Micro–scale simulation of atmospheric emissions from power–plant stacks in the Po Valley

The atmospheric dispersion of the NOX plume that will be emitted from a new power–plant, at present under installation, was simulated at micro–scale with Micro–Swift–Spray (MSS) Model. The plant will be constructed in a residential urban area in the town of Modena (Po Valley, Northern Italy), where low wind speeds and thermal inversions are quite frequent. Simulation results point out a different behavior of urban canopy in influencing the 3D dispersion patterns among urban obstacles, according to atmospheric mixing conditions: in case of moderate wind events, urban canyon phenomena may occur with a consequent increasing of NOX concentration gradients among buildings, while with low winds the near–field influence of the buildings emphasizes pollutant accumulation. The MSS simulated NOX concentrations result always much lower than the regulatory limits for air quality. The comparison of simulation results with measured concentration data for NOX shows the importance of micro–scale dispersion modeling to perform an accurate and reliable assessment of meteorological condition effects on pollutant distribution, and the ability of MSS in providing reliable simulations of atmospheric dispersion

SURFACE PARAMETERS EVALUATED FROM SATELLITE REMOTE SENSING IMAGES FOR POLLUTANT ATMOSPHERIC DISPERSION MODELLING

This contribute deals with the use of surface parameters extracted from satellite remote sensing images for the setup of the input dataset required by pollutants atmospheric dispersion models (PATM). These models need 2D distributions (grids) of many surface parameters to model turbulence parameters, as roughness length, albedo, leaf area index and Bowen ratio. Very often these parameters are set using predefined tables defined as a function of land cover (LC). Usually, this last information is extracted from public datasets, such as, for European countries, the CORINE Land Cover (CLC). Some of these parameters can be computed directly from remote sensing. Moreover, land cover classification evaluated from remote sensing can be used to update existing LC datasets. In this work ASTER images have been used to evaluate, using a supervised classification method, the LC map of the area. This LC is used to update the CLC. Moreover, albedo was directly calculated from the image. The importance of information extracted from remote sensing is evaluated using the SPRAY lagrangian PATM. SPRAY has been used to simulate the dispersion of an inert generic pollutant emitted from two virtual sources on a 30 km x 40 km domain in a study area located at Venice (Northern Italy), where a big industrial site is found (Porto Marghera). Real (measured) meteorological data have been used

IMPATTO DELLA DIFFUSIONE DI VEICOLI ELETTRICI E A IDROGENO SULLE CONCENTRAZIONI DI PM10 IN EMILIA-ROMAGNA

PM10 is a critical pollutant for the air quality in Emilia Romagna, a Northern Italy region that includes a large part of the Po Valley. The atmospheric levels of PM10 are strongly affected by vehicular traffic emissions, due to fuel exhaust and also to tires, brake and road surface wear, and to road dust resuspension (non-exhaust emissions). This study presents atmospheric PM10 scenarios deriving from vehicular traffic emissions in Emilia Romagna as resulting in 2030 from the growth of the Fuel Cell Electric Vehicle (FCEV) and battery electric vehicles (BEV) fleet in the region. Both exhaust and non-exhaust vehicular emissions are considered, evaluated according to the most up-to-date regional bottom-up emission inventory, which attributes about 60% of total primary PM10 traffic emissions to wear processes. PM10 concentration maps for actual (2019) and 2030 scenarios are obtained by a Lagrangian dispersion model (PMSS). Preliminary results highlight the future impact on atmospheric PM10 from tires, brake and road surface wear produced by battery electric vehicles, due to their larger mass compared to FCEVs, which have smaller batteries and mass. These emissions will partially offset the lack of PM10 exhaust emissions for electric vehicles. Finally, the daily primary PM10 levels by traffic emissions simulated by PMSS and CHIMERE models were compared at specific sites relevant for the studied domain, i.e. the regulatory air quality monitoring stations, only for actual (2019) scenario

Risk of congenital anomalies around a municipal solid waste incinerator: a GIS-based case-control study

<p>Abstract</p> <p>Background</p> <p>Waste incineration releases into the environment toxic substances having a teratogenic potential, but little epidemiologic evidence is available on this topic. We aimed at examining the relation between exposure to the emissions from a municipal solid waste incinerator and risk of birth defects in a northern Italy community, using Geographical Information System (GIS) data to estimate exposure and a population-based case-control study design. By modelling the incinerator emissions, we defined in the GIS three areas of increasing exposure according to predicted dioxins concentrations. We mapped the 228 births and induced abortions with diagnosis of congenital anomalies observed during the 1998–2006 period, together with a corresponding series of control births matched for year and hospital of birth/abortion as well as maternal age, using maternal address in the first three months of pregnancy to geocode cases and controls.</p> <p>Results</p> <p>Among women residing in the areas with medium and high exposure, prevalence of anomalies in the offspring was substantially comparable to that observed in the control population, nor dose-response relations for any of the major categories of birth defects emerged. Furthermore, odds ratio for congenital anomalies did not decrease during a prolonged shut-down period of the plant.</p> <p>Conclusion</p> <p>Overall, these findings do not lend support to the hypothesis that the environmental contamination occurring around an incineration plant such as that examined in this study may induce major teratogenic effects.</p

Dispersione atmosferica a microscala di emissioni veicolari da flussi di traffico rilevati automaticamente e confronto con misure di qualità dell’aria

La stima del contributo del traffico veicolare all’inquinamento atmosferico urbano è una informazione fondamentale per la popolazione e le amministrazioni. A questo scopo è stata condotta una simulazione microscala della dispersione delle emissioni da traffico veicolare presso un incrocio trafficato lungo la circolare interna a Reggio Emilia, una città di medie dimensioni nella parte centrale della pianura Padana (Italia settentrionale). L’area studiata include una stazione della rete regionale di monitoraggio della qualità dell’aria: la stazione è classificata come sito urbano di traffico, ovvero ci si attende che la stazione sia principalmente influenzata dalle emissioni da traffico veicolare. I modelli di simulazione a microscala sono maggiormente adatti alla modellizzazione della dispersione in aree urbane, dove la concentrazione in gran parte dipende anche dalla stagnazione di aria dovuta ad edifici ed ostacoli. Micro-Swift-Spray (Aria Technologies, Francia), un modello di dispersione lagrangiano a particelle derivato direttamente dal modello Spray a scala locale, è stato utilizzato per simulare al dispersione delle emissioni da traffico veicolare (in particolare NOx e CO), tenendo conto anche della volumetria degli edifici e degli ostacoli. Un radar conta traffico installato localmente ha fornito velocità e lunghezza dei veicoli in continuo per un periodo di 12 giorni (13 – 24 gennaio 2014). Questi dati, assieme ai dettagli della composizione della flotta, sono stati usati per calcolare fattori di emissioni su misura in base alla tipologia, alimentazione, velocità e classe EURO di emissione. Sono stati prodotti dei campi 3D di concentrazione e i risultati sono stati confrontati con le misure locali di qualità dell’aria: la correlazione tra le concentrazioni orarie di NO x simulate ed osservate è risultata estremamente soddisfacente (r = 0.86). Il confronto con le misure di qualità dell’aria in condizioni di fondo urbano ha permesso di stimare meglio la performance del modello e la quantità di NO x primario e secondario al sito di studio