Evaluation of geochemical baselines and metal enrichment factor values through high ecological quality reference points: a novel methodological approach

Butterflies as bioindicators of metal contamination

Anthropogenic trace metal contamination has significantly increased and has caused many hazardous consequences for the ecosystems and human health. The Terni basin valley (Central Italy) shows a heavy load of pollutants from industrial activities, while the characteristic orography structure of the valley favours air stagnation, thus limiting air pollution dispersal. The present study conducted in 2014 aimed to determine the concentration of ten metals in five species of butterflies at nine sites in the Terni valley along a 21-km-long transect, including both relatively pristine and industrial areas. At sites where soil contamination was high for a given metal, such as for chromium as in the case of site 4 (the closest to the steel plant) and for lead as in the case of site 2 (contaminated by a firing range), higher levels of contamination were observed in the tissues of butterflies. We found a correlation between soil contamination and the concentration of Cr, Al and Sr in the tissues of some species of butterflies. The sensitivity to contamination differed among the five species; in particular, Coenonympha pamphilus was generally the species that revealed the highest concentrations of all the ten trace metals at the sites closer to the industrial area. It is known that C. pamphilus is a sedentary species and that its host plants are the Poaceae, capable of accumulating high quantities of metals in their rhizosphere region, thus providing the link with soil contamination. Therefore, monitoring the metal concentration levels in butterflies might be a good indicator and a control tool of environmental quality, specifically in areas affected by high anthropogenic pollution loads linked to a specific source.

Sources and trends of trace elements and polycyclic aromatic hydrocarbons in a shallow lake in the Mediterranean area from sediment archives of the Anthropocene

In this study, the anthropogenic contamination in Trasimeno lake (Central Italy) was investigated using three sediment cores spanning over the last 150 years (Anthropocene) to identify the primary sources of pollution and quantify the level of contaminant enrichment in the basin. First, based on the relative cumulative frequency and linear regression methods, we obtained a geochemical baseline for the lake using the deeper parts of the sediment cores. The geochemical baseline allowed us to determine the values of trace elements enrichment factors. On this knowledge, as a second result, we were able to reconstruct the natural sources and the anthropogenic impact on the lake with a biennial resolution. This goal has been obtained by combining different inorganic and organic chemical proxies such as trace elements, polycyclic aromatic hydrocarbons, and lead isotope ratios and exploiting both principal component and factor analysis to associate chemical proxies to human-driven contamination processes. Five different groups of elements have been identified, one of which is of natural origin and four of anthropogenic origin. In particular, it was possible to identify the times and impacts of the industrial activities during the Second World War, which dispersed heavy metals in sediments. Moreover, we found evidence of the recent human activities that have characterized the surroundings of the basin, such as Pb inputs related to the use of gasoline and the enrichment of certain elements generally used in agricultural activities (such as P, Cu, and Mn) due to the development of this sector in the last 40 years.

Does mercury emission from small-scale gold mining cause widespread soil pollution in Ghana?

The use of mercury in small-scale gold mining is globally the largest anthropogenic source of mercury in the environment. In countries like Ghana, where small-scale gold mining is a highly important economic sector, the activity is also expected to cause local pollution. This study is based on a hypothesis that the mining activity in Ghana is causing more widespread soil pollution also outside active mining sites, and that the main part of regional differences in soil concentrations of mercury might come from pollution. Little systematic and dependable data has been collected to assess the extent of mercury contamination of soils in areas outside active mining areas. The regional aspect of mercury pollution from mining has not been studied in Ghana or other countries with a large small-scale gold mining sector. Systematic collection of soil samples on a 25 × 25 km² net covering the entire country was carried out to ensure the representativeness of data and to allow calculation of spatial trends. The soil concentrations found in one-third of the country, where most intensive mining takes place, are three times higher than concentrations in the rest of the country. This difference cannot be explained by sources of natural variation in mercury concentrations but can be explained by decades of atmospheric deposition. It is therefore likely that the mining activity has caused a more widespread increase in soil concentrations, also outside active mining sites. The mercury concentrations found are on average 0.024 mg kg^-1, which is low compared to published studies from other countries and regions and estimated world averages. All measured concentrations are well below soil quality criteria for human health. The build-up of soil concentrations in the mining area is still problematic because mercury is a hazardous substance in the environment.

Improved enrichment factor model for correcting and predicting the evaluation of heavy metals in sediments

As the most widely used method for evaluating heavy metals (HMs) in soil or sediment, the enrichment factor (EF) is prone to bias and even yields misleading assessment results for HM pollution due to data uncertainties, lack of local background values and a failure to assess the comprehensive pollution of multiple HMs. Here, we developed an improved EF model integrating stochastic mathematical methods and geochemical baselines (GBs). First, GBs were obtained using the relative cumulative frequency distribution method. The probability that each HM belongs to each enrichment degree was then quantified based on the probability density function deduced from the maximum entropy method. Furthermore, we defined a synthetic index to reveal the probability that multiple HMs belongs to comprehensive enrichment degree considering the weight of each HM. Finally, the enrichment category for each HM and multiple HMs were determined following the first-order moment principle. The improved EF model was successfully applied to evaluate and predict the HM pollution in sediments collected from Poyang Lake, the largest freshwater lake in China. Slight enrichment (1.88) of multiple HMs was found in sediments from Poyang Lake, characterized by a pronounced probability (0.35) to deteriorate to the "moderate enrichment" category. Among the different HMs, Cd requires more attention considering its dominant contribution (0.51) to the comprehensive pollution and high probability (0.65) for deterioration. Otherwise, assessment results employing the improved EF model agree with the spatial patterns of HM concentrations based on spatial autocorrelation analysis and source apportionment using Pb isotopic signatures and principal component analysis. Compared with the conventional EF method, the assessment results of the improved EF model were more accurate, comprehensive and reliable. In conclusion, the improved EF model has a better capability of evaluating and predicting HM enrichment in sediments and can be helpful for optimizing control measures for HM pollution.