Assessing the Feasibility of Vertical Greening Systems for Air Pollution Mitigation in Lisbon: A GIS Approach to Identifying Suitable Buildings

Abstract

Vertical Greening Systems (VGS) presents a myriad of advantages, encompassing air pollution mitigation, aesthetic enhancement, improved well-being, noise reduction, enhanced thermal comfort and others. These attributes position VGS as a valuable addition to urban environments, fostering sustainability and environmental friendliness. Functioning as natural filters, Green Walls (GW) trap airborne pollutants, contributing to a reduction in NO2 and PM10 levels. The effectiveness of GW hinges on various factors, including vegetation characteristics and physical dimensions. Integrating VGS in urban settings holds the potential to create healthier and more sustainable surroundings. This study, informed by a literature review, suggests a potential decrease of up to 34.25% in NO2 levels and 42.5% in PM10 levels. The research seeks to advance the understanding of air pollution in Lisbon, explore the potential of VGS in mitigating air pollution, and establish a framework for selecting suitable buildings for VGS implementation. The study unfolds through four primary objectives: mapping air pollution, developing a comprehensive framework with expert-defined criteria for building selection, applying this framework to identify suitable buildings, and creating comparison maps to assess the GW impact on air pollution. Expert consultations played a crucial role in identifying six key criteria for determining a building’s suitability for hosting VGS. The spatial analysis, integrating criteria such as building structure, wind effects, solar exposure, and the 3-30-300 rule, employs the Analytical Hierarchy Process (AHP) for multi-criteria analysis. The outcome is a suitability map, categorizing buildings based on their suitability for GW deployment. Air pollution analysis reveals elevated NO2 levels in Lisbon throughout 2022, exceeding legal limits by up to five times, while PM10 levels generally remained below legal thresholds. The study underscores the potential of VGS, emphasizing the spatial impact on air pollution mitigation. Comparison maps elucidate the effectiveness of implementing these structures in reducing air pollution levels. Future research opportunities include the integration of Artificial Intelligence (AI) for pattern detection, refining criteria for optimal GW deployment, expanding wind sensor deployment, continuous sensor maintenance, improving building footprint accuracy, and fostering collaborative efforts among experts. In conclusion, this study lays a robust foundation for translating theoretical insights into practical solutions. The collaborative model developed underscores VGS’s potential to significantly reduce air pollution in Lisbon, presenting a holistic approach to address environmental challenges.