# Investigation of Aerosol Climatology and Long-Range Transport of Aerosols over Pokhara, Nepal
## 3 Results and Discussion
### Angstrom Exponents, Curvature of AOD Spectra, SSA, AAOD and AAE  
This section uses linear and second-order polynomial fit to study monthly and seasonal variation of spectral AOD in the wavelength ranges of 0.34 to 1.02 \(\upmu\)m. Angstrom parameters have been  
Figure 3: Temporal variation, monthly mean \(\tau_{0.50}\) (right axis), and precipitable water level in cm (left axis). The vertical dotted lines indicate the boundaries between different seasons. investigated in the past, by using spectral \(\tau_{\rm AOD}\) by distinguishing several AERONET sites with a variety of individual aerosol types such as biomass burning, urban and industrial, and desert dust ([PERSON], 2017). Figure 4 shows monthly Angstrom parameters (\(\alpha\) and \(\beta\)) and curvature of the spectral AOD curve (\(\alpha_{2}\)). We observed that the average seasonal \(\alpha\) as \(1.14\pm 0.01\) in winter, \(1.17\pm 0.07\) in the pre-monsoon season, \(1.10\pm 0.08\) in monsoon, and \(1.22\pm 0.08\) in the post-monsoon season, based on the monthly mean data. Similarly, \(\alpha\,\prime(=-2\alpha_{2})\) were obtained \(1.03\pm 0.23\) for winter, \(0.55\pm 0.14\) for pre-monsoon, \(0.23\pm 0.38\) for monsoon, and \(1.22\pm 0.08\) for post-monsoon seasons. The seasonal turbidity parameters, \(\beta\), were also found \(0.18\pm 0.05\) in winter, \(0.31\pm 0.04\) in pre-monsoon, \(0.11\pm 0.06\) in monsoon, and \(0.16\pm 0.04\) in post-monsoon seasons. Moreover, \(\beta\) gives a picture of aerosol loading with the higher the value, the higher the aerosol loading, and similarly, smaller \(\beta\) shows lower aerosol loading. We observe from Figure 4 that \(\alpha\) shows more or less the same from one season to another, even though with a significant variation of \(\tau_{0.50}\), by indicating the seasonal differences of the aerosol size spectrum. However, \(\alpha\) can be seen to be the highest in post-monsoon, followed by pre-monsoon, winter, and monsoon. We found different values of \(\alpha\,\prime\), even for a similar value of \(\alpha\), which indicates that the variation of aerosol microphysical properties can be presented by a climatological pattern of \(\alpha\,\prime\) rather than \(\alpha\). Figure 5a,b show that the significant variation on \(\alpha\,\prime\) are observed for the months even with the similar \(\alpha\). It was observed mainly in the months of a shift from one season to another season, in which prevailing air masses will also be in transition. Higher values of \(\alpha\,\prime\)(greater or close to 1) in the post-monsoon season followed by winter season provide a picture of columnar aerosol size distribution showing strong contribution by fine mode particles, which are mainly originated from anthropogenic, biomass burning, urban and industrial sources. The medium valu  
Figure 4: Angström parameters (\(\alpha\), \(\beta\)) computed by using the linear regression (solid line), and \(\alpha_{2}\) from second-order polynomial fit (dotted curve) of monthly mean spectral AOD, between years 2010–2018, in the logarithmic scale for different seasons, as indicated. pre-monsoon indicate a bimodal distribution of particles, and while the lowest values of \(\alpha\) (close to 0.2) in monsoon season indicate a dominance by coarse mode particles. The monthly mean variation of \(\tau_{0.50}\) and \(\beta\) is shown in Figure 5a. We found that \(\tau_{0.50}\) and \(\beta\) show a significant correlation (R\({}^{2}\) = 0.98 and \(p\)-value = 4.6 \(\times 10^{-11}\), scatter plot is not shown). This result shows that higher values of \(\beta\) correlating with \(\tau_{0.50}\) was associated with aerosol loading, mainly dominated by fine mode aerosols. In July and August (peak monsoon) of monsoon, we observed lowest \(\beta\) along with low \(\tau_{0.50}\), and smallest values of \(\alpha(\sim 1)\), and \(\alpha\) (smallest, closest to 0.2) supports the contribution of coarse mode particles compared to fine mode particles on overall AOD.