Giovanni Bonafè

Soil Initialization Strategy for Use in Limited-Area Weather Prediction Systems

AbstractThree diverse methods of initializing soil moisture and temperature in limited-area numerical weather prediction models are compared and assessed through the use of nonstandard surface observations to identify the approach that best combines ease of implementation, improvement in forecast skill, and realistic estimations of soil parameters. The first method initializes the limited-area model soil prognostic variables by a simple interpolation from a parent global model that is used to provide the lateral boundary conditions for the forecasts, thus ensuring that the limited-area model’s soil field cannot evolve far from the host model. The second method uses the soil properties generated by a previous limited-area model forecast, allowing the soil moisture to evolve over time to a new equilibrium consistent with the regional model’s hydrological cycle. The third method implements a new local soil moisture variational analysis system that uses screen-level temperature to adjust the soil water conten...

Leaf Area Index Specification for Use in Mesoscale Weather Prediction Systems

Abstract The energy budget at the surface is strongly influenced by the presence of vegetation, which alters the partitioning of thermal energy between sensible and latent heat fluxes. Despite its relevance, numerical weather prediction (NWP) systems often use only two parameters to describe the vegetation cover: the fractional area of vegetation occupying a given pixel and the leaf area index (LAI). In this study, the Consortium for Small-Scale Modelling (COSMO) limited-area forecast model is used to investigate the sensitivity of regional predictions to LAI assumptions over the Italian peninsula. Three different approaches are compared: a space- and time-invariant LAI dataset, a LAI specification based on Coordination of Information on the Environment (CORINE) land classes, and a Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-retrieved dataset. The three approaches resolve increasingly higher moments both in time and space of LAI probability density functions. Forecast scores employing ...

Poster 13 Long-term simulation and validation of ozone and aerosol in the Po Valley

Abstract The Po Valley is characterized by a large number of exceedances of air quality standards for ozone and PM10, as well as very strong air pollution episodes. To assist local authorities in air quality evaluation and management, the Emilia Romagna Environmental Agency (ARPA) has implemented an operational Air Quality forecast system, called NINFA (Northern Italy Network to Forecast Aerosol pollution). NINFA has been run over 1 year, simulating air pollution over Northern Italy for the period April 2003–March 2004.

Preliminary Results Of The Project “Supersito” Concerning The Atmospheric Aerosol Composition In Emilia-Romagna Region, Italy: PM Source Apportionment And Aerosol Size Distribution

The Emilia-Romagna region and its Agency for Prevention and Environment are running a project – called Supersito – the purpose of which is to gain further knowledge about the components of fine and ultrafine particles in the atmosphere. Supersito began the measurements at the end of 2011, in this paper we summarize the preliminary results observed for the aerosol size distribution and source apportionment of PM2.5 in Bologna’s urban background. Results show that nitrates, sulphates and ammonium accounts for more than 40% of the mass of PM2.5 in the cold season and for about 30% in the summer. The carbonaceous fraction (organic aerosol plus elemental carbon) is about 40% in both seasons. PMF analysis of the data coming from the results of the mass composition shows that important fractions of PM2.5 during the cold season come from

Exploitation of C- and X-band SAR images for soil moisture change detection estimation in agricultural areas (Po Valley, Italy)

This paper presents the analysis of C and X band images in the scope of soil moisture detection in agricultural fields. Archived data have been analyzed in order to understand the SAR signal behavior of vegetated fields in comparison to bare soils. The results indicate that the sensitivity to bare fields of C and X band signatures is very close, while it changes in presence of vegetation. In particular the effect is directly proportional to amount of vegetation that in this preliminary analysis has been evaluated through the NDVI variable. After this analysis, a statistical approach has been applied to SAR images to infer the information on the soil moisture values. Several experiments have been carried out by considering only C band data, only X band data and a combination of C and X band data. For bare soils, C and X band data determine very similar results and in good agreement to ground measurements. For vegetated fields, C band data tend to underestimate soil moisture due to the vegetation attenuation, while X band data, mainly influenced by vegetation, determine very poor results. Encouraging results are obtained by the combination of C and X band data, thus indicating that X band data can be used in combination to C band data in order to compensate the effect of vegetation.

