Greenspace and children's lung function in China: A cross-sectional study between 2013 and 2015

Data Insights for Sustainable Cities: Associations between Google Street View-Derived Urban Greenspace and Google Air View-Derived Pollution Levels

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.

Residential surrounding greenness is associated with improved lung function in adults: a cross-sectional study in eastern China

BACKGROUND

While benefits of greenness exposure to health have been reported, findings specific to lung function are inconsistent. The purpose of this study is to assess the correlations of greenness exposure with multiple lung function indicators based on chronic obstructive pulmonary disease (COPD) monitoring database from multiple cities of Anhui province in China.

METHODS

We assessed the greenness using the annual average of normalized difference vegetation index (NDVI) with a distance of 1000-meter buffer around each local community or village. Three types of lung function indicators were considered, namely indicators of obstructive ventilatory dysfunction (FVC, FEV₁, FEV₁/FVC, and FEV₁/FEV₃); an indicator of large-airway dysfunction (PEF); indicators of small-airway dysfunction (FEF_25%, FEF_50%, FEF_75%, MMEF, FEV₃, FEV₆, and FEV₃/FVC). Linear mixed effects model was used to analyze associations of greenness exposure with lung function through adjusting age, sex, educational level, occupation, residence, smoking status, history of tuberculosis, family history of lung disease, indoor air pollution, occupational exposure, PM_2.5, and body mass index.

RESULTS

A total of 2768 participants were recruited for the investigations. An interquartile range (IQR) increase in NDVI was associated with better FVC (153.33mL, 95%CI: 44.07mL, 262.59mL), FEV₁ (109.09mL, 95%CI: 30.31mL, 187.88mL), FEV₃ (138.04mL, 95%CI: 39.43mL, 236.65mL), FEV₆ (145.42mL, 95%CI: 42.36mL, 248.47mL). However, there were no significant associations with PEF, FEF_25%, FEF_50%, FEF_75%, MMEF, FEV₁/FVC, FEV₁/FEV₆, FEV₃/FVC. The stratified analysis displayed that an IQR increase in NDVI was related with improved lung function in less than 60 years, females, urban populations, nonsmokers, areas with medium concentrations of PM_2.5 and individuals with BMI of less than 28 kg/m². Sensitivity analyses based on another greenness indice (enhanced vegetation index, EVI) and annual maximum of NDVI remained consistent with the main analysis.

CONCLUSIONS

Our findings supported that exposure to greenness was strongly related with improved lung function.