Envi-MET Simulation Dataset for the LIFE AGREEN_NET Project (2019 and 2030)

Description: This dataset presents the results of environmental simulations performed using the Envi-MET software, version 5.6.1, within the framework of the LIFE AGREEN_NET project (https://www.lifeagreenet.eu/). The primary objective of this study is to evaluate the impact of green infrastructure and nature-based solutions (NBS) on urban microclimates. This research was conducted by the University of Camerino (Unicam) research group (https://saad.unicam.it), which is actively involved in the project. The simulations were specifically designed to assess the effects of NBS implementation in diverse urban areas across the Marche and Abruzzo regions of Italy. The dataset encompasses simulations for the baseline scenario (2019) and projections for 2030, allowing for the quantification of the environmental benefits resulting from the implementation of NBS. All simulations were executed using the "full forcing" setting and with specific spatial dimensions tailored to each study area. Study Areas: The simulations were conducted in the following urban areas, grouped into four homogeneous zones from a meteorological and climatic perspective: Group 1: Ancona: Coordinates 42.88516928837891, 13.915096138866966 - Google Maps Plus Code: VWP8+329 Group 2: San Benedetto del Tronto: Coordinates 42.954563321649644, 13.880004440423859 - Google Maps Plus Code: XV3J+R2C Martinsicuro: Coordinates 42.88516928837891, 13.915096138866966 - Google Maps Plus Code: VWP8+329 Group 3: Alba Adriatica: Coordinates 42.8270934482265, 13.930143609309905 - Google Maps Plus Code: RWGJ+R3J Giulianova: Coordinates 42.75507215009131, 13.963487453185918 - Google Maps Plus Code: QX47+29H Roseto degli Abruzzi: Coordinates 42.67042428855379, 14.018159687341589 - Google Maps Plus Code: M2C9+577 Tortoreto: Coordinates 42.80365629756125, 13.917095496313655 - Google Maps Plus Code: RW38+FR9 Group 4: Pineto: Coordinates 42.60987067789971, 14.066268211642692 - Google Maps Plus Code: J358+WGR Silvi: Coordinates 42.55077192258711, 14.118570435570092 - Google Maps Plus Code: H429+8C4 Pescara: Coordinates 42.45384654667533, 14.23227901358361 - Google Maps Plus Code: F63J+GWJ Climatic Analyses and Representative Day: To understand the climatic conditions in the areas of interest, a historical dataset (air temperature, relative humidity, wind speed) covering the period 2011-2021 was analysed. The Universal Thermal Climate Index (UTCI) was also calculated to assess thermal comfort. Analyses show more distinct temperature differences between the groups during the colder parts of the year, while these differences become less pronounced during warmer periods. Notably, an average peak maximum of 42°C was observed in July 2017, and peak minimums of -13°C in January 2018. For the Envi-MET simulations, a common representative day, 21st July 2019, was selected. This day was identified through an analysis evaluating the smallest deviation compared to all real days in the period 2017-2022. The 21st of July 2019 shows a deviation in the four groups ranging from 0.3% to 1% compared to the specific representative days of each group. This date was chosen for its representativeness and the availability of satellite data, and it was used as input for the simulations across all case studies. Simulation Methodology: For each study area, simulations were conducted in two phases: Baseline Scenario (2019): Simulation of current environmental conditions using data from 21st July 2019 in order to provide a baseline for comparing with the projection and to evaluate the effectiveness of the NBS. 2030 Projection with NBS: Simulation of the environmental conditions projected for 2030, assuming the implementation of nature-based solutions previously studied and catalogued. The implemented NBS were selected based on a catalogue accessible via the following https://airtable.com/app0ywMtBkqujiWfn/shr9Ol2ueLYdpu988 The Envi-MET simulations enabled the analysis of microclimatic parameters such as air temperature, relative humidity, wind speed, surface temperature, and solar radiation. This allowed for the evaluation of the effectiveness of NBS in mitigating the urban heat island effect, improving thermal comfort, and enhancing air quality. Data Format: The Envi-MET simulations enabled the analysis of microclimatic parameters such as air temperature, relative humidity, wind speed, surface temperature, and solar radiation. This allowed for the evaluation of the effectiveness of NBS in mitigating the urban heat island effect, improving thermal comfort, and enhancing air quality. Supporting Resources: The simulation data can be visualised and analysed using specific software tools. For convenient and quick data consultation, the use of "EnviReader" is recommended. EnviReader is a tool created specifically for reading Envi-MET data. It is accessible via the following publication: Marchesani, G. E., Cocci Grifoni, R. & Khodaparast, M. (2024) «EnviReader». Zenodo. doi: 10.5281/zenodo.14500979 (https://envireader.altervista.org/) Licence: This dataset is released under a Creative Commons Attribution (CC BY) licence to promote the reproducibility and use of research results.