Measured concentrations of chemical species in filtrated samples of surface waters are summarised in Table 1. Values reported for heavy metals as well as for the major anions at the headwater stations C1, F1 and Mi1 (in italics in Table 1) represent background concentrations. They were in the range expected from the mineralogical and geological settings of the region. With the exemption of the Zn concentration at C1, they complied with the European quality standards in rivers (see Table 3). Concentrations of SO4, Fe, Mn, Ni, Cu and As in the tributary Noiagul, station N1, went beyond the background values. This small pollution reflects the impact of small mines and their waste dumps that were operated in the valley from approximately 1750 to 1950. Mapping of heavy metal concentrations clearly visualises the very large differences in metal concentrations between Certej River, downstream from the first AMD, and the other surface and groundwaters (two examples see Fig. 3).
The longitudinal profiles of heavy metals, SO4 and alkalinity, resp. acidity (Figs. 4 and 5) clearly depict, quantitatively, the strong pollution in the Certej River caused by the mining operations in the last decades. Concentrations increased two to three orders of magnitude from background stations C1 to C2, situated downstream from the first AMD input. From station C2 to C7, the water exhibited an acid pH value of 2.9 to 3.5 and very high concentrations of Mn, Fe, Zn, Cu and Cd. They were only slightly lower than those in the three AMD outflows from underground mines near the open pit Coranda. The high concentrations of dissolved and particulate Fe (data not shown) resulted in an ochre-brownish colour in the river water, a distinct and classical optical sign of AMD pollution (hydrolysed Fe(III) hydroxide polymers). The creek downstream from the Mialu dam, stations Mi2 and Mi3, still exhibited a low alkalinity and a neutral pH value, but their high SO4, Mn, Fe, Zn and As concentrations clearly indicated an input of AMD. Downstream Certej valley, at station C8, waters from non- or less polluted tributaries caused a minor dilution. Consequently, the pH value increased depending on the relation between waters originating from mines and non-polluted waters. The acidity also decreased; at higher discharge, the river water may even exhibit an alkalinity. However, most heavy metal concentrations still exceeded clearly the European quality standards in rivers (see Table 3). The single ICP-MS measurements in samples from C8 yielded the following concentrations: 4 μg L−1 for Se, 1 μg L−1 for Sb, 2 μg L−1 for U and 33 μg L−1 for B. The elevated concentrations of Se and Sb were due to the input of the Mialu creek, where respectively 21 μg L−1 and 8 μg L−1 were found. This observation is plausible since mined ores always contain other metal-bearing minerals (Frei 2006), which can also be dissolved. The Certej River inputs of heavy metals into Mures River will be substantial, despite the water discharge in Mures River being about 20 to 50 times larger than in the Certej River. Although not measured, chemical results made irreproachably provide evidence that the ecological condition in the Certej River also did not comply with the European Water Frame Work Directive. Data for pollutants measured before and after mining closure did not indicate any significant change, i.e. a decrease after ceasing mining activities.
Groundwater in the piezometers downstream from the Mialu and Miresul tailings exhibited a different water composition than background surface waters. The elevated alkalinity, Ca and Mg content, combined with a moderately high SO4 concentration, indicated an acid production by pyrite oxidation, which is neutralised by carbonate minerals. The relatively high concentrations of Mn and Fe in unfiltrated samples were due to colloidal particles, although the water was only slightly turbid. Concentrations of other heavy metals were also above background values. This fact indicates the impact caused by leaching of heavy metal-containing minerals occurring in waste ore deposits. It may be worthwhile to note that the water on top of the piezometer tube, which is usually monitored by the Romanian monitoring institution, displayed a much lower electrical conductivity than water pumped from the middle part of the piezometer. This anomaly may suggest a density separation of more saline groundwater and groundwater diluted with rainwater.
Drinking waters taken from the 11 dug wells situated at a distance of 7 to 25 m from the heavily polluted Certej River exhibited a composition (Table 2) that differed greatly from that of the river. pH values were neutral and heavy metal concentrations were mostly low and near background values. The metallic water extraction equipment of the dug wells, sometimes not well maintained, might have caused heavy metal concentrations slightly above background. Most of these well waters, as well as the drinking water of the public water supply in Certeju de Sus (data not shown), complied chemically with EU quality standards for drinking water (Table 3). The two wells in Hondol showed SO4 concentrations in the range of 900 mg L−1 and a low alkalinity, indicating pollution, probably caused by a small input of AMD. In two wells, As concentrations exceeded the quality standards for drinking water (see Fig. 2). The big differences between the water composition of river and well water proved that, at the time of sampling, the heavily polluted river did not infiltrate, or at most, slightly only, into the aquifer feeding the wells. Probably, the groundwater stems from the valley slopes, where local geogenic pollution sources could also exist. A hydrogeological study would be needed to clarify the condition of the groundwater used as drinking water.
