Introduction to the thematic issue: Mineral deposits exploration and environmental geochemistry: case studies in Italy and in China

Raw materials are fundamental to the economy, and hence to growth and jobs, and they are essential for maintaining and improving our quality of life. Securing reliable, sustainable and economic access to certain 'critical' raw materials is of growing concern around the globe. But it is as well a priority to acquire detailed information about the distribution of PTE and POP both at regional and local scales for environmental issues. The latter are of fundamental importance for environmental risk assessment and analysis that have a crucial role in the evaluation of human health risk, especially in mining and intensive urbanized areas. In addition, geochemical knowledge of the territory and mostly of top soils, where the main agricultural products grow, to become the foods for citizens, may be useful for land-use planning. Geochemical exploration methods are widely used to manage, visualize, analyse and interpret data for further identifying geochemical anomalies, for both the discovery of new ore bodies and for environmental purposes

Status, sources and contamination levels of organochlorine pesticide residues in urban and agricultural areas: a preliminary review in central–southern Italian soils

Organochlorine pesticides (OCPs) are synthetic chemicals commonly used in agricultural activities to kill pests and are persistent organic pollutants (POPs). They can be detected in different environmental media, but soil is considered an important reservoir due to its retention capacity. Many different types of OCPs exist, which can have different origins and pathways in the environment. It is therefore important to study their distribution and behaviour in the environment, starting to build a picture of the potential human health risk in different contexts. This study aimed at investigating the regional distribution, possible sources and contamination levels of 24 OCP compounds in urban and rural soils from central and southern Italy. One hundred and forty-eight topsoil samples (0–20 cm top layer) from 78 urban and 70 rural areas in 11 administrative regions were collected and analysed by gas chromatography–electron capture detector (GC–ECD). Total OCP residues in soils ranged from nd (no detected) to 1043 ng/g with a mean of 29.91 ng/g and from nd to 1914 ng/g with a mean of 60.16 ng/g in urban and rural area, respectively. Endosulfan was the prevailing OCP in urban areas, followed by DDTs, Drins, Methoxychlor, HCHs, Chlordane-related compounds and HCB. In rural areas, the order of concentrations was Drins > DDTs > Methoxychlor > Endosulfans > HCHs > Chlordanes > HCB. Diagnostic ratios and robust multivariate analyses revealed that DDT in soils could be related to historical application, whilst (illegal) use of technical DDT or dicofol may still occur in some urban areas. HCH residues could be related to both historical use and recent application, whilst there was evidence that modest (yet significant) application of commercial technical HCH may still be happening in urban areas. Drins and Chlordane compounds appeared to be mostly related to historical application, whilst Endosulfan presented a complex mix of results, indicating mainly historical origin in rural areas as well as potential recent applications on urban areas. Contamination levels were quantified by Soil Quality Index (SoQI), identifying high levels in rural areas of Campania and Apulia, possibly due to the intensive nature of some agricultural practices in those regions (e.g., vineyards and olive plantations). The results from this study (which is in progress in the remaining regions of Italy) will provide an invaluable baseline for OCP distribution in Italy and a powerful argument for follow-up studies in contaminated areas. It is also hoped that similar studies will eventually constitute enough evidence to push towards an institutional response for more adequate regulation as well as a full ratification of the Stockholm Convention

Exploring Soil Pollution Patterns Using Self-Organizing Maps

The geochemical composition of bedrock is the key feature determining elemental concentrations in soil, followed by anthropogenic factors that have less impact. Concerning the latter, harmful effects on the trophic chain are increasingly affecting people living in and around urban areas. In the study area of the present survey, the municipalities of Cosenza and Rende (Calabria, southern Italy), topsoil were collected and analysed for 25 elements by inductively coupled plasma mass spectrometry (ICP-MS) in order to discriminate the different possible sources of elemental concentrations and define soil quality status. Statistical and geostatistical methods were applied to monitoring the concentrations of major oxides and minor elements, while the Self-Organizing Maps (SOM) algorithm was used for unsupervised grouping. Results show that seven clusters were identified—(I) Cr, Co, Fe, V, Ti, Al; (II) Ni, Na; (III) Y, Zr, Rb; (IV) Si, Mg, Ba; (V) Nb, Ce, La; (VI) Sr, P, Ca; (VII) As, Zn, Pb—according to soil elemental associations, which are controlled by chemical and mineralogical factors of the study area parent material and by soil-forming processes, but with some exceptions linked to anthropogenic input

Radon flux estimates, from both gamma radiation and geochemical data, to determine sources, migration pathways, and related health risk: The Campania region (Italy) case study

An empirical method was applied to estimate the 222Rn fluxes distribution across the Campania region (Italy) by using both gamma-rays and U, Th, K concentrations in soils. As a first step, K, Th and U soil concentrations and 4 K, 238U and 232Th activity have been converted into their own specific activity to calculate the Terrestrial Gamma Dose Rate (TGDR). This latter has been then used to determine the 222Rn fluxes across the region. Regardless of the radiometric or geochemical origin, 222Rn fluxes reached, as expected, their maximum values in correspondence with the volcanic centres of Campania (Mt. Somma-Vesuvius, Phlegrean Fields, Mt. Roccamonfina). However, comparing the results obtained from the two different datasets, it was also possible to infer the existence of contributions to surficial 222Rn fluxes proceeding from both some underlying geological bodies and active seismogenic sources. In line with some national regulations, the 222Rn flux esteemed from gamma radiations was also used to assess the possible regional distribution of risk deriving from the indoor environmental exposure to 222Rn; results were compared with standardized incidence rates (SIRs) of lung cancer for an area on the south-western sector of Mt. Somma-Vesuvius showing a potential spatial relationship among flux data and SIRs

