###### Abstract
\begin{table}
\begin{tabular}{p{42.7 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Ref.** & **Author and Year** & **Model Name** & **Microclimate Features/Outdoor Thermal Comfort** & **Air Pollution and/or Traffic Modeling** & **Scale of Use** & **Mitigation Measures** \\ \hline
[26] & [PERSON] et al., 2017 & ENVI-met et al., 2020 & Air temperature, Mean Radiant Temperature & - & Neighborhood & Trees \\ \hline
[52] & [PERSON] et al., 2020 & ENVI-met et al., 2020 & Mean Radiant Temperature, PET & - & Neighborhood & Trees, green walls \\ \hline
[53] & [PERSON] et al., 2021 & ENVI-met et al. & Air temperature & - & District & River and trees \\ \hline
[54] & [PERSON] et al., 2021 & ENVI-met et al. & Mean Radiant Temperature, PET & - & Neighborhood & Trees, green roofs, low vegetation \\ \hline
[18] & [PERSON] et al., 2020 & ENVI-met et al. & Air temperature, Mean Radiant Temperature & - & Neighborhood & Cool materials \\ \hline
[50] & [PERSON] et al., 2011 & [PERSON] et al., 2011 & Mean Radiant Temperature & - & City & Trees, bushes \\ \hline
[55] & [PERSON] et al., 2018 & ENVI-met et al., 2020 & ENVI-met & - & CO dispersion & District & Trees \\ \hline
[5] & [PERSON] et al., 2020 & ENVI-met et al., 2020 & Air temperature & CO\({}_{2}\) storage, air quality & Neighborhood & Trees, green roofs, low vegetation \\ \hline
[8] & [PERSON] et al., 2022 & ENVI-met et al. & - & PM\({}_{2.5}\) and PM\({}_{10}\) dispersion & Neighborhood & Trees \\ \hline
[27] & [PERSON], 2022 & ENVI-met & - & O\({}_{3}\) dispersion & Street canyon & Trees \\ \hline
[56] & [PERSON], 2018 & CFD-RANS & - & NO\({}_{\text{x}}\) dispersion & Street canyon & Trees \\ \hline
[57] & [PERSON] et al., 2016 & RayMan model & Universal Thermal Climate Index & - & Neighborhood & Street tree canopies \\ \hline
[58] & [PERSON] et al., 2018 & RayMan model & Pedestrian thermal comfort & - & District & Cool materials, shading, water features \\ \hline
[59] & [PERSON] et al., 2021. & VISSUM, COPERT, R-LINE & - & CO, NO\({}_{\text{x}}\) and PM emissions and dispersion & District & Traffic flow reduction \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Main studies dealt with air pollution, urban microclimate, urban thermal comfort, numerical models, mitigation measures, and the scale of use. Despite the breadth of existing literature, significant gaps remain in both methodology and application. In particular, there is a lack of studies employing an integrated and validated microscale approach capable of simultaneously modeling traffic, air pollution, and outdoor thermal comfort. Moreover, while various urban environments have been widely investigated, university campuses remain substantially underexplored despite their distinct characteristics--such as high pedestrian density; internal traffic flows; limited green coverage; and climate vulnerability--that make them highly relevant for environmental research. Even more notable is the absence of case studies focused on Mediterranean university campuses, which often feature complex urban morphologies and climatic conditions that exacerbate environmental vulnerability. University campuses represent unique urban microcosms, characterized by internal traffic flows, pedestrian zones, open spaces, and green areas that interact to influence both air quality and thermal comfort for students, faculty, and staff. This study aims to fill this dual gap--methodological and contextual--by evaluating whether a validated integrated simulation framework can provide realistic and transferable insights into the combined effects of traffic reduction, greening, and material interventions in such a specific setting. In this context, walkability and user experience are closely tied to environmental conditions such as traffic congestion, shade availability, and vegetation cover. The lack of shaded areas, insufficient green infrastructure, and high vehicular traffic can significantly impair the livability of outdoor spaces, with consequences for sustainable mobility and environmental health [62, 63].