Abstract
Poor air quality has been a major urban environmental issue in large high-density cities all over the world, and particularly in Asia, where the multiscale complex of pollution dispersal creates a high-level spatial variability of exposure level. Investigating such multiscale complexity and fine-scale spatial variability is challenging. In this study, we aim to tackle the challenge by focusing on PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm,) which is one of the most concerning air pollutants. We use the widely adopted land use regression (LUR) modeling technique as the fundamental method to integrate air quality data, satellite data, meteorological data, and spatial data from multiple sources. Unlike most LUR and Aerosol Optical Depth (AOD)-PM2.5 studies, the modeling process was conducted independently at city and neighborhood scales. Correspondingly, predictor variables at the two scales were treated separately. At the city scale, the model developed in the present study obtains better prediction performance in the AOD-PM2.5 relationship when compared with previous studies ( from 0.72 to 0.80). At the neighborhood scale, point-based building morphological indices and road network centrality metrics were found to be fit-for-purpose indicators of PM2.5 spatial estimation. The resultant PM2.5 map was produced by combining the models from the two scales, which offers a geospatial estimation of small-scale intraurban variability.
Highlights
The predictor variables selected by stepwise regression mainly reflect features that affect the PM2.5 level from the following three aspects: spatial location, built environment density, meteorological condition
Buffer radius of 250 m was identified as a major influential factor during summertime, in most cases, evidence still shows that high population density is a main factor driving which indicates the dominant effect of local building density and geometrical factors on the the accumulation of air pollution [79,80], which seems to be more in line with common pollution dispersal in summer
The critical cally significant positive correlation between PM2.5 and residential land use area as well as buffer radius of 250 m for frontal area index (FAI) is consistent with the findings from a previous study based on the number of bus stops was observed in the resultant geographically and temporally weighted regression (GTWR) models
Summary
Poor air quality has been a major urban environmental issue in cities, especially those large and compact cities in Asia, for the last several decades [1]. Urbanization alters the local climate, contributing to ambient air pollution levels in cities [2]. The interaction between the urban environment and air pollution dispersion is a complex multiscale mechanism [3]. The spatial scales of atmospheric pollution can range from a few hundred meters for urban street canyons to a few hundred kilometers for a whole Megalopolis [4]
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