Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens

Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

Study and implementation of control strategies for polymerization processes assisted by atmospheric pressure plasma jets

In recent years, polymerization processes assisted by atmospheric pressure plasma jets (APPJs) have received increasing attention in numerous industrially relevant sectors since they allow to coat complex 3D substrates without requiring expensive vacuum systems. Therefore, advancing the comprehension of these processes has become a high priority topic of research. This PhD dissertation is focused on the study and the implementation of control strategies for a polymerization process assisted by an atmospheric pressure single electrode plasma jet. In the first section, a study of the validity of the Yasuda parameter (W/FM) as controlling parameter in the polymerization process assisted by the plasma jet and an aerosolized fluorinated silane precursor is proposed. The surface characterization of coatings deposited under different W/FM values reveals the presence of two very well-known deposition domains, thus suggesting the validity of W/FM as controlling parameter. In addition, the key role of the Yasuda parameter in the process is further demonstrated since coatings deposited under the same W/FM exhibit similar properties, regardless of how W/FM is obtained. In the second section, the development of a methodology for measuring the energy of reactions in the polymerization process assisted by the plasma jet and vaporized hexamethyldisiloxane is presented. The values of energy per precursor molecule are calculated through the identification and resolution of a proper equivalent electrical circuit. To validate the methodology, these energy values are correlated to the bond energies in the precursor molecule and to the properties of deposited thin films. It is shown that the precursor fragmentation in the discharge and the coating characteristics can be successfully explained according to the obtained values of energy per molecule. Through a detailed discussion of the limits and the potentialities of both the control strategies, this dissertation provides useful insights into the control of polymerization processes assisted by APPJs.