Estimating deaths attributable to airborne particles: sensitivity of the results to different exposure assessment approaches

BackgroundEpidemiological evidences support the existence of an effect of airborne particulate on population health. However, few studies evaluated the robustness of the results to different exposure assessment approaches. In this paper, we estimated short term effects and impacts of high levels of particulate matter with aerodynamic diameter ≤10 μm (PM10) and ≤2.5 μm (PM2.5) in the Emilia-Romagna region (Northern Italy), one of the most polluted areas in Europe, in the period 2006–2010, and checked if the results changed when different exposure definitions were used.MethodsShort-term impact of particles on population mortality was assessed, both considering the 9 provincial capitals of the Emilia-Romagna and the region as a whole. We estimated the effects of PM10 and PM2.5 on natural mortality by combining city-specific results in a Bayesian random-effects meta-analysis, and we used these estimates to calculate impacts in terms of attributable deaths. For PM10, we considered different definitions of exposure, based on the use of the air pollutant levels measured by different monitoring stations (background or traffic monitors) or predicted by a dispersion model.ResultsAnnual average concentrations of PM10 and PM2.5 exceeding the WHO limits of 20 and 10 μg/m3 were respectively responsible for 5.9 and 3.0 deaths per 100 000 inhabitants per year in the provincial capitals, during the period 2006–2010. The total impact in the region in 2010 amounted to 4.4 and 2.8 deaths per 100 000 for PM10 and PM2.5, respectively. The impact estimates for PM10 did not substantially change when the exposure levels were derived from background or traffic monitoring stations, or arose from the dispersion model, in particular when the counterfactual value of 20 μg/m3 was considered. The effect estimates appeared more sensitive to the exposure definition.ConclusionsA reduction in particle concentrations could have produced significant health benefits in the region. This general conclusion did not change when different exposure definitions were used, provided that the same exposure assessment approach was used for both effect and impact estimations. Caution is therefore recommended when using effect estimates from the literature to assess health impacts of air pollution in actual contexts.

May Weather Types and Wind Patterns Enhance Our Understanding of the Relationship Between the Local Air Pollution and the Synoptic Circulation

Aim of this work is to better understand the connections between synoptic circulation patterns, local wind regimes and air pollution in the Po Valley which is a densely populated and heavily industrialized area. In this study we present a classification of weather types (WTs) in the Alps region performed with an objective method (COST Action 733 “Harmonization and Applications of Weather Type Classification for European regions”) based on hierarchical cluster analysis followed by a k-means cluster analysis, which is applied to the daily 500hPa time series from ERA INTERIM reanalysis. In order to take in account the strong influence of the regional wind regime on the local air quality, a classification of surface wind pattern (WPs) is performed as well with a cluster analysis technique. The link between WTs and WPs is investigated, and the statistical properties of pollutants concentration, aerosol chemical composition and dimensional distribution are analyzed in connection with WTs and WPs.

Air quality assessment in Bologna by an urban dispersion model

An urban dispersion model (ADMS?Urban) was run to calculate PM10 and NO2 concentration during a one-year period, on a district of Bologna, Italy. Moreover, the exposure of 333 children was estimated using model outputs corrected with observations. The model was able to correctly simulate the long-term statistical properties of roadside observed concentrations (such as annual mean and frequency distribution), but it failed in reproducing instantaneous values. The proposed methodology is of easy implementation, and it could be useful to identify areas with high pollutant levels, to estimate population exposure and to evaluate the benefit of pollution reduction policies.

Assessment of Tropospheric Ozone Increase in Future Climate Change Scenarios

This work aims to assess the impact of climatological increment of temperature on the tropospheric ozone concentration in the Po Valley (Italy). Creation, destruction, and transport of ozone is not only governed by the sun, via photochemical reactions, but also by atmospheric conditions. Air quality is therefore significant, and its connection with climate change important. With a statistical downscaling of data from different General Circulation Models (GCMs), and the application of a Weather Generator (WG), it was possible to generate data series of daily temperature in the future (2021–2050). These were compared to data from the past (1961–1990, from the Agroscenari project), and the present (2000–2013, measured in six stations), showing how temperatures are bound to increase. We calibrated a simple statistical model based on a stratified sampling technique over a dataset of measured ozone and temperature, predicting the summer ozone daily maximum distribution. This allowed us to determine changes in ozone concentration over the years as a consequence of temperature increase. The results suggest that the last decade can be viewed as a projection of the future “ozone climate” in the Po Valley.

UHI in the Metropolitan Cluster of Bologna-Modena: Mitigation and Adaptation Strategies

The pilot action took place in a district of Modena, the Villaggio Artigiano, characterized by the presence of disused small industrial buildings, which is part of a wider redevelopment context and regeneration process.