## 5 Conclusions  
Due to the limited NAI observation sites, regional NAIs have seldom been modeled. In this study, based on the 107 NAI stations from the Fresh Air Network, we realized the spatio-temporal modeling of NAI using an RF model when SIF was incorporated. Meanwhile, we verified the contributions of different driving factors of NAI dynamics. We also inversed the spatio-temporal distribution of NAIs in Zhejiang Province. We concluded that:  
Figure 11: The population density and the ratio of annual mean NAI concentrations to population density in the different counties of Zhejiang province.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**OBJECTID** & **DEM (m)** & **SLOPE (\({}^{\circ}\))** \\ \hline Barren & 440.02 & 17.12 \\ Built-up & 54.52 & 3.20 \\ Water & 48.72 & 4.56 \\ Grassland & 344.07 & 16.39 \\ Forest & 413.30 & 18.44 \\ Cropland & 107.09 & 5.73 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The mean DEM and slope of each land type in Zhejiang Province.  
1. Topography dominated the spatial difference of NAIs in different regions, mostly indirectly, by controlling vegetation, climate, air quality, etc., among which the SIF was most related to the NAI dynamics;
2. The RF model succeeded in modeling the spatio-temporal differences in NAI among different sites, while limitations still existed;
3. Due to the dominance of topography, the NAI concentration in Zhejiang Province declined from the southwest to the northeast, and summer and winter have the highest and lowest NAI concentrations, respectively, for all land-use types.  
Even though the mean NAI concentration in Zhejiang province reaches the threshold for maintaining basic human health, NAIs per capita were quite unevenly distributed, which dramatically increases the risk of sub-health for people living in the northern and coastal regions with the highest population density.  
Conceptualization, S.T., Z.S., and Z.Z. (Zhenzhen Zhang); data curation, Z.Z. (Zhenzhen Zhang), C.W., and Z.Z. (Zhaoyang Zhang); formal analysis, Z.S.; funding acquisition, Z.Z. ([PERSON]) and C.W.; investigation, Z.S., Z.Z. ([PERSON]), Q.Z., Q.W., Y.X., and C.C.; methodology, S.T. and Z.S.; project administration, Z.Z. ([PERSON]) and C.W.; resources, X.L.; software, X.L. and B.Z.; supervision, X.L. and Z.Z. ([PERSON]); validation, S.T. and X.L.; visualization, Z.S., Z.Z. ([PERSON]), and X.G.; writing--original draft, S.T. and Z.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the \"Jinhua Science and Technology Research Program, grant numbers 2022-4-036, 2021-4-341\" and the \"Department of Science and Technology of Zhejiang Province in China, \"Pioneer\" and \"Bellwethers\" R & D projects, grant number 2022C03119\".  
The data that support the findings of this study are available, open, and free to the public and can be downloaded from the websites presented in the \"Materials and Methods\" section. We thanked the Zhejiang Fresh Air Release System ([[http://223.4.64.202/zjqxkqfb/index](http://223.4.64.202/zjqxkqfb/index)]([http://223.4.64.202/zjqxkqfb/index](http://223.4.64.202/zjqxkqfb/index)), accessed on 4 January 2021) supervised by Zhejiang Ecological Environmental Monitoring Center for providing massive public site-based NAI observations.  
The authors declare no conflict of interest.