# How May Building Morphology Influence Pedestrians' Exposure to PM2.5?
## 2 Materials and Methods
### Data Preparation
#### 2.3.3 Directional Viewshed  
The amount of open area around a location could impact the PM2.5 value observed at a location. [PERSON] et al. (2018) provided evidence for the effect of the interaction between wind direction and site characteristics on PM2.5. Thus, this study calculated the open area in the direction of the wind for each segment centroid (Figure 6a) at varying distances of 100 m, 200 m, 400 m, 800 m, and 1500 m by applying viewshed analysis to determine the amount of area visible from any given location in all directions. The viewshed analysis considered 12 different wind directions, starting with 0\({}^{\circ}\) in an increment of 30\({}^{\circ}\), resulting in viewsheds at 15\({}^{\circ}\), 45\({}^{\circ}\), 75\({}^{\circ}\),..., 345\({}^{\circ}\). These directional viewsheds served as the basis to analyze the interactions of PM2.5 and openness based on the corresponding wind direction.  
\begin{table}
\begin{tabular}{c c c} \hline
**Parameter** & **Formula** & **Relevance** \\ \hline \multirow{2}{*}{Mean Building Area} & The sum of areas of all building & Measures the average size of buildings. Larger footprints in a 100-m buffer/Number of buildings in 100-m buffer & buildings provide greater horizontal enclosure, hindering PM2.5 dispersion, and vice versa. \\ \hline \multirow{2}{*}{Number of Buildings per 1000 Square Meters} & Number of buildings in a 100-m buffer \(\times\) 1000/Area of buffer in square meters & Standardized to number of buildings per 1000 m\({}^{2}\) to account for buffer size variations. The number of buildings along with the mean building area indicates the amount of built-up area. A large number of large-sized buildings occupy more space and hence leave less room for dispersion, and vice versa. \\ \hline \multirow{2}{*}{Mean Building Height} & The sum of heights of all buildings in a 100-m buffer/Number of buildings in a 100-m buffer & Taller buildings provide greater vertical enclosure. \\ \hline \multirow{2}{*}{Average Nearest-Neighbor Distance between Buildings} & Average nearest-neighbor distance between buildings. Computed using the generate near table tool from ArcGIS Pro 2.5 & Reflects building density. Tightly packed buildings hinder dispersion; greater distance between buildings allows more room for dispersion. \\ \hline \multirow{2}{*}{Building Coverage Ratio} & Area of a 100-m buffer occupied by buildings/Area of a 100-m buffer & Indicates the proportion of buffer area covered by buildings. A greater coverage ratio limits room for dispersion; and vice versa. \\ \hline \end{tabular}
\end{table}
Table 1: Building morphology calculation and relevance.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Path** & **Building** & **Mean Building** & **Number of Buildings** & **Average Distance** & **Mean Building** \\  & **Coverage Ratio** & **Area** & **per 1000 m\({}^{2}\)** & **Nearest-Neighbor** & **Height (m)** \\  & & & & **Buildings (m)** & \\ \hline Path A & 0.19 & 886 & 0.23 & 12 & 6.70 \\ \hline Path B & 0.33 & 2837 & 0.12 & 9 & 9.70 \\ \hline Path C & 0.38 & 4132 & 0.07 & 13 & 14.80 \\ \hline Path D & 0.36 & 5661 & 0.06 & 14 & 12.00 \\ \hline Path E & 0.16 & 2520 & 0.04 & 16 & 8.40 \\ \hline \end{tabular}
\end{table}
Table 2: Summary of building morphological characteristics around data collection paths.