The aerosol size distribution, particularly the number and mass distributions, plays a crucial role in understanding changes in optical properties due to hygroscopic growth, which affects visibility and radiative forcing on a regional scale. The Indo-Gangetic Plain (IGP), including National Capital Region (NCR) of Delhi, experiences severe fog and haze with reduced visibility during the post-monsoon to winter months (October-February) every year. This study reports aerosol mass size distribution over Delhi during a winter fog campaign (December 15, 2015-February 15, 2016) using a ground-based optical particle counter. The fine and coarse mode aerosols were contributed to similar to 85% and 15% to the total aerosol mass concentration during the campaign period. The characteristic changes in aerosol size distribution, effective radius, and the influence of meteorological factors, particularly relative humidity (RH) and temperature, under three visibility conditions: Vis-1 (1200 m) were investigated. Fine-mode aerosols accounted for similar to 85 % of the total aerosol mass, with their concentration increasing by a factor of 3.7 during Vis-1 and 2.3 during Vis-2 compared to Vis-3, when the effective radius of aerosol was lowest (R-eff: 0.44 mu m). Fine particle concentrations showed a positive correlation with RH (R = 0.35) and a negative correlation with visibility (R = -0.65), suggesting that the high RH and fine-mode aerosols contribute to fog formation and reduced visibility in Delhi-NCR.

Loess landforms in the Loess Plateau are typical landforms in arid and semiarid areas and have a significant impact on the environment and soil erosion. Quantitative analyses on loess landform have been employed from various perspectives. Peak intervisibility can provide the potential topographic information implied in the visual connectivity of peaks, however, its application in loess landform analysis remains unexplored. In this study, the interwoven sightlines among peaks, representing peak intervisibility, were extracted from the digital elevation model and simulated into a peak intervisibility network (PIN). Nine indices were proposed to quantify the PIN. Through a case study in Northern Shaanxi, China, three tasks were conducted, including, landform interpretation, spatial pattern mining, and landform classification. The main findings are as follows: (1) PIN responds to terrain morphology and is beneficial for loess landform interpretation. (2) The spatial patterns of PIN indices are heterogeneous and strongly coupled with the terrain morphologies, showing anisotropy and autocorrelation in spatial variations. (3) Using the light gradient boost machine classifier, the PIN index-based classification reaches a mean accuracy of 86.09%, an overall accuracy of 86% and a kappa coefficient of 0.84. These findings shed light on the applicability of PIN in loess landform analysis. Peak intervisibility not only enriches the theories and methodologies of relation-based digital terrain analysis, but also enhances our comprehension of loess landform genesis, morphology, distribution, and evolution.

Aerosols are an important factor leading to reduced visibility. In order to better comprehend the connection between visibility and aerosols, aerosol optical depth (AOD) and Angstrom exponent (AE) data from the Himawari-8 Advanced Himawari Imager (AHI) are used for validation in comparison with the data from the Aerosol Robotic Network (AERONET) observations in this paper, which amounted to 69,026 sets of data. The results indicate that the AOD of AHI is in good agreement with AERONET observations, but AE performs poorly. The correlation coefficients between the AOD of AHI and AERONET data increase with decreasing visibility and the root mean square error increase. The AE of AHI performs poorly in different visibility conditions. The conclusion drawn from further analysis of the correlation between aerosol products and meteorological factors is that the factor with the highest correlation with visibility. Mixed aerosols dominate at higher visibility and biomass burning/urban-industrial aerosols dominate at lower visibility. The visibility in a typical city (Beijing) has a strong negative correlation with AOD, a weak negative correlation with AE, and a strong correlation with aerosol radiative forcing. The reduction in visibility may be caused by the scattering and adsorption effects of aerosols. The results are important for the improvement and application of AHI aerosol products in regional pollution studies.