Carranza, E. J.

Fügedi, Ubul

Jordán, Győző

Lois, L.

Rukezo, G.

Somody, A.

Szebenyi, G.

Vekerdy, Zoltán

English

Repository of the Academy's Library

(1) Joint Research Centre of the European Commission, Ispra I-21020, Italy.(2) Hungarian Geological Survey, Stefania ut 14, Budapest 1143.(3) International Institute for Geoinformation Sciences and Earth Observation (ITC) P.O.Box 6, 7500AA Enschede, The Netherlands.(4) Recsk Ore Company Ltd. Recsk, H-3245, Hungary.ENVIRONMENTAL IMPACT OF METAL MINING ON CATHCMENTDRAINAGE IN THE HISTORIC MINING AREA OF RECSK-LAHÓCAMINES, HUNGARYJordan G.(1,2), Rukezo G.(3), Fügedi U.(2), Carranza E.J.M.(3), Somody A.(4), Vekerdy Z. (3),Szebényi G.(2) and Lois L.(4)Session 13 - Poster 713KEY WORDS: catchment, drainage geochemistry,environmental impact, heavy metals, mining.INTRODUCTIONThe mining of volcanogenic sulphide oredeposits in the Recsk-Lahóca mines in the MátraMountains of Hungary resulted in the exposure ofsulphide bearing rocks to surface water and atmos-pheric oxygen, which accelerate oxidation, leachingand release of metals and acidity. Tailings, mineadits and associated waste rock dumps resultingfrom the two-century Cu, Au and Ag mining arescattered along the streams in the catchment area(fig. 1). Environmental problems arise from AcidMine Drainage (AMD) discharge into the drainagesystem, which results in metal pollution and acidi-fication of the aquatic environment within the vicin-ity of the mine areas. Elevated metal content inboth surface waters and sediments were reportedby earlier studies.The objective of the study was to identify andassess the impacts of AMD on the receivingstream waters and sediments. Specific objectiveswere to (1) identify and map metal contaminationdue to sulphide ore deposit mining, (2) use spatialvariability to determine sources of heavy metalcontamination in the studied catchment, (3) distin-guish natural background contributions from minepollution, and (4) create a geochemical risk map ofcatchment drainage. Figure 1 - Study area. Main mine features and sample locations.GEOLOGICAL SETTING AND MININGOre minerals are hosted in andesitic subvolcanicbodies, and subaerial and submarine strato-vol-canic rocks that formed in the thrust-subductionzones of the inner Carpathian volcanic arc. TheEocene strato-volcanic sequence is the main hostof sulphide mineralisation. Overlying the Oligoceneclayey sediments, Miocene pyroxene andesite lavaflows and rhyolite tuffs build-up sub-volcanic bod-ies and stratovolcanic sequences. Gold, silver andbase metal deposits of epithermal, porphyry, veinand skarn types are associated with Eocene intru-sives. The epithermal mineralisation is charac-terised by Au-Cu high sulphidation deposits foundnear surface. The porphyry copper, Cu-Zn skarn,vein and replacement mineralisations are found atdeeper levels (Recsk Deeps). The near surface Au-Cu epithermal deposits are hosted by the upper-most Eocene calc-alkaline andesitic stratovolcanicsequences. In the mineralised zones, the mostcommon ore sulphides are pyrite, chalcopyrite,sphalerite, enargite, luzonite and tetrahydrite whilethe gangue minerals are calcite, quartz, barite andother sulphides. The Recsk Deeps are mainly com-posed of three ore mineralisation types. These aregalena-sphalerite vein type deposit, porphyry cop-per deposit and Cu-Zn skarn. Base and preciousmetal mining in the Recsk-Lahóca area startedabout 200 years ago. Several ancient adits exist inthe area. The major mining activities took placemostly between the 1950s and 1998. The Lahócahill was mined for copper between 1852 and 1979.Development of Recsk Deeps mines resulted inunderground shafts extending 1200 m deep. Themine was meant to produce 3 to 5 million tons ofore per year but it never went into production sinceits construction in 1970.MATERIALS AND METHODS79 stream water samples were collected atabout 250 m intervals along the stream courses inthe study area (fig. 1). Duplicate samples were col-lected after every 10 sampling points. Sampleswere filtered (45µm) and acidified with HNO3.Temperature, pH, electrical conductivity (EC) weremeasured in the filed. A total of 59 stream sedi-ment samples were collected at the same samplesites as stream water samples where field condi-tions allowed. Composite samples of fine sedi-ments collected in the active part of the streamaround each water sample site were homogenisedusing 2-mm mesh sieve. Samples were dried in anoven at 40 ºC in lab before processing. Sample frac-tions of <180 µm were then sieved before subse-quent chemical analysis. Metal extraction used63% hot HNO3 followed by shaking on a vortexshaker and shaking in a water bath at 90 ºC for 2hours. All samples were kept on ice until analysis.Element concentrations in water samples and sed-iment extracts of As, Cd, Cu, Fe, Mn, Ni, Pb, Sband Zn were determined using the ICP-AESanalyser.In this study, geochemical processes were stud-ied as stochastic processes and statistical toolswere used for data analysis. Univariate exploratorydata analysis (EDA) techniques followed by multi-variate statistical analyses including cluster analysis(CA) and Q-mode principal component analysis(PCA), were used to investigate element distribu-tion patterns, geochemical