Maria Macchiato

Mono- and multi-fractal investigation of scaling properties in temporal patterns of seismic sequences

Understanding the statistical properties of time-occurrence series of seismic sequences is considered one of the most pervasive scientific topics. Investigating into the patterns of seismic sequences reveals evidence of time-scaling features. This is shown in the fractal analysis of the 1986–2001 seismicity of three different seismic zones in Italy. Describing the sequence of earthquakes by means of the series of the interevent times, power-law behaviour has been found applying Hurst analysis and detrended fluctuation analysis (DFA), with consistent values for the scaling exponents. The multifractal analysis has clearly evidenced differences among the earthquake sequences. The multifractal spectrum parameters (maximum a0, asymmetry B and width W ), derived from the analysis of the shape of the singularity spectrum, have been used to measure the complexity of seismicity. 2003 Elsevier Ltd. All rights reserved.

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.

A new approach to investigate the correlation between geoelectrical time fluctuations and earthquakes in a seismic area of southern Italy

We propose a new approach to investigate the possible correlation between electrical signals and earthquakes. Good correlation has been found between the spectral power-law exponent of geoelectrical signals and the Hurst exponent of the seismicity of the area investigated. A tendency of both parameters to converge toward unity, typical of self-organized critical dynamics, is evident before the occurrence of the major event recorded in the area during the observation period.

Multifractal fluctuations in seismic interspike series

Multifractal fluctuations in the time dynamics of seismicity data have been analyzed. We investigated the interspike intervals (times between successive earthquakes) of one of the most seismically active areas of central Italy by using the Multifractal Detrended Fluctuation Analysis (MF-DFA). Analyzing the time evolution of the multifractality degree of the series, a loss of multifractality during the aftershocks is revealed. This study aims to suggest another approach to investigate the complex dynamics of earthquakes.

Heavy Metal Concentrations in Dairy Products from Sheep Milk Collected in Two Regions of Southern Italy

Inorganic or aggregated forms of chemical substances (metalloids, heavy metals etc.) in feed and food represent a severe risk for their long-term toxicological effects. Heavy metals are widely dispersed in the environment. The toxicity induced by excessive levels of some of these elements, such as chromium (Cr), cadmium (Cd), lead (Pb) and mercury (Hg), are well known [8]. The toxic metal content of milk and dairy products is due to several factors – in particular – environmental conditions, the manufacturing process and the possible contamination during several steps of the manufacturing processes. Southern Italy with more than 1.000.000 sheep represents an important source of income for rural areas of this territory. The milk from sheep is almost entirely used to produce cheese. At present, no data are available concerning levels of heavy metal contamination in milk and dairy products from sheep in Calabria and Campania – two regions of southern Italy. The aim of this work was to detect the concentrations of some heavy metals in milk collected from ewes in several farms in Calabria and Campania and to evaluate to what extent these metals may be present in dairy products for human consumption. This study is a part of a work published elsewhere [1].

Depth‐dependent time‐clustering behaviour in seismicity of southern California

Temporal fluctuations in seismicity of southern California have been investigated by means of two methods, the Allan Factor Analysis and the Detrended Fluctuation Analysis, which are used to detect the scaling behaviour of an nonstationary observational time series. Performing the time-clustering analysis varying the depth of the events, we found that the seismicity of the area reveals a tendency toward Poissonian behaviour near the depth ranges 14–16 km.

Multifractal fluctuations in earthquake-related geoelectrical signals

Multifractal fluctuations in the time dynamics of geoelectrical data, recorded in a seismic area of southern Italy, have been analysed. We find that the multifractality of the signal depends mostly on the different long-range properties for small and large fluctuations. Furthermore, we quantitatively characterized the multifractality of the geoelectrical time series, on the basis of the characteristic parameters derived from the multifractal spectrum (maximum α0, asymmetry B and width W) (Shimizu Y, Thurner S and Ehrenberger K 2002 Fractals 10 103). We then analysed the time evolution of the multifractal parameters and we found that the multifractal degree of the signal, revealed by the variation of the width of the multifractal spectrum, is enhanced in association with the occurrence of the largest seismic event. This study aims to suggest another approach to investigate the complex dynamics of geoelectrical signals.

1/fβ Fluctuations and self-similarity in earthquake dynamics: observational evidences in southern Italy

Abstract Recently, it has been determined that many statistical features of earthquakes are scale-invariant with universal values for exponents. The analysis of scaling laws has led to the development of a wide variety of physical models of seismogenesis, involving nonlinear dynamics, and it can be used to better characterize the seismicity pattern. In this work, the presence of scale-invariance properties in the seismicity of a selected area of the Southern Appennine chain is revealed. 1/fβ fluctuations are detected from the analysis of earthquake sequences using the counting statistics and, at the spatial scale, a self-similar structure in the epicentre aggregate is determined by the estimation of its fractal dimension. Finally, correlations between temporal β-exponent, fractal dimension and b-value variations are described.

Levels, chemical composition and sources of fine aerosol particles (PM1) in an area of the Mediterranean basin

Daily samples of fine aerosol particles (i.e., PM1, aerosol particles with an aerodynamic diameter less than 1.0mum) were collected in Tito Scalo - Southern Italy - from April 2006 to March 2007. Measurements were performed by means of a low-volume gravimetric sampler, and each PM1 sample was analyzed by means of Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) or Atomic Absorption Spectrometry (GFAAS and FAAS) techniques in order to determine its content in fourteen trace elements (Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Ti and Zn). During the period examined, PM1 daily concentrations ranged between 0.3microgm(-3) and 55microgm(-3) with a mean value of 8 microg m(-3), a standard deviation of 7microgm(-3) and a median value of 6microgm(-3). As far as PM1 chemical composition is concerned, the mean values of the trace element concentrations decreased in the following order: Ca>Fe>Al>Na>K>Cr>Mg>Pb>Ni approximately Ti approximately Zn>Cd approximately Cu>Mn. Principal Component Analysis (PCA) allowed the identification of three probable PM1 sources: industrial emissions, traffic and re-suspension of soil dust. Moreover, the results of a procedure applied to study the potential long-range transport contribution to PM1 chemical composition, showed that trace element concentrations do not seem to be affected by air mass origin and path. This was probably due to the strong impact of the local emission sources and the lack of the concentration measurements of some important elements and compounds that could better reveal the long-range transport influence on PM1 measurements at ground level.

Spatial variability of the time-correlated behaviour in Italian seismicity

Abstract Using the National Institute of Geophysics and Volcanology seismic catalogue, an analysis of the time-clustering behaviour of the instrumental seismicity of Italy was performed. The time span of the analysed catalogue is from 1986 to 2001, and only the events with magnitude M ≥2.4 were considered. The analysis, carried out on the full and aftershock-depleted catalogues, was performed using detrended fluctuation analysis, which permits the identification of correlated temporal structures in time series, even in the presence of trends or non-stationarities. Our findings confirm the presence of long-range behaviour in the temporal distribution of seismicity data of both full and depleted catalogues, suggesting that the clustering phenomenon is not due only to the generation of aftershocks following the occurrence of large shocks, but relies on the underlying time structure of the seismicity of Italian areas.