Identifying the Main Urban Density Factors and Their Heterogeneous Effects on PM2.5 Concentrations in High-Density Historic Neighborhoods from a Social-Biophysical Perspective: A Case Study in Beijing

Abstract

The contradiction between urban density and sustainable environmental development is increasingly prominent. Although numerous studies have examined the impact of urban density on air pollution at the macro level, most previous research at the micro scale has either neglected socioeconomic factors, failed to analyze heterogeneous effects, or ignored historic neighborhoods where high pollution coexists with high density. By considering population, commercial buildings, vegetation, and road factors, an integrated social-biophysical perspective was introduced to evaluate how urban density influences PM2.5 concentration in a historic neighborhood. The study area was divided into 56 units of 120 m × 150 m granularity, as determined by the precision of the LBS population data. The lasso regression and quantile regression were adopted to explore the main factors affecting PM2.5 and their heterogeneous effects. The results showed that (1) building density was the most important driving factor of pollutants. It had a strong and consistent negative effect on PM2.5 concentrations at all quantile levels, indicating the homogeneity effect. (2) Short-term human mobility represented by the visiting population density was the second main factor influencing pollutants, which has a significantly positive influence on PM2.5. The heterogeneous effects suggested that the areas with moderate pollution levels were the key areas to control PM2.5. (3) Vegetation Patch Shape Index was the third main factor, which has a positive influence on PM2.5, indicating the complex vegetation patterns are not conducive to PM2.5 dispersion in historic neighborhoods. Its heterogeneous effect presented a curvilinear trend, peaking at the 50th quantile, indicating that moderately polluted areas are the most responsive to improvements in vegetation morphology for PM2.5 reduction. These findings can provide effective support for the improvement of air quality in historical neighborhoods of the city’s central area.