Giuseppe Raspa

Towards more ecologically realistic scenarios of plant uptake modelling for chemicals: PAHs in a small forest

The importance of plants in the accumulation of organic contaminants from air and soil was recognized to the point that even regulatory predictive approaches now include a vegetation compartment or sub-compartment. However, it has recently been shown that many of such approaches lack ecological realism to properly evaluate the dynamic of air/plant/soil exchange, especially when environmental conditions are subject to sudden variations of meteorological or ecological parameters. This paper focuses on the development of a fully dynamic scenario in which the variability of concentrations of selected chemicals in air and plant leaves was studied weekly and related to the corresponding meteorological and ecological parameters, to the evaluate their influence. To develop scenarios for modelling purposes, two different sampling campaigns were performed to measure temporal variability of: 1) polycyclic aromatic hydrocarbon (PAH) concentrations in air of a clearing and a forest site, as well as in leaves of two broadleaf species and 2) two important leaf and canopy traits, specific leaf area (SLA) and leaf area index (LAI). The aim was to evaluate in detail how the variability of meteorological and ecological parameters (SLA and LAI) can influence the uptake/release of organic contaminants by plants and therefore air concentrations. A principal component analysis demonstrated how both meteorological and ecological parameters jointly influence PAH air concentrations. SLA, LAI, as well as leaf density were showed to change over time and among species and to be directly proportional to leaf/canopy uptake rate. While hazelnut had the higher leaf uptake rate, maple became the most important species when considering the canopy uptake rate due to its higher LAI. Other species specific traits, such as the seasonal variation in production of new leaves and the timing of bud burst, were also shown to influence the uptake rate of PAHs by vegetation.

Integration of an atmospheric dispersion model with a dynamic multimedia fate model: development and illustration.

Growing attention is devoted to understand the influence of the short-term variations in air concentrations on the environmental fate of semivolatile organic compounds (SVOCs) such as polycyclic aromatic hydrocarbons (PAHs). These variations are ascribable to factors such as temperature-mediated air-surface exchange and variability of planetary boundary layer (PBL) height and structure. But when investigating the fate of SVOCs at a local scale, further variability can derive from specific point source contributions. In this context, a new modeling approach (AirPlus) which integrates a previously developed model (AirFug) with an air dispersion model (AERMOD) is presented. The integrated model is illustrated for two PAHs in a Northern Italy scenario. Results show how chemical contributions deriving from background advective inflows, local emissions and a point source interact in an hourly-varying meteorological scenario to determine air concentration rapid changes and the consequent response of the soil compartment.

Rhizoremediation half-lives of PCBs: Role of congener composition, organic carbon forms, bioavailability, microbial activity, plant species and soil conditions, on the prediction of fate and persistence in soil

Polychlorinated biphenyls (PCBs) are persistent organic pollutants widely produced and used in many countries until the increasing concern about their environmental risk lead to their ban in the 1980s. Although their emissions decreased, PCBs are nowadays still present in the environment and can be reemitted from reservoir compartments such as contaminated soils. In the last two decades, there has been a growing interest in bioremediation technologies that use plants and microorganisms (i.e. rhizoremediation) to degrade organic chemicals in contaminated sites. Different studies have been conducted to investigate the potential of plant-microbe interactions in the remediation of organic chemical contaminated soils. They range from short-term and laboratory/greenhouse experiments to long-term and field trials and, when correctly set up, they could provide useful data such as PCB rhizoremediation half-lives in soil. Such type of data are important input parameters for multimedia fate models that aim to estimate the time requested to achieve regulatory thresholds in a PCB contaminated site, allowing to draw up its remediation plan. This review focuses on the main factors influencing PCB fate, persistence and bioavailability in soil including PCB mixture congener composition, soil organic carbon forms, microorganism activity, plant species and soil conditions. Furthermore, it provides an estimate of rhizoremediation half-lives of the ten PCB families starting from the results of literature rhizoremediation experiments. Finally, guidance to perform appropriate experiments to obtain comparable, accurate and useful data for fate estimation is proposed.

