Impact Assessment of Nature-Based Solutions on Urban Air Quality Using Remote Sensing

Urban areas are increasingly impacted by climate change, including air quality degradation and elevated temperatures. Building on previous research that assessed the effectiveness of Nature-Based Solutions (NBSs) in mitigating surface temperatures, this study expands the analysis to investigate the impact of NBSs on urban air quality. By integrating remote sensing data from the Sentinel-5P (TROPOMI) satellite, with daily revisits, and in situ measurements of atmospheric pollutants (NO₂, PM₁₀, and PM₂.₅), this research analyzes spatiotemporal trends in air quality and their relationship with Land Surface Temperature (LST) and the implementation of NBSs, having as a case study the city of Guimarães, Portugal.

Using machine learning models and multitemporal datasets, this study evaluates changes in air quality and LST between 2017 and 2023, with projections for 2028. The methodology combines satellite data, such as nitrogen dioxide (NO₂) concentrations, with daily and annual in situ measurements from local monitoring stations. To enhance both temporal and spatial analysis, LST data from two sources will be utilized: Landsat 8, offering high spatial resolution (30 meters) with a 16-day revisit cycle, and Sentinel-3, providing frequent revisits (1 to 2 days) but lower spatial resolution (1 km x 1 km). This integration reconciles Landsat 8’s spatial precision with Sentinel-3’s temporal frequency, enabling a more comprehensive analysis.

Preliminary findings highlight the role of NBSs, such as green roofs and urban gardens, in reducing surface temperatures. This study aims to deepen these observations by quantifying the potential of NBSs to mitigate urban air pollution and identifying critical hotspots where targeted interventions are most needed.

This research provides a replicable framework for evaluating the impacts of NBSs on air quality and urban temperature, offering practical findings for sustainable urban planning. Future directions include testing the methodology in diverse urban contexts and exploring the scalability and adaptability of NBS interventions.