TY - JOUR
T1 - Data Insights for Sustainable Cities
T2 - Associations between Google Street View-Derived Urban Greenspace and Google Air View-Derived Pollution Levels
AU - Sabedotti, Maria E.S.
AU - O’Regan, Anna C.
AU - Nyhan, Marguerite M.
N1 - Publisher Copyright:
© 2023 The Authors. Published by American Chemical Society
PY - 2023/12/5
Y1 - 2023/12/5
N2 - 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.
AB - 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.
KW - air pollution
KW - Google Air View
KW - Google Street View
KW - sustainable cities
KW - urban analytics
KW - urban greenspace
UR - https://www.scopus.com/pages/publications/85178574887
U2 - 10.1021/acs.est.3c05000
DO - 10.1021/acs.est.3c05000
M3 - Article
C2 - 37972280
AN - SCOPUS:85178574887
SN - 0013-936X
VL - 57
SP - 19637
EP - 19648
JO - Environmental Science and Technology
JF - Environmental Science and Technology
IS - 48
ER -