This study aims at identifying the relationships among various variables that influence city-wide PM2.5pollution levels in the six largest cities in Texas. The variables were categorized into three groups for statistical analysis: 1) urban components (city land area, urban population, population density); 2) green space components (coverage, percentage, connectivity, and shape); and 3) meteorological factors (ambient temperature and wind speed). To identify the relationship between meteorological features and daily PM2.5concentration, we used descriptive statistics for each city and all six cities combined. A bivariate statistical test was used to examine the correlation between urban and green feature components and city-level PM2.5. To avoid a collinearity problem, the combination of variables that have perfect correlation (e.g., city land area and population) were excluded from the statistical model. Lastly, the hierarchical linear modeling (HLM) technique was used to estimate the effects of the meteorological features and urban and green space variables on the daily particle pollution level, which accounts for the clustering of particulate measurements within cities. The results showed that city-wide particulate pollution has significant, positive associations with temperature, city land area, population, population density, and shape complexity, and negative associations with wind speed, amount of green spaces, tree canopy, and connectivity of green spaces. It is notable that there are negative synergies in the cities with higher population density where there was a greater increase in the pollution level. Similarly, the cities with less green spaces exhibited a modest green space mitigation effect, whereas the cities with more green spaces had only a gradual increase in the pollution level even if it increased due to a higher temperature. This study indicates that both the quantity and spatial configuration of green spaces can play an important role in managing fine particulate matter in large cities.
|Journal||International Journal of Geospatial and Environmental Research|
|State||Published - Feb 2020|
- Air pollution
- Fine particulate matter
- Urban green spaces