Seismic microzonation of the central archaeological area of Rome: results and uncertainties

The paper summarizes the results of a multidisciplinary study aimed at seismic microzonation of the Central Archeological Area of Rome including the Palatine hill, Roman Forum and Coliseum. A large amount of subsoil data, available mainly from adjacent subway lines and from the archaeological superintendence, were collected and used to plan new multidisciplinary investigations, carried out in 2010–2011. First, the paper describes the integrated subsoil model aimed at numerical modeling of site effects. The results of equivalent linear 2D site response analyses carried out on seven representative cross-sections of the area are then presented and discussed. Ground motion amplification factors defined in terms of Housner Intensity were computed in different ranges of period, covering the different fundamental vibration periods pertaining to the monuments and structures. The contouring of amplification factor values from all the numerical simulations, based on morphological and geological constrains, eventually allowed to create microzonation maps. Finally, a sensitivity study was carried out to investigate the effects of uncertainties of input parameters and soil heterogeneity on microzonation.

Multivariate Geostatistics for Soil Classification

This paper deals with soil classification for semi-detailed mapping (scale 1:25000) in an area situated in the Emilia Romagna Region (Northern Italy). The available data consist of field and laboratory measurements of more than 750 soil samples spaced at various distances. For this study six variables were considered, namely three grain sizes, pH and 2 calcium contents. Principal Component Analysis was carried out in order to further reduce the number of variables. The three first factors extracted more than 80% of the global variance and seemed to synthesize adequately the soil characteristics and to be relevant to soil genesis. Geostatistical structural analysis of the factors showed nested structures at different scale. Thus it was possible to estimate their spatial components at the sample locations through a simplified version of factorial kriging. Then, a cluster analysis was applied sequentially over the groups of samples consecutively identified on the basis of specific combinations of the components of the factors. The procedure seems to help the paedologist to identify criteria for classifying and mapping soils at detailed scale.

Towards a Direct Structural Analysis of an IRF-k

The automatic structure recognition of an Intrinsic Random Function of order k (IRF-k) is the solution that is available today and fully implemented for modelling the Generalised Covariance (GC). However, in many cases, still working in the frame of the IRF-k, it could be interesting to be able to infer the GC directly. This paper proposes a way for the direct modelling of an IRF-k based on the identification of particular authorised measures. These measures are such that the variances of the consequent experimental generalised increments, in accordance with the usual elementary polynomial models of GC, could be expressed as functions of only one parameter. Hence, it is possible to try to model the GC practically like the stationary case where the experimental variogram is plotted versus the distance h. Any such particular measure can be identified by solving one non-linear system. This paper presents the formalism of the methodology, then provides some comparisons for different cases of GC modelling, by automatic recognition and by the proposed direct modelling.

How different data supports affect geostatistical modelling: the new aggregation method and comparison with the classical regularisation and the theoretical punctual model

ABSTRACT In geostatistical analysis, often the data have different support (volume). Data with different supports can be treated separately or together but in a consistent way. In many applications, data are considered as point variable averaged over the sample volume. Regularisation of data has a significant impact on variograms and geostatistical estimations. Two methods of managing data with different supports (“integrating”) are compared: regularisation and aggregation. This paper examines the consequences of the regularisation on sample variograms and proposes another procedure to integrate samples called “aggregation”. The variogram models of integrated data are compared with the theoretical punctual model. The point-support variogram presents some advantages, such as the possibility of utilizing samples without compositing their values. But, this implies to modify the classical kriging system. The ways of managing data with different supports are applied to a complex dataset of an iron ore body. The spatial variable analysis from the composited borehole samples demonstrates the impact of the integrating methods through cross validation. Results show the effect of the variogram model in the kriging system and the accuracy of the evaluation. Also evidenced are the sensitivity to the integration method, the selected parameters and the benefits of the theoretical punctual variogram.