The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on Suomi National Polar-orbiting Partnership (S-NPP) satellite in late 2011. Similar to the Moderate resolution Imaging Spectroradiometer (MODIS), VIIRS observes top-of-atmosphere spectral reflectance and is potentially suitable for retrieval of the aerosol optical depth (AOD). The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. The “MODIS-like” VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the “dark-target” algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012–31 March 2014 at three sites. These sites represent three different surface types: urban (Beijing), suburban (XiangHe) and rural (Xinglong). Firstly, we evaluate the retrieved spectral AOD. For the three sites, VIIRS_EDR AOD at 550 nm shows a positive mean bias (MB) of 0.04–0.06 and the correlation of 0.83–0.86, with the largest MB (0.10–0.15) observed in Beijing. In contrast, VIIRS_ML AOD at 550 nm has overall higher positive MB of 0.13–0.14 and a higher correlation (0.93–0.94) with CE318 AOD. Secondly, we evaluate the aerosol model types assumed by each algorithm, as well as the aerosol optical properties used in the AOD retrievals. The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. The overall accuracy rate of the aerosol model used in VIIRS_ML over NCP three sites (0.48) is higher than that of VIIRS_EDR (0.27). The differences in Single Scattering Albedo (SSA) at 670 nm between VIIRS_ML and CE318 are mostly less than 0.015, but high seasonal differences are found especially over the Xinglong site. The values of SSA from VIIRS_EDR are higher than that observed by CE318 over all sites and all assumed aerosol modes, with a positive bias of 0.02–0.04 for fine mode, 0.06–0.12 for coarse mode and 0.03–0.05 for bi-mode at 440 nm. The overestimation of SSA but positive AOD MB of VIIRS_EDR indicate that other factors (e.g., surface reflectance characterization or cloud contamination) are important sources of error in the VIIRS_EDR algorithm, and their effects on aerosol retrievals may override the effects from non-ideality in these aerosol models.

We present the mapping at fine spatial scale of aerosol optical properties using a mobile laboratory equipped with LIDAR (Light Detection And Ranging), sun photometer and in situ instruments for performing on-road measurements. The mobile campaign was conducted from 9 May to 19 May 2017 and had the main objective of mapping the distribution of pollutants in the Beijing and North China Plain (NCP) region. The highest AOD (Aerosol Optical Depth) at 440 nm of 1.34 and 1.9 were recorded during two heavy pollution episodes on 18 May and 19 May 2017, respectively. The lowest Planetary Boundary Layer (PBL) heights (0.5–1.5 km) were recorded during the heavy pollution events, correlating with the highest AOD and southern winds. The transport of desert dust from the Gobi Desert was captured during the mobile measurements, impacting Beijing during 9–13 May 2017. Exploring the NCP outside Beijing provided datasets for regions with scarce ground measurements and allowed the mapping of high aerosol concentrations when passing polluted cities in the NCP (Baoding, Tianjin and Tangshan) and along the Binhai New Area. For the first time, we provide mass concentration profiles from the synergy of LIDAR, sun photometer and in situ measurements. The case study along the Binhai New Area revealed mean extinction coefficients of 0.14 ± 0.10 km⁻¹ at 532 nm and a mass concentration of 80 ± 62 μg/m³ in the PBL (<2 km). The highest extinction (0.56 km⁻¹) and mass concentrations (404 μg/m³) were found in the industrial Binhai New Area. The PM₁₀ and PM_2.5 fractions of the total mass concentration profiles were separated using the columnar size distribution, derived from the sun photometer measurements. This study offers unique mobile datasets of the aerosol optical properties in the NCP for future applications, such as satellite validation and air quality studies.

Knowledge of vertical air motion in the atmosphere is important for both meteorological and climate studies due to its impact on clouds, precipitation and the vertical transport of air masses, heat, momentum, and composition. The vertical velocity (VV) of air is among the most difficult and uncertain quantities to measure due to its generally small magnitude and high temporal and spatial variability. In this study, a descending radiosonde system is developed to derive VV at the low and middle troposphere in north China during the summer months. The VV is estimated from the difference between the observed radiosonde descent speed and the calculated radiosonde descent speed in still air based on the fluid dynamic principle. The results showed that the estimated VV generally ranged from −1 m/s to 1 m/s, accounting for 80.2% of data points. In convective conditions, a wider distribution of the VV was observed, which was skewed to large values relative to those in nonconvective conditions. The average VV throughout the entire profile was close to 0 m/s under nonconvective conditions. In contrast, distinctive vertical air motions below 5 km above the ground were recorded under convective activities. Vigorous air motions with an absolute VV >2 m/s were occasionally observed and were often associated with the occurrence of cloud layers. Moreover, the detailed structure of the instant air motion near the cloud boundaries (i.e., top and base), with an absolute VV >10 m/s in convective weather systems, was clearly revealed by this technique. The uncertainty estimation indicated that this method has the potential to capture and describe events with vertical air motions >0.69 m/s, which is useful for a convective weather study. Further studies are required to carefully assess the accuracy and precision of this novel VV estimation technique.