1,721,218 research outputs found
Recent statistical issues in multivariate receptor models
No full textIn pollution source apportionment studies, multivariate receptor models heavily rely on statistical factor analytic techniques to estimate the source-specific contributions from a large number of observed chemical concentrations. The scope of this paper is to offer a review of some recent statistical literature in order to describe the main features and recent advances of this field, advice on the possible “statistical risks” in using standard methods and finally show how some theoretical and practical failures of the commonly used methodologies can be addressed by proper statistical modeling and estimation tools. The topics addressed include: the estimation of the number of sources, model identifiability issues, the consideration of the temporal dependence in the data and systematic effects of physical factors such as meteorological conditions, possible extensions to spatial data collected by multiple receptors and the assessment of source specific health effects
Qualità dell’aria e salute: statistici, chimici ed epidemiologi ... l’unione fa la forza!
No full textUna rassegna di metodi per l’analisi della variazione spaziale del rischio di malattia tramite studi caso-controllo
No full textA critical review of some statistical issues implied by the use of multivariate receptor models
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Sensibilità alle osservazioni anomale delle statistiche EDF per la verifica dell’adattamento in distribuzione: un’analisi esplorativa
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An inla spatio-temporal model for zero-inflated marine plastic litter abundance
No full textThe marine plastic litter pollution is a worldwide growing environmental concern. Despite
its negative effects on marine ecosystems, the phenomenon is still not well-known at global and local
scale. This work aims at assessing the spatio-temporal distribution of plastic litter amounts found at the
sea-floor in a region of the central Mediterranean (Ionian sea). Inspired by species distribution models,
we propose a two-parts model to accommodate the excess of zeros and the spatio-temporal correlation
characterizing abundance monitoring data. A common spatial effect that links the plastic abundances
and the probabilities of occurrences is implemented with the Stochastic Partial Differential Equation
approach extended to a non-stationary barrier model. The INIA methodology allows to efficiently
perform Bayesian inference to fit complex spatio-temporal models including effects of environmental
covariates and enables to investigate the assemblages of plastic litter over the study region
An integrated georeferenced dataset of public investments for soil defence in Italy
No full textThe dataset collects and harmonizes financial data about public works in Italy, focusing on soil defence investments. The data are sourced from three distinct platforms: the Italian Ministry of Economics and Finance's open data platform OpenBDAP, the OpenCoesione website, concerned with interventions framed in cohesion policies financed by additional resources from the European and national budgets, and the ReNDiS database, provided by the Italian Institute for Environmental Protection and Research (ISPRA), that exclusively gathers information about public works in soil defence. The data records belonging to these three sources are linked by a unique project code (CUP), ensuring that there is no duplication of data. The OpenBDAP and OpenCoesione repositories report financial variables classified into various funds. In contrast, the ReNDiS database only provides the total amount of financial resources allocated to each intervention. Consequently, the merged dataset consolidates these financial variables into one, representing the total investment amount. For the first two databases this aggregate is derived by summing the financial flows from the different funds. Geographical referencing has been added to each intervention and each financial observation is associated with an Italian municipality. The database includes information on the region, province, and municipality for each record. Each database entry has also been equipped with the coordinates of the municipality's centroid and with the polygonal shape of the municipality area. Overall, the merged dataset encompasses 28 variables reporting three descriptive variables, one financial variable representing the total amount of financial resources, six geographic variables representing the codes and names of regions, provinces, and municipalities, sixteen variables referring to key dates of the process of public works, two geographical references variables respectively representing the centroids and the shape polygons of the municipality. This comprehensive dataset allows to analyse the spatial distribution of the resources allocated to soil defence investments. It offers insights to policymakers striving to allocate resources more efficiently, thereby fostering sustainable land management practices and ensuring the long-term health of the Italian ecosystems. The dataset can be complemented with additional information related to various concomitant aspects such as those pertaining to the environmental and socio-economic fields. This integration allows for broad analysis of the relationships between soil defence efforts and surrounding environmental and socio-economic contexts
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