Unprecedented levels
of urbanization have escalated urban
environmental
health issues, including increased air pollution in cities globally.
Strategies for mitigating air pollution, including green urban planning,
are essential for sustainable and healthy cities. State-of-the-art
research investigating urban greenspace and pollution metrics has
accelerated through the use of vast digital data sets and new analytical
tools. In this study, we examined associations between Google Street
View-derived urban greenspace levels and Google Air View-derived air
quality, where both have been resolved in extremely high resolution,
accuracy, and scale along the entire road network of Dublin City.
Particulate matter of size fraction less than 2.5 μm (PM2.5), nitrogen dioxide, nitric oxide, carbon monoxide, and
carbon dioxide were quantified using 5,030,143 Google Air View measurements,
and greenspace was quantified using 403,409 Google Street View images.
Significant (p < 0.001) negative associations
between urban greenspace and pollution were observed. For example,
an interquartile range increase in the Green View Index was associated
with a 7.4% [95% confidence interval: −13.1%, −1.3%]
decrease in NO2 at the point location spatial resolution.
We provide insights into how large-scale digital data can be harnessed
to elucidate urban environmental interactions that will have important
planning and policy implications for sustainable future cities.