.6 Pertusaria dactylina 1 0 4 0 0 1.0 Tuckermanopsissepincola 5 4 4 3 5 4.2 Vulpicidapinastri 2 2 2 2 2 2.0 Sum of abundance 19 24 24 12 21 20 (2.21)- Number of species 7 6 7 5 6 6.2 (0.37)

180 Appendix 1.11. Epiphytic lichen speciesand their cover abundancerecorded growing on Befula nana in plots at site F7j (Kolva river). Species F71Kolva river 1 2 3 4 5 111can (se) Epiphytes Alectoria nigricans 0 0 0 0 2 0.4 Bryoria simplicior 0 0 1 0 0 0.2 Hypogýmnia physodes 3 1 0 2 3 1.8 Lecanora argentata 2 0 2 0 0 0.8 Melanelia olivacea 2 0 0 1 0 0.6 Ochrolechiaftigida 0 0 1 1 0 0.4 Parmelia sulcata 2 1 0 1 2 1.2 Parmeliopsis ambigua 3 2 3 2 2 2.4 P. hyperopta 2 2 2 2 2 2.0 Pertusaria dactylina 2 1 0 0 0 0.6 Tuckermanopsis sepincola 3 2 4 4 3 3.2 Vulpicidapinastri 2 1 2 2 2 1.8 Sum of abundance 16 7 9 9 11 10.4 (1.54) Number of species 9 7 7 8 7 7.6 (0.40)-

Appendix 1.12. Epiphytic lichen speciesand their cover abundancerecorded growing on Betuld nana in plots at site F8, (Mareyu river). Species F8, Marc yu river 1 2 3 4 5 mean (sc)__ Epiphytes Alectoria nigricans 0 2 0 0 2 0.8 A. ochroleuca * 0 1 0 0 2 0.6 Celraria nigricans 2 2 2 1 1 1.6 Bryocaulon divergens 0 1 0 0 0 0.2 Bryoriafuscescens * 1 0 0 0 1 0.4 Hypogymnlaphysodes 3 3 0 0 2 1.6 H. tubulosa 1 0 0 0 0 0.2 Lecanora argentata 2 2 2 2 2 2.0 Melanelia olivacea 2 2 1 0 1 1.2 Ochrolechiaftigida 2 2 2 3 2 2.2 Parmelia sulcata 2 2 0 1 1 1.2 Parmeliopsis ambigua 2 2 2 2 2 2.0 P. hYP eropta 2 2 2 2 2 2.0 Pertusaria corallina 0 0 0 1 2 0.6 P. coccodes 0 2 1 0 0 0.6 P. dactylina 2 0 1 0 2 1.0 Tuckermanopsis sepincola 5 4 3 4 4 4.0 Vulpicidapinastri 2 2 2 2 2 2.0 Sum of abundance 21 23 13 12 22 18.2 (2-15) Number of species 13 14 10 9 15 12.2 (1.161 * Epiphytic specieswhich are pollution sensitiveaccording to I lawksworth and Rose(1970).

181