Despite the progress made in recent years, reliable modeling of indoor air quality is still far from being obtained. This requires better chemical characterization of the pollutants and airflow physics included in forecasting tools, for which field observations conducted simultaneously indoors and outdoors are essential. The project “Integrated Evaluation of Indoor Particulate Exposure” (VIEPI) aimed at evaluating indoor air quality and exposure to particulate matter (PM) of humans in workplaces. VIEPI ran from February 2016 to December 2019 and included both numerical simulations and field campaigns carried out in universities and research environments located in urban and non-urban sites in the metropolitan area of Rome (Italy). VIEPI focused on the role played by micrometeorology and indoor airflow characteristics in determining indoor PM concentration. Short- and long-term study periods captured diurnal, weekly, and seasonal variability of airflow and PM concentration. Chemical characterization of PM10, including the determination of elements, ions, elemental carbon, organic carbon, and bioaerosol, was also carried out. Large differences in the composition of PM10 were detected between inside and outside as well as between different periods of the day and year. Indoor PM composition was related to the presence of people, to the season, and to the ventilation regime.

The present paper aims to show and discuss the long\ud term and continuous recordings of both meteorological and\ud hydrodynamic data collected in a semi enclosed sea. The site in\ud question is composed by the Mar Grande and Mar Piccolo basins\ud (Southern Italy), which are mutually connected. In turn, the Mar\ud Grande is joined to the Ionian Sea by means of two openings.\ud Therefore, the system shows features typical of a lagunar\ud environment, which is also affected by coastal heavy industry and\ud anthropic pressure, thus being highly vulnerable. A monitoring of its\ud hydrodynamics could be useful, allowing both to check the real-time\ud status of the basin and promptly intervene when accidents occur and\ud to create a dataset necessary to calibrate and validate modelling\ud systems providing forecasts. To this, in the framework of the Italian\ud flagship Project RITMARE, a meteo-oceanographic station, a wavecurrent\ud meter and a tide gauge have been installed in the area, since\ud December 2013. In detail, measurements of wind, waves, tides and\ud current profiles, are acquired on site with different sampling\ud frequencies and are transmitted on a web cloud by a router 3G, where\ud they are stored, thus being available for download by remote users.\ud The data acquisition and processing is managed by the research group\ud of the Department of Civil, Environmental, Building, Engineering\ud and Chemistry (Technical University of Bari). All the acquired data\ud are archived in monthly time-series, examined and discussed.The analysis of currents is made in two different measuring\ud stations for the whole year 2015, as well as the analysis of wave data.\ud On the contrary, tide data have been assessing only recently, since\ud August 2015. Comparisons with available recordings of the year\ud 2014 are examined. Also spatial and temporal correlations of both\ud waves and currents are discussed. Finally, tidal trends are shown,\ud consistent with current inversions

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We present turbulent Schmidt number ( ) estimations above threedimensional urban canopies, where is a property of the flow defined as the ratio of the eddy diffusivity of momentum ( ) to the eddy diffusivity of mass ( ). Despite the fact that modelling is of great interest, inter alia, for pollutant dispersion simulations conducted via computational fluid dynamics, no universal value is known. Simultaneous measurements of fluid velocity and mass concentration are carried out in a water channel for three staggered arrays of cubical obstacles corresponding to isolated flow, wake-interference, and skimming-flow regimes. A passive tracer is released from a continuous point source located at a height 1.67 , where H is the obstacle height. The results show an increase of with height above the canopy for all three arrays, with values at 2 ( 0.6) about double compared to that at . The observed agrees well with that modelled by using a simple formulation for based on expressions for and published in previous studies. Comparisons with other models found in the literature are also presented and discussed.

A neutral boundary layer was generated in the laboratory to analyze the mean\ud velocity field and the turbulence field within and above an array of two‐dimensional obstacles\ud simulating an urban canopy. Different geometrical configurations were considered in order to\ud investigate the main characteristics of the flow as a function of the aspect ratio (AR) of the canopy.\ud To this end, a summary of the two‐dimensional fields of the fundamental turbulence parameters is\ud given for AR ranging from 1 to 2. The results show that the flow field depends strongly on AR only\ud within the canyon, while the outer flow seems to be less sensitive to this parameter. This is not\ud true for the vertical momentum flux, which is one of the parameters most affected by AR, both\ud within and outside the canyon. The experiments also indicate that, when (i.e. the\ud skimming flow regime), the roughness sub‐layer extends up to a height equal to 1.25 times the\ud height of the obstacles (H), surmounted by an inertial sub‐layer that extends up to 2.7 H. In\ud contrast, for (i.e. the wake‐interference regime) the inertial sub‐layer is not present.\ud This has significant implications when using similarity laws for deriving wind and turbulence\ud profiles in canopy flows. Furthermore, two estimations of the viscous dissipation rate of turbulent\ud kinetic energy of the flow are given. The first one is based on the fluctuating strain rate tensor,\ud while the second is related to the mean strain rate tensor. It is shown that the two expressions\ud give similar results, but the former is more complicated, suggesting that the latter might be used\ud in numerical models with a certain degree of reliability. Finally, the data presented can also be\ud used as a dataset for the validation of numerical models