*2.2. PM2.5 Data Source and Processing*

Our previous studies examined the influences of neighborhood green space and urban morphology on PM2.5 separately, providing evidence for the effects of urban green space coverage and morphological patterns and gray space forms on PM2.5 [18,32,35]. As a series of studies, hourly PM2.5 concentrations from 2016 to 2017 were collected from monitoring stations to ensure the consistency of PM2.5 data. These data in different cities were monitored with the same standard. Because of the different locations of 37 neighborhoods, the uncontrolled factors (such as weather conditions, PM2.5 background concentration of five cities) were kept at similar levels to remove the external impact factors as much as possible and to greatly minimize evident differences, thereby performing an intercomparison. Consistent with our previous studies [32,35], three relative indicators, the range (Cin and Cde), duration (Δtin and Δtde), and rate (Cin' and Cde'), of the increase and decrease in PM2.5 concentration were calculated. To investigate pollution-level differences in the effect of the neighborhood-level built environment on PM2.5, four pollution levels, including slight (PM2.5 level ranging from 75 μg/m<sup>3</sup> to 114 μg/m3), moderate (PM2.5 level ranging from 115 μg/m3 to 150 μg/m3), heavy (PM2.5 level greater than 150 μg/m3), and overall pollution, were analyzed based on Chinese ambient air quality standards. The average of slight, moderate, and heavy pollution levels of observations was defined as the overall pollution level. The process of PM2.5 data is shown in Figure 2. Consequently, PM2.5 data of eight, three, and two days in 2016, and eight, two, and one day in 2017 were used for slight, moderate, and heavy pollution, respectively (Table S2).

**Figure 2.** The process of PM2.5 data.
