Cost-effective reductions of PM2.5 concentrations and exposure in Italy

In recent years several European air pollution policies have been based on a cost-effectiveness approach. In the European Union, the European Commission starts using the multi-pollutant, multi-effect GAINS (Greenhouse Gas Air Pollution Interactions and Synergies) model to identify cost-effective National Emission Ceilings and specific emission control measures for each Member State to reach these targets. In this paper, we apply the GAINS methodology to the case of Italy with 20 subnational regions. We present regional results for different approaches to environmental target setting for PM2.5 pollution in the year 2030. We have obtained these results using optimization techniques consistent with those of GAINS-Europe, but at a higher resolution. Our results show that an overall health-impact oriented approach is more cost-effective than setting a nation-wide limit value on ambient air quality, such as the one set for the year 2030 by the European Directive on ambient air quality and cleaner air for Europe. The health-impact oriented approach implies additional emission control costs of 153 million €/yr on top of the baseline costs, compared to 322 million €/yr for attaining the nation-wide air quality limit. We provide insights into the distribution of costs and benefits for regions within Italy and identify the main beneficiaries of a health-impact approach over a limit-value approach

LIFE Med Hiss: An innovative cohort design for public health

The aim of MED HISS methodology was to test the effectiveness of a low-cost approach to study long-term effects of air pollution, applicable in all European countries. This approach is potentially exportable to other environmental issues where a cohort representative of the country population is needed. The cohort is derived from the National Health Interview Survey, compulsory in European countries, which has information on individual lifestyle factors. In Life Med Hiss approach, subjects recruited have been linked at individual level with health data and have been then followed-up for mortality and hospital admissions outcomes. Exposure values of air pollution (PM2.5 and NO 2 ) have been assigned using national dispersion models, enhanced by the information derived from monitoring station with data fusion techniques, and then upscaled at municipality level (highest level of detail achievable for the Italian Survey). Results for mortality have been used to test the effectiveness of this methodology and are encouraging if compared with European ones. The advantages of this technique are summarized below: • It uses a cohort already available and compulsory in European countries• It uses air quality modelling data, available for most of the countries• It permits to implement versatile environmental surveillance system

Long term effect of air pollution on incident hospital admissions: Results from the Italian Longitudinal Study within LIFE MED HISS project

Background: The LIFE MED HISS project aims at setting up a surveillance system on the long term effects of air pollution on health, using data from National Health Interview Surveys and other currently available sources of information in most European countries. Few studies assessed the long term effect of air pollution on hospital admissions in European cohorts. Objective: The objective of this paper is to estimate the long term effect of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) on first-ever (incident) cause-specific hospitalizations in Italy. Methods: We used data from the Italian Longitudinal Study (ILS), a cohort study based on the 1999–2000 National Health Interview Survey (NHIS), followed up for hospitalization (2001–2008) at individual level. The survey contains information on crucial potential confounders: occupational/educational/marital status, body mass index (BMI), smoking habit and physical activity. Annual mean exposure to PM2.5 and NO2 was assigned starting from simulated gridded data at spatial resolution of 4 × 4 km2 firstly integrated with data from monitoring stations and then up-scaled at municipality level. Statistical analyses were conducted using Cox proportional hazard models with robust variance estimator. Results: For each cause of hospitalization we estimated the hazard ratios (HRs) adjusted for confounders with 95% Confidence Interval (CI) related to a 10 μg/m3 increase in pollutants. For PM2.5 and NO2, respectively, we found positive associations for circulatory system diseases [1.05(1.03–1.06); 1.05(1.03–1.07)], myocardial infarction [1.15(1.12–1.18); 1.15(1.12–1.18)], lung cancer [1.18(1.10–1.26); 1.20(1.12–1.28)], kidney cancer [1.24(1.11–1.29); 1.20(1.07–1.33)], all cancers (but lung) [1.06(1.04–1.08); 1.06(1.04–1.08)] and Low Respiratory Tract Infections (LRTI) [1.07 (1.04–1.11); 1.05 (1.02–1.08)]. Discussion: Our results add new evidence on the effects of air pollution on first-ever (incident) hospitalizations, both in urban and rural areas. We demonstrated the feasibility of a low-cost monitoring system based on available data

La diffusione dei GIS nelle istituzioni pubbliche di un paese in via di sviluppo. Una indagine diretta per valutare la fattibilita' di un'applicazione GIS a supporto del Ministero dell'Industria e del Commercio del Paraguay per la pianificazione delle attivita' produttive

La ricerca descritta nel rapporto e' stata realizzata nell'ambito del 'Proyecto del apoyo al desarollo industrial del Paraguay' obiettivo programmatico 'Mapa territorial para la promocion de la localizacion de actividades industriales'. Modulo 4 'Ordinamento Territorial'Consiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7 Rome / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

A Hybrid Sampling Strategy for Sparse Magnetic Resonance Imaging

A hybrid acquisition sequence for Sparse 2D Magnetic Resonance Imaging (MRI) is presented. The method combines random sampling of Cartesian trajectories with an adaptive 2D acquisition of radial projections. It is based on the evaluation of the information content of a small percentage of the k-space data collected randomly, to identify radial blades of k-space coefficients having maximum information content. An entropy function is defined on the power spectrum of the projections for evaluating the information content of each direction. The method has been tested on MRI images and it was also compared to the weighted Compressed Sensing. Some results are reported and discussed

Creazione di una Banca dati ed elaborazione dei dati pregressi dello stato qualitativo della Sacca di Goro

Provincia di Ferrara Servizio Risorse idriche e Tutela Ambientale U:O:P:C: Acque costiere ed economia ittic

Intracellular Shigella remodels its LPS to dampen the innate immune recognition and evade inflammasome activation

110(46):E4345-5