Mariagrazia D’Emilio

Source origin and parameters influencing levels of heavy metals in TSP, in an industrial background area of Southern Italy

In this paper, we investigate the relationships among atmospheric concentration of trace elements and some meteorological parameters. In particular, the effects of different meteorological conditions on heavy metal levels are interpreted by means of a multivariate statistical approach. The analysed variables were measured during a monitoring survey that started in 1997, and this survey was carried out in order to evaluate the atmospheric concentrations of heavy metals in the industrial area of Tito Scalo (Basilicata Region, Southern Italy). Here we present and analyse the data set collected from 1997 to 1999. The data set includes daily concentrations of total suspended particulates (TSP), daily concentrations of eight metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) in TSP and daily meteoclimatic data (temperature, rainfall, speed and wind directions). Both the concentration level and the occurrence of peak concentration events are consistent with the characteristics of the study area: abundant small and medium industrial plants in a mountainous and unpolluted zone. Regarding the origin of sources of heavy metals in TSP, the statistical procedure allows us to identify three profiles: SP1 and SP2 related to industrial sources and SP3 related to other sources (natural and/or anthropogenic). In particular, taking into account the effect of different meteorological conditions, we are able to distinguish the contribution of different fractions of the same metal in the detected source profiles.

Soil heavy metal contamination in an industrial area: analysis of the data collected during a decade

Soil contamination by heavy metals has become a serious problem mainly because, above certain concentrations, all metals have adverse effects on human health. In particular, the accumulation of heavy metals in agricultural soils leads to elevated uptake by crops and affects food quality and safety. In this paper, we present the results of a study carried out over a decade for evaluating the impact of a new industrial settlement in an area geared to agriculture and livestock and far from urban sites. We focus our study on the bioavailable fraction of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn in soil samples. Heavy metal concentrations in soil are analysed with both univariate and multivariate statistical procedures. The main goal of this paper is the development of a statistical procedure, based on a mix of multivariate analysis, able to compare field surveys carried out during different years and to characterize spatial and temporal changes in soil heavy metals concentrations.

Magnetic susceptibility measurements as proxy method to monitor soil pollution: the case study of S. Nicola di Melfi

The development of in situ, cheep, noninvasive, and fast strategies for soil monitoring is a crucial task for environmental research. In this paper, we present the results of three field surveys carried out in an industrial area of Southern Italy: S. Nicola di Melfi. The monitoring procedure is based on soil magnetic susceptibility measurements carried out by means of experimental protocols that our research group developed during the last years. This field surveys is supported by both geological characterization of the area and analytical determinations of metal concentrations in soils. Magnetic studies were carried out not only in situ but also in laboratory. Results show that, taking into account the influence due to the geomorphologic difference, soil magnetic susceptibility is an optimal indicator of the anthropogenic impact. So, our monitoring strategy discloses that the combined use of magnetic susceptibility measurements and soil geomorphology information may be used as a useful tool for the temporal monitoring of pollution evolution and for a fast screening of polluted zones.

A method for the integration of satellite vegetation activities observations and magnetic susceptibility measurements for monitoring heavy metals in soil.

We present a procedure for monitoring heavy metals in soil based on the integration of satellite and ground-based techniques, tested in an area affected by high anthropogenic pressure. High resolution multispectral satellite data were elaborated to obtain information on vegetation status. Magnetic susceptibility measurements of soils were collected as proxy variable for monitoring heavy metal presence. Chemical analyses of heavy metals were used for supporting and validating the integrated monitoring procedure. Magnetic and chemical measurements were organized in a GIS environment to be overlapped to satellite-based elaborations and to analyze the pattern distribution. Results show the presence of correlation between anomalies in vegetation activity and soil characteristics. The relationship between the distribution of normalized difference vegetation index anomalies and magnetic susceptibility values provides hints for adopting the integrated procedure as preliminary screening to minimize monitoring efforts and costs by supporting the planning activities of field campaigns.

Input strategy analysis for an air quality data modelling procedure at a local scale based on neural network

In recent years, a significant part of the studies on air pollutants has been devoted to improve statistical techniques for forecasting the values of their concentrations in the atmosphere. Reliable predictions of pollutant trends are essential not only for setting up preventive measures able to avoid risks for human health but also for helping stakeholders to take decision about traffic limitations. In this paper, we present an operating procedure, including both pollutant concentration measurements (CO, SO2, NO2, O3, PM10) and meteorological parameters (hourly data of atmospheric pressure, relative humidity, wind speed), which improves the simple use of neural network for the prediction of pollutant concentration trends by means of the integration of multivariate statistical analysis. In particular, we used principal component analysis in order to define an unconstrained mix of variables able to improve the performance of the model. The developed procedure is particularly suitable for characterizing the investigated phenomena at a local scale.

Integrated Indicators for the Estimation of Vulnerability to Land Degradation

The setting up of sustainable development strategies, able to balance the opposite demands of economic growth and environmental protection, is one of the fundamental challenges for the international community. Our developing world is experiencing growing pressures on its land, water, and food production systems and the role of the human society in determin‐ ing change within the Earth environment is becoming ever more central [1]. In this context, preserving the land productivity is a prior goal, especially in those areas, such as drylands, which are particularly fragile from an ecological point of view.

Satellite data and soil magnetic susceptibility measurements for heavy metals monitoring: findings from Agri Valley (Southern Italy)

Heavy metals pollution is a widespread problem in urbanized and industrial areas and there is a need of optimized and effective strategies for identifying and monitoring polluted areas. This study proposes an improved methodology based on Landsat satellite data and magnetic susceptibility measurements carried out in situ and in laboratory. Findings suggest that expeditious field surveys of soil magnetic susceptibility within stressed vegetated areas are a reliable indicator of soil contamination. Moreover, this procedure could provide a method for assessing heavy metals impacts and could be used to examine the effectiveness of emission control strategies.