µ-MO assessing the contribution of NOXtraffic emission to atmospheric pollution in modena by microscale dispersion modelling

Based on the air pollutant emission inventory data (INEMAR – Arpa Emilia-Romagna 2010) road traffic in Modena, a city in the central Po valley (Northern Italy), contributes up to the 60% of the total emission in terms of NOx, followed by Domestic Heating (15%) and Industrial Combustion (14%). Goal of the -MO project is to assess the road traffic impact on air quality in the urban area of Modena by a combined experimental and modelling approach. Dispersion of vehicular NOxwas simulated by Parallel Micro Swift Spray (PMSS, Arianet srl, Italy and Aria Technologies, France) over a domain of 6 km x 6 km, including most of the urban areas of Modena, with a horizontal resolution of 4 m. The atmospheric emission sources were estimated by merging local fleet composition data, traffic flux at rush hours simulated by PTV VISUM mobility software and direct measurements collected by radar traffic counters, provided by the Municipality of Modena. The modelling system, implemented on a 16 cores cluster (64 GB of total memory), includes PSWIFT, a parallelized mass-consistent diagnostic wind field model, and PSPRAY, a three-dimensional parallel lagrangian particle dispersion model, both able to take into account obstacles (buildings). A run of the system on an entire day has been performed and is presented. In the next step of the work, NOxatmospheric concentration measurements will be provided by the two urban air quality monitoring sites and by a set of 10 monitoring boxes distributed over the domain and featured by small sensors for NO, NO2and particulates. Among the final goals of the -MO project there is the tentative source-apportionment of urban atmospheric NOxbetween traffic emissions, domestic heating and regional background, to support epidemiological studies and finally future urban development strategies

Impact of different exposure models and spatial resolution on the long-term effects of air pollution.

Abstract Long-term exposure to air pollution has been related to mortality in several epidemiological studies. The investigations have assessed exposure using various methods achieving different accuracy in predicting air pollutants concentrations. The comparison of the health effects estimates are therefore challenging. This paper aims to compare the effect estimates of the long-term effects of air pollutants (particulate matter with aerodynamic diameter less than 10 μm, PM10, and nitrogen dioxide, NO2) on cause-specific mortality in the Rome Longitudinal Study, using exposure estimates obtained with different models and spatial resolutions. Annual averages of NO2 and PM10 were estimated for the year 2015 in a large portion of the Rome urban area (12 × 12 km2) applying three modelling techniques available at increasing spatial resolution: 1) a chemical transport model (CTM) at 1km resolution; 2) a land-use random forest (LURF) approach at 200m resolution; 3) a micro-scale Lagrangian particle dispersion model (PMSS) taking into account the effect of buildings structure at 4 m resolution with results post processed at different buffer sizes (12, 24, 52, 100 and 200 m). All the exposures were assigned at the residential addresses of 482,259 citizens of Rome 30+ years of age who were enrolled on 2001 and followed-up till 2015. The association between annual exposures and natural-cause, cardiovascular (CVD) and respiratory (RESP) mortality were estimated using Cox proportional hazards models adjusted for individual and area-level confounders. We found different distributions of both NO2 and PM10 concentrations, across models and spatial resolutions. Natural cause and CVD mortality outcomes were all positively associated with NO2 and PM10 regardless of the model and spatial resolution when using a relative scale of the exposure such as the interquartile range (IQR): adjusted Hazard Ratios (HR), and 95% confidence intervals (CI), of natural cause mortality, per IQR increments in the two pollutants, ranged between 1.012 (1.004, 1.021) and 1.018 (1.007, 1.028) for the different NO2 estimates, and between 1.010 (1.000, 1.020) and 1.020 (1.008, 1.031) for PM10, with a tendency of larger effect for lower resolution exposures. The latter was even stronger when a fixed value of 10 μg/m3 is used to calculate HRs. Long-term effects of air pollution on mortality in Rome were consistent across different models for exposure assessment, and different spatial resolutions

A practical and improved synthesis of 1, 2, 3, 4, 4a, 10, 11, 11a-octahydro-3-(5H-dibenzo-[a,d]cyclohepten-5-ilyden)-N,N-dimethylpropylamine

The aim of our work was to develop a synthetic pathway in order to obtain 1,2,3,4,4a,10,11,11a-octahydro-3- (5H-dibenzo-[a,d]cyclohepten-5-ilyden)-N,N-dimethylpropylamine, an impurity arising from the Amitriptyline industrial production and reported in the most important Pharmacopoeias. To own a standard of the aforementioned impurity is useful for any company that wants to market Amitriptyline. We performed the synthesis of the target compound in 9 steps, with a good overall yield, exploiting as a keystep a MW-assisted Heck-reaction. Moreover MW heating was successful in the optimization of the entire synthetic scheme

Application of a Lagrangian particle model to the source apportionment for primary macropollutants in Taranto area (South Italy)

modelling system has been applied to estimate the annual contribution to the total concentrations of different pollutant sources in Taranto, one of the most industrialized areas in Italy. Industrial sources, traffic, domestic heating and harbour emissions have been taken into account. Modelling system includes 3-dimensional meteorological models SWIFT-SURFPRO with the Lagrangian particle dispersion model SPRAY. The air emissions inventory was partially established using measured data, local activity indicators and emission factors. The meteorology was reconstructed by the SWIFT model from the products supplied, for the year 2007,by the national MINNI project. The annual simulation led to the identification of the main emitting sources for primary pollutants such as NOx, SO2, PM10, PM2.5 and C6H6 at receptor sites. In addition, a more refined source apportionment was achieved for industrial primary PM10, providing a useful preliminary identification of the main industrial sources emitting dangerous micropollutants, such as POPs and heavy metals