abundances and gradi-ents in the water and sediment and identify samplepopulations. Correlation analysis and canonical cor-relations were applied to investigate significantrelationships among the variables measured. Allcorrelations were visually controlled and robust-714 Session 13 - Poster Figure 2 - Geochemical groups in stream water identified by CA and PCA. Cluster A: mines, B: biotetite-hornblende andesite, C:Oligocene clay, D: andizite with argillization, along potassium metasomatic zone, E: hydrothermal alteration zone, F-G: probable gas(CO2, H2S, CH4, Radon) exhalation locations.ness of regression analysis was assured by inter-active outlier rejection. Throughout geochemicalmodelling the use of robust and non-parametrictechniques were preferred to classical statisticalmethods because geochemical datasets are oftencharacterised by small sample sizes, multi-modalpopulations, outliers and non-normality. Analysis ofspatial relationship between pollution source andreceiving aquatic environment in the studied catch-ment used geographic information system (GIS)techniques. Location of mine features and sam-pling points were determined with GPS in the field.Digitised layers of mines, waste dumps anddrainage network were overlaid on geo-referencedgeological maps to study influence of the naturalbackground and mine-induced pollution.RESULTS AND DISCUSSIONStem-and-leaf displays, frequency histogramsand box-plots of the data sets showed poly-modalbehaviour with positively skewed populations andwere characterised by the presence of less than20% outlying values, as defined by the inner-fencecriteria. Outliers (forming the ‘anomalous popula-tion’) in water and in sediments were located eitherat mine sites or at the hydrothermal alteration area.All dissolved metals apart from Fe and Zn werebelow detection limits for other locations whichform the ‘background population’. Associationsamong metals were studied by means of theSpearman correlation analysis of log-transformeddata. Where it was geochemically justified, correla-tions were subjected to partial correlation analysisin order to correct for possible induced correlationscaused by a common variable. All correlations werechecked for significance at the 0.05 significancelevel and were graphically examined to avoid spuri-ous correlations. Correlations in the ‘backgroundpopulation’ in stream water showed strong correla-tion (r>0.7) between SO4, EC, Mn and to lesserextent with Fe. Lack of correlation with pH indi-cates that pH is determined most probably by theabundant bi-carbontes in related areas. Strong cor-relation (r>0.7) of pH with SO4, EC and metals inmining areas is charactersitic to AMD. Strong cor-relation (r>0.8) for sediments among As, Cu, Zn,and to a lesser extent with Pb is typical to the min-eralisation of the area. All sedimentary metals cor-relate with Fe, in particular close to mine siteswhere yellow boy sediments were observed, indi-cating metal control by co-precipitation with Fe-oxyhydroxides. Using the nearest neigbour linkagemethod and the Euclidean-distance as a measureof similarity in CA, water samples separated into 6groups corresponding to well-defined geochemicalregimes in the cathment (fig. 2). PCA confirmedthe existence of the same groups. Sediment sam-ples showed the same grouping but with less well-defined boundaries, indicating mixing due to sedi-ment transport.CONCLUSIONSDrainage water has dynamic contact with thesurroundings and thus water chemistry reflectsaccurately AMD pollution locations. The analysedfine stream sediments also correlate with ambientgeology and pollution sources but frequent flood-ing events in the catchment renders them a mix-ture of up-stream drainage area contributions.Based on univariate and multivariate analysis ofdrainge chemistry, the main geochemical regimesof the catchment could be delineated. This infor-mation can be used to optimise drainage monitor-ing system, which aims at monitoring spatial andtemporal variability due to pollution sources andnatural background. This study has shown loca-tions of elevated metal contamination in thedrainage system due to natural background pollu-tion. Finally, geochemical risk map of the drainagewas created for surface waters and sedimentsusing (1) the obtained spatial geochemical resultsand (2) comparison to international standards (fig.3). The map shows that surface water is contami-nated almost all along its course, partly due to nat-ural background. Sediment pollution is concentrat-ed in areas where physico-chemical conditionsfacilitate metal accumulation.Session 13 - Poster 715Figure 3 - Geochemical Risk Maps. A. Map showing stream water with base metal concentrations above the maximum permissiblelimits for EU drinking water standards. B. Map of stream sediments showing base metal concentrations requiring additional investi-gations and cleaning-up according to the NEN standards for soils.

Environmental impact of metal mining on catchment drainage in the historic mining area of Recsk-Lahoca mines, Hungary

Environmental impact of metal mining on catchment drainage in the historic mining area of Recsk-Lahoca mines, Hungary

Abstract

Similar works

Full text

Available Versions

Repository of the Academy's Library