Impact of urban green spaces on air quality: A study of PM10 reduction across diverse climates.

Urban areas face high particulate matter (PM10) levels, increasing the risk of respiratory and cardiovascular diseases. Green spaces can significantly reduce PM10 concentration, as shown at various scales, from boroughs to whole cities. However, long-term monitoring is needed to understand the specific mechanisms and cumulative impact of green spaces on air quality to changing pollution levels. We investigated the influence of neighbourhood green space percentage, climatic variables, and population density on PM10 deposition during the vegetation period across eight cities in contrasting climate zones over 20 years (2000-2020). We used a correlation matrix, generalized additive model, one-way ANOVA, and Tukey HSD test to analyze the impact of these factors on PM10 deposition rates, assess the role of green space percentage in reducing it, and identify significant differences in PM10 parameters at different proximities to emission sources. Cities with higher population density in warmer, drier climates had higher PM levels, since land surface temperature and wind pressure positively correlated with PM10 deposition, while relative humidity showed a negative correlation. The study found significantly higher PM10 concentrations in industrial areas (36.25 μg/m³) than in roadside areas (25.73 μg/m³) and parks (20.17 μg/m³) (p < 0.01). This highlights the need for targeted interventions in different zones. The study found a complex relationship between green space percentage and PM10 deposition rate onto plant surfaces. Our model suggests that at least 27% of green spaces as land cover can significantly reduce the particulate matter flux, although the minimum threshold can vary depending on the specific urban contexts. The study focused on the proportionate cover of green spaces; still, further investigation including quantitative aspects of urban surface forms, and traffic emissions can comprehend the climatic context and determine the optimal extent of green space required for strategic planning toward future urban sustainability initiatives.