Exploring uni-element geochemical data under a compositional perspective

Different features of geochemical information were studied by comparing spatial distribution of concentration values and compositional data values. Geochemical data are compositional and should be treated as such to avoid spurious correlations and misleading interpretations. However, geochemists are also interested to discuss in terms of elemental concentrations. In this work the spatial distribution of Fe, Mn, Ti, Co, Cr, Ni and V based on 3535 topsoil samples collected in Campania region (Southern Italy) and analysed by ICP-MS after aqua regia digestion, is studied. Unielement maps and CoDA based maps, namely of ilr-transformed data and of two subcompositions of 3 components have been produced and interpreted. Results show that the ilr maps often show different geochemical patterns from those provided by the maps based on raw concentrations, namely for V, Fe and Co. This is not surprising as each studied ilr is a (log)ratio of an element against the others and account for the compositional variability. Nevertheless, the geochemical patterns of both raw and ilr based maps relate mostly with the geolithological features of the region: (1) (Ti, Ni, Cr)log-ratio variables are the best pathfinder in differentiating between volcanic (relative enrichment in Ti) and non-volcanic (relative enrichment in Ni and Cr) areas. (2) Soil alteration phenomena could locally enhance log-ratios of Ti due its high geochemical stability. (3) The spatial analysis of ilr-Fe and ilr Mn variables amplifies their relative degree of enrichment in correspondence of silici-clastic formations suggesting that Mn-Fe oxides of clay minerals mainly dominate the geochemical composition of the soils of the survey area. (4) Local enrichments of Cr and Ni at the main rivers' mouths and in the metropolitan areas of Naples and Salerno, possibly of anthropogenic origin, are highlighted in the 3-part subcomposition analysis. The developed exploration methodology of uni-element geochemical data under a compositional perspective leads to deeper insight and the gain is a more accurate interpretation of processes controlling soils geochemical variability

DISTRIBUZIONE GEOCHIMICA DEGLI ELEMENTI INORGANICI NEI SUOLI DEL S.I.N. LITORALE DOMIZIO FLEGREO E AGRO AVERSANO - GEOCHEMICAL DISTRIBUTION OF INORGANIC ELEMENTS IN SOILS OF DOMIZIO FLEGREO LITTORAL AND AGRO AVERSANO AREA

Il volume rappresenta un approfondimento dell’Atlante geochimico–ambientale del S.I.N. Litorale Domizio Flegreo e Agro Aversano (Lima et al., 2012). In esso vengono illustrati, infatti, i risultati ottenuti da ulteriori indagini eseguite sui suoli di questo stesso territorio. Su un’area di circa 1.555 Km2 sono stati raccolti complessivamente 967 campioni di suolo con una densità nominale di circa 1 campione ogni 1,5 km2 e il campionamento è stato infittito nelle aree a maggior impatto antropico. I suoli sono stati analizzati con una metodologia che combina l’ICP–MS e l’ICP–ES per la determinazione delle concentrazioni di 47 elementi chimici. Per ogni elemento chimico analizzato sono riportate le sue proprietà, le applicazioni, gli effetti sulla salute, nonché la sua distribuzione geochimica nei suoli attraverso la compilazione di carte geochimico–ambientali. Queste rappresentano una fotografia del momento del campionamento e potranno essere utilizzate in futuro come riferimento per la valutazione dell’impatto ambientale delle attività antropiche presenti sul territorio. Sono altresì uno strumento di notevole valenza ambientale per quanto concerne la valutazione dei tenori di fondo (background/baseline) dei vari elementi chimici esaminati. L’opera vuole quindi essere di grande utilità per tutti coloro che sono preposti al controllo ambientale, che operano nell’ambito della pianificazione e del recupero di aree contaminate, ma anche per tutti gli abitanti di quest’area, ormai nota come “Terra dei Fuochi”, venuta più volte alla ribalta per il suo degrado ambientale

Geochemical atlas of agricultural and grazing land soil of Italy (The GEMAS project in Italy)

Geochemical Mapping of Agricultural Soils (GEMAS) is a cooperation project between the Geochemistry Expert Group of EuroGeoSurveys (EGS) and Eurometaux. The GEMAS project aim was to produce soil geochemical data at the continental-scale consistent with the EU regulation REACH (Registration, Evaluation and Authorisation of Chemicals). All GEMAS project samples were analysed by variety of methods, including ICP-AES and ICP-MS following an aqua regia extraction, XRF and an MMI leach. The Italian Atlas contains colour surface maps displaying interpolated data and graduated dots, maps for regional variability of factor scores of elemental associations, and 15 baseline maps of selected elements following the Italian statutory intervention criteria. The maps in the Italian Geochemical Atlas show that the spatial distribution of chemical elements in the agricultural and grazing land soil is governed mostly by geogenic factors, even though the concentration levels of many of the investigated elements are well above the intervention limits set by the Italian environmental law (D.L. 152/2006). Regional-scale maps show that the element distribution patterns reflect the geochemistry of the major lithological units and structural lineaments, even using a very low sampling density grid of 1 sample site/2500 km2. Areas are easily detectable on the produced maps