Exploring Climate and Air Pollution Mitigating Benefits of Urban Parks in Sao Paulo Through a Pollution Sensor Network
Year: 2025
Type: article
Abstract: Ambient air pollution is the most important environmental factor impacting human health. Urban landscapes present unique air quality challenges, which are compounded by climate change adaptation challenges, as air pollutants can also be affected by the urban heat island effect, amplifying the deleterious effects on health. Nature-based solutions have shown potential for alleviating environmental stressors, including air pollution and heat wave abatement. However, such solutions must be designed in order to maximize mitigation and not inadvertently increase pollutant exposure. This study aims to demonstrate potential applications of nature-based solutions in urban environments for climate stressors and air pollution mitigation by analyzing two distinct scenarios with and without green infrastructure. Utilizing low-cost sensors, we examine the relationship between green infrastructure and a series of environmental parameters. While previous studies have investigated green infrastructure and air quality mitigation, our study employs low-cost sensors in tropical urban environments. Through this novel approach, we are able to obtain highly localized data that demonstrates this mitigating relationship. In this study, as a part of the NERC-FAPESP-funded GreenCities project, four low-cost sensors were validated through laboratory testing and then deployed in two locations in São Paulo, Brazil: one large, heavily forested park (CIENTEC) and one small park surrounded by densely built areas (FSP). At each site, one sensor was located in a vegetated area (Park sensor) and one near the roadside (Road sensor). The locations selected allow for a comparison of built versus green and blue areas. Lidar data were used to characterize the profile of each site based on surrounding vegetation and building area. Distance and class of the closest roadways were also measured for each sensor location. These profiles are analyzed against the data obtained through the low-cost sensors, considering both meteorological (temperature, humidity and pressure) and particulate matter (PM1, PM2.5 and PM10) parameters. Particulate matter concentrations were lower for the sensors located within the forest site. At both sites, the road sensors showed higher concentrations during the daytime period. These results further reinforce the capabilities of green–blue–gray infrastructure (GBGI) tools to reduce exposure to air pollution and climate stressors, while also showing the importance of their design to ensure maximum benefits. The findings can inform decision-makers in designing more resilient cities, especially in low-and middle-income settings.
Institutions: Universidade de São Paulo, University of Surrey
Language: English
Topic: Urban Heat Island Mitigation
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,016
Funders: UK Research and Innovation, Department for Environment, Food and Rural Affairs, UK Government, Sight Research UK, Fundação de Amparo à Pesquisa do Estado de São Paulo, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, University of Surrey, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Ministério da Educação, Arts and Humanities Research Council, Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Natural Environment Research Council
Awards: G1123372118, G121811674, G1718857279, G2169368184, NERC-FAPESP Informed Greening of Cities for Urban Cooling (GreenCities), G255510393, G3053641579, G3277444435, G3285823997, G3411591628, G4799798904, G5281415664, Informed greening of cities for urban cooling (GreenCities), G5899837305, G5991734939, G6469624462, G6566911200, G6573844451, G7584932661, G8068773759, G8394028016, Reclaiming Forgotten Cities - Turning cities from vulnerable spaces to healthy places for people [RECLAIM], G874917338
OpenAlex ID: W4407695006
