# How May Building Morphology Influence Pedestrians' Exposure to PM2.5?
## 5 Conclusions  
The study collected the PM2.5 data using a mobile monitoring platform at a non-near-road site with different building morphological characteristics. Building morphological characteristics varied from high-density, small-sized, shorter buildings to low-density, medium to large-sized, taller buildings. The data collection strategy included multiple runs across paths representing varied building morphology. The fixed-effects panel model was used to investigate the effect of weather-related variables and building morphological characteristics on PM2.5. Unlike meteorological variables, building morphological characteristics did not change with time. A regression model was developed to find the contribution of building morphological characteristics to fixed effects extracted from the panel data model. While the weather-related variables explained variations in PM2.5, building morphological characteristics also showed positive effects on PM2.5. Furthermore, openness in the direction of the wind allowed pollutants from other areas and raised PM2.5 concentration in the area.  
The model presented in the study carried spatially autocorrelated errors even with spatial specifications, possibly due to the small study area with low PM 2.5 variability. A larger study extent and coarser unit of spatial analysis might mediate the issues of spatially autocorrelated errors. Moreover, the fixed-effects model applied the same spatial weight matrix across all runs. Depending on the weather conditions and its interactions with the surrounding built environment, the nature of spatial dependence could change. Therefore, a dynamic spatial weight matrix would be more appropriate to account for this spatial dependence. Alternatively, space-time convolution could also address the complex space-time dependence in the data overlooked in the current model specification. Nevertheless, this study showed small spatial variation in PM2.5 over a small area (\(<\)1 km\({}^{2}\)), typical of non-near-road sites with moderate variation in building morphology. The study considered interactions between wind and openness in the wind direction and overall building morphological characteristics within a 100 m buffer. Future studies can incorporate interactions between wind and building heights and measures related to the spatial arrangement of buildings to further understand the effects of buildings on PM2.5. Furthermore, variation in PM2.5 depends on many factors like weather parameters and emission sources that vary across different parts of the year. All the scenarios cannot be explored at a single site with a limited number of runs. More sites with different urban settings need to be studied over an extended period to improve our understanding of the microscale dynamics of PM2.5.  
Conceptualization, M.Y. and Y.K.; methodology, Y.K.; software, Y.K.; validation, Y.K.; formal analysis, Y.K.; investigation, Y.K.; resources, M.Y.; data curation, Y.K.; writing--original draft preparation, Y.K.; writing--review and editing, Y.K. and M.Y.; visualization, Y.K.; supervision, M.Y.; funding acquisition, M.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the University of Texas STAR program through the University of Texas at Dallas. The work was finalized when [PERSON] was serving at the US National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the University of Texas at Dallas or the US National Science Foundation.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.