Samples taken on the top of the Mialu tailings dam contained mainly silicates (quartz, K-feldspar and muscovite), some pyrite and little carbonates, shown by X-ray diffraction. Few samples also hosted traces of gypsum and sphalerite (Frei 2006). The elemental composition, obtained by X-ray fluorescence (Table 4) indicated a distinct average content of pyrite, 36 g kg−1, (0.3 mol kg−1, std. dev. 0.036) if all sulphur was taken as pyrite, and also a small amount of carbonates. The total carbon (TC), measured separately, indicated levels of carbonate, since the organic content of the material was negligibly small. Taken as calcite, the average of ten samples amounted to 36 g kg−1 (0.36 mol kg−1, std. dev. 0.073). The conversion of all Ca displayed in Table 4 into calcite would yield 55 g kg−1, a calculation which does not account for the Ca in silicates and gypsum. Data on the composition allowed performing an acid–base accounting (ABA) by assuming that the four protons produced by reaction (1) and (2) will be neutralised by four calcite to obtain a pH of 8.2. This procedure estimates roughly if the tailings impoundment material will produce an excess of acidity or if it will be able to neutralise the acidity produced. The stoichiometric calculation with given values of pyrite and calcite contents resulted in net acid production potential of 0.84 mol H+ kg−1, corresponding to a lack of (84 g calcite as acid-neutralising capacity per kilogram, 95% confidence interval 38 g kg−1). An extrapolation to the whole Mialu deposit would give a non-neutralised production potential of about 50,000 t sulphuric acid (about equivalent to a 0.1 m3 s−1 flow of acidic water with a pH of 3 in a time frame of 300 years). The ABA calculation presents an upper limit of the acid production since the slow neutralising weathering reactions of silicates is not considered. Data on the composition of Mialu tailings dam samples also indicated approximately that of the rock in the Coranda ore deposit.
Heavy metals content of Zn, Cu, Pb and Cd increased distinctly in river sediments from the downstream station C3 and reached a peak at station C4 or C 5 (Fig. 6). Several factors might have caused this increase; higher sedimentation rate due to lower slope of the river bed, remaining inputs from the ore processing plant and a nearby tailings dam. In the upper part of the river, metal concentrations, except those for Cd, fell in the region of the target values set by the German Association for Water (LAWA) to protect the aquatic biota in sediments (see Table 3). At the downstream station C8, target values were still surpassed, except for Cu. In the Mures River, downstream from the confluence of Certej River, metal contents in sediments did not decrease to background values, but those for dissolved Zn and Pb diminished (data not shown). This fact suggests a pollution of Mures River by sediments and precipitates of dissolved heavy metals, both stemming from Certej River.
This part summarises results of the extensive study performed by Dogaru et al. (2009). Answers related to the socioeconomic dependencies of the people to the mining industry revealed that 20% of the households had redundant mine workers and that 45% of the households were partly or completely reliant on financial compensation as a result of mine closure. For 64% of the respondents, mining was the major source of income. Mine closure and the high unemployment rate of 35% were considered as the main cause for social problems by 93% of the people. Of the interviewed families, 60% possess no arable land besides that surrounding their houses.
Table 5 adds further primary results obtained from the survey and factors considered in the perception study. It also designates the predictor variables and the dependent variables used in logistic regressions. Answers to the questions of the enquiry reflected the social structure and the economic situation in the region and how people assessed pollution and its impact. A statistical analysis indicated a relative spatial homogeneity of the data within the main river valley, suggesting that the study was reasonably representative.
The stepwise logistic regression revealed that, for the perception ‘highly polluted river water’, four predictors were most significant in explaining the opinion of the interviewed people (Table 6). They were: education, household income, pollution during last years before mine closure and familiarity with environmental problem. Out of the four education-level groups, the post-high school group was about seven times (odds ratio 6.97) more likely to consider the River Certej as highly polluted than the high school graduates taken as a reference category. The other two education-level predictors exhibited also an odds ratio >1, but they were less significant (p > 0.05) and had low B values. This result supported the general view that more highly educated people show more concern with environmental problems. Regarding household income, respondents who reported a household income below 1,000RON per month were more likely to perceive the Certej River as highly polluted than the more affluent ones, although this effect was not significant at a 0.05 level. This income predictor was inconsistent with the general expectation that people with higher income usually show more concern with the environmental problems. The inverse relationship in the Certej catchment may be viewed as people associating their current economic condition with the precarious living neighbourhood. The other two explanatory variables were pollution in the last years before mine closure and familiarity with environmental problems. They showed an increased likelihood of predicting that locals perceive the Certej River to be highly polluted. People who believed that the water quality stayed the same or deteriorated compared to the period before mine closure were five to seven times more likely to perceive the water as being highly polluted than those who said that the water quality had improved since then. Also, people who reported that the mine would pollute more if it were still functioning were more likely to consider the river water to be highly polluted. These results were consistent with the fact that people perceive mining as a major source of pollution. The independent variables ‘observable effects’ were statistically insignificant in the analysis. In this model for the perception of the river water quality, 77% of the observations were correctly predicted (74% for those who considered the water as highly polluted and 80% for those who did not, e.g. who considered the river water as only being polluted). The outcome of the perception study agrees with the chemical data indicating a strong pollution of the river.
Three significant predictors estimated the perception ‘polluted drinking water’, education, household income and people who consider drinking water would be even more polluted if mines were still in operation. The model results indicated that these three categories were about three times more likely to consider drinking water to be polluted. Characteristics for pollution during the last years before mine closure and taste of drinking water were also tested, but none proved to be statistically significant. This model was able to correctly predict 66% of the observations, leading to the conclusion that the approach might not be able to estimate properly whether people in the Certej catchment believe their drinking water to be polluted by mining, or where there might be other independent variables, i.e. questions not included in the questionnaire, which could better explain the drinking water quality perception model. Indeed, the chemical data of the drinking water do not indicate polluted water in general.