Numerical weather prediction models require an accurate parametrization of the energy budget at the air-ground interface, that can be obtained only through long-term atmospheric boundary layer measurements at different spatial and temporal scales. Despite their importance, such measurements are still scarce even in well-characterized areas. In this paper, a three-year dataset from four micrometeorological stations run by the Regional Agency for Environmental Protection of Lazio was analyzed to estimate albedo, zero-displacement height, roughness length and surface properties over Rome and its suburbs, characterizing differences and interconnections between urban, suburban and rural areas of the same municipality. The integral albedo coefficient at the zenith for the urban station was found to be almost twice that for suburban and rural stations. The zero-displacement height of the urban site was strongly dependent on wind direction, with values varying between 12.0 and 17.8 m, while the roughness length (≈1.5 m) was almost independent of upwind direction, but it was significantly higher than the typical values calculated for rural stations (≈0.4 m). The apparent thermal capacities and thermal conductivity at all the non-urban sites were in fair agreement with each other and typical of soils with relatively low water content, as expected for a relatively dry Mediterranean area like Rome, while the apparent thermal diffusivity reflected the presence of different soil types.

Air temperature ($T_a$) measurements are crucial for characterizing phenomena like the urban heat island (UHI), which can create critical conditions in cities during summer. This study aims to develop a machine learning-based model, namely gradient boosting, to estimate $T_a$ from geostationary satellite LST data and to apply these estimates to investigate UHI dynamics. Using Rome, Italy, as a case study, the model was trained with $T_a$ data from 15 weather stations, taking multi-temporal LST values (instantaneous and lagged up to 4 h) and additional predictors. The model achieved an overall RMSE of 0.9 °C. The resulting $T_a$ fields, with a 3 km spatial and hourly temporal resolution, enabled a detailed analysis of UHI intensity and dynamics during the summers of 2019–2020, significantly enhancing the spatial and temporal detail compared to previous studies based solely on in situ data. The results also revealed a slightly higher nocturnal UHI intensity than previously reported, attributed to the inclusion of rural areas with near-zero imperviousness, thanks to the complete mapping of $T_a$ across the domain now accessible.

Understanding temperature variations within the complex urban canopy layer (UCL) is challenging due to limitations and discrepancies between temperature measurements taken in urban canyons and on rooftops. The key question is how much these measurements differ and what factors contribute to these differences. According to the guidance by the World Meteorological Organization (WMO), rooftop observations are not encouraged for urban monitoring, due to potentially anomalous microclimatic conditions, whereas measurements within urban canyons are recommended. This is particularly relevant given the increasing number of rooftop sensors deployed through citizen science, raising questions about the representativeness of such data. This study aimed to address this knowledge gap by comparing temperatures within the UCL using two sensors: one located on a rooftop, and the other positioned within the canyon. The temperature difference between these two nearby locations followed a clear diurnal cycle, peaking at over 1 °C between 12:00 and 16:00 local time, with the canyon warmer than the rooftop. This daytime warming was primarily driven by solar radiation and, to a lesser extent, by wind speed, but only under clear-sky conditions. During the rest of the day, the temperature difference remained negligible.

This contribution presents the project "Urban hEat and pollution iSlands inTerAction in Rome and possible mitigation strategies” (RESTART), funded by the Italian Ministry of University and Research within the Research Project of National Interest program. RESTART aims to investigate the relationship between the Urban Heat Island (UHI) and the Urban Pollution Island (UPI) in Rome (Italy). The project offers a series of mitigation strategies, including tailored Nature-Based Solutions (NBS) such as green areas, green walls/roofs, trees, and ready-to-use guidelines for improving well-being and livability in urban environments.The first phase of the project involves investigating data acquired in Rome by ground-based weather and air quality monitoring instruments, belonging to international observatories and dense networks. This dataset allows us to determine the current state of UHI and UPI in Rome, analyze the meteorological processes affecting these phenomena, identify possible links between them, and examine how severe/low pollution events and extreme weather events could interact and trigger their occurrence.These environmental vulnerabilities drive the numerical investigation of city-scale ventilation, heat transport, and air pollutant removal/accumulation planned for the second phase of the project. The most up-to-date numerical modeling chain combines cutting-edge simulations with mesoscale and dispersion models (Weather Research & Forecasting Model – WRF – and Atmospheric Dispersion Modeling System – ADMS-Urban) to simulate the connection between UHI and UPI in both pre- and post-NBS implementation scenarios. The thermodynamic and chemical processes governing UHI and UPI are also analyzed, focusing on thermal comfort, pollutant dispersion, and photochemical tropospheric ozone reactions.The outcomes from the combination of numerical and experimental analyses will provide general recommendations and guidelines to be disseminated to the scientific community, the public, and policymakers.

Urban Pollution Island (UPI) and Urban Heat Island (UHI) are two major issues affecting cities' liveability and sustainability, making them more vulnerable to climate change. The former phenomenon indicates the higher concentration of air pollutants in the city compared to its rural surroundings, while the latter refers to the higher air temperatures compared to rural neighboring, primarily due to the large extent of built-up.Although the scientific community has now recognized that UPI and UHI could interact, making urban areas more susceptible to extreme weather and pollution events, the debate about the determination of the atmospheric mechanisms responsible for triggering or weakening the UPI-UHI relationship is still open.This contribution aims to quantify and characterize the UPI in the urban area of Rome (Italy) by exploiting in-situ measurements of air pollutant concentrations collected over the period 2018-2023 by air quality stations belonging to the monitoring network managed by the Regional Agency for Environmental Protection (ARPA Lazio). The meteorological dataset is supplied by dense networks of instruments providing quality-checked datasets of WMO-compliant.Different approaches for the determination of UPI are proposed and tested. Moreover, the temporal variability of the UPI Intensity is studied for both atmospheric particulate matters (PM10 and PM2.5) and the main trace gases present in metropolitan areas (NO2, NO, and O3). Furthermore, the UPI-UHI relationship during peculiar atmospheric events is investigated. For example, the UPI-UHI association is analyzed by selecting days with specific meteorological (heatwaves, calm wind, atmospheric stagnation) or air quality patterns (desert dust advection, lockdown period), mainly investigating the impact of atmospheric dynamics on UPI and UHI.The results of the present study will help to deepen our understanding of UPI, providing useful information for the scientific community and stakeholders driving urban planning and pollution control actions.