Previous studies have shown that bioaerosols are injected into the atmosphere during dust events. These bioaerosols may affect leeward ecosystems, human health, and agricultural productivity and may even induce climate change. However, bioaerosol dynamics have rarely been investigated along the transport pathway of Asian dust, especially in China where dust events affect huge areas and massive numbers of people. Given this situation, the Dust-Bioaerosol (DuBi) Campaign was carried out over northern China, and the effects of dust events on the amount and diversity of bioaerosols were investigated. The results indicate that the number of bacteria showed remarkable increases during the dust events, and the diversity of the bacterial communities also increased significantly, as determined by means of microscopic observations with 4,6-diamidino-2-phenylindole (DAPI) staining and MiSeq sequencing analysis. These results indicate that dust clouds can carry many bacteria of various types into downwind regions and may have potentially important impacts on ecological environments and climate change. The abundances of DAPI-stained bacteria in the dust samples were 1 to 2 orders of magnitude greater than those in the non-dust samples and reached 10⁵–10⁶ particles m⁻³. Moreover, the concentration ratios of DAPI-stained bacteria to yellow fluorescent particles increased from 5.1 % ± 6.3 % (non-dust samples) to 9.8 % ± 6.3 % (dust samples). A beta diversity analysis of the bacterial communities demonstrated the distinct clustering of separate prokaryotic communities in the dust and non-dust samples. Actinobacteria, Bacteroidetes, and Proteobacteria remained the dominant phyla in all samples. As for Erenhot, the relative abundances of Acidobacteria and Chloroflexi had a remarkable rise in dust events. In contrast, the relative abundances of Acidobacteria and Chloroflexi in non-dust samples of R-DzToUb were greater than those in dust samples. Alphaproteobacteria made the major contribution to the increasing relative abundance of the phylum Proteobacteria in all dust samples. The relative abundance of Firmicutes did not exceed 5 % in all the air samples, even though it is the predominant phylum in the surface sand samples from the Gobi Desert. These results illustrate that the bacterial community contained in dust aerosol samples has a different pattern compared with non-dust aerosol samples, and the relative abundances of airborne bacteria are different from those in the surface sand or soil and differ by location and transmitting vector.

The current study investigates the variation and physicochemical properties of ambient particulate matter (PM) in the very important location which lies in the foothills of the Hindu Kush ranges in northern Pakistan. This work investigates the mass concentration, mineral content, elemental composition and morphology of PM in three size fractions, i.e., PM₁, PM_2.5 and PM₁₀, during the year of 2019. The collected samples were characterized by microscopic and spectroscopic techniques like Fourier transform infrared spectroscopy, X-ray diffraction spectroscopy and scanning electron microscopy (SEM) coupled with energy-dispersive X-ray (EDX) spectroscopy. During the study period, the average temperature, relative humidity, rainfall and wind speed were found to be 17.9 °C, 65.83%, 73.75 mm and 0.23 m/s, respectively. The results showed that the 24 h average mass concentration of PM₁₀, PM_2.5 and PM₁ were 64 µgm⁻³, 43.9 µgm⁻³ and 22.4 µgm⁻³, respectively. The 24 h concentration of both PM₁₀ and PM_2.5 were 1.42 and 2.92 times greater, respectively, than the WHO limits. This study confirms the presence of minerals such as wollastonite, ammonium sulphate, wustite, illite, kaolinite, augite, crocidolite, calcite, calcium aluminosilicate, hematite, copper sulphate, dolomite, quartz, vaterite, calcium iron oxide, muscovite, gypsum and vermiculite. On the basis of FESEM-EDX analysis, 14 elements (O, C, Al, Si, Mg, Na, K, Ca, Fe, N, Mo, B, S and Cl) and six groups of PM (carbonaceous (45%), sulfate (13%), bioaerosols (8%), aluminosilicates (19%), quartz (10%) and nitrate (3%)) were identified.

Previous studies have shown that dust aerosols may accelerate the melting of snow and glaciers over the Tibetan Plateau. To investigate the vertical structure of dust aerosols, we conducted a ground-based observation by using multi-wavelength polarization lidar which is designed for continuous network measurements. In this study, we used the lidar observation from September to October 2020 at the Ruoqiang site (39.0°N, 88.2°E; 894 m ASL), located at the junction of the Taklimakan Desert–Tibetan Plateau. Our results showed that dust aerosols can be lifted up to 5 km from the ground, which is comparable with the elevation of the Tibetan Plateau in autumn with a mass concentration of 400–900 μg m⁻³. Moreover, the particle depolarization ratio (PDR) of the lifted dust aerosols at 532 nm and 355 nm are 0.34 ± 0.03 and 0.25 ± 0.04, respectively, indicating the high degree of non-sphericity in shape. In addition, extinction-related Ångström exponents are very small (0.11 ± 0.24), implying the large values in size. Based on ground-based lidar observation, this study proved that coarse non-spherical Taklimakan dust with high concentration can be transported to the Tibetan Plateau, suggesting its possible impacts on the regional climate and ecosystem.

Accurate estimation of the atmospheric boundary layer height (ABLH) is critically important and it mainly relies on the detection of the vertical profiles of atmosphere variables (temperature, humidity,’ and horizontal wind speed) or aerosols. Aerosol Lidar is a powerful remote sensing instrument frequently used to retrieve ABLH through the detection of the vertical distribution of aerosol concentration. A challenge is that cloud, residual layer (RL), and local signal structure seriously interfere with the lidar measurement of ABLH. A new objective technique presenting as giving a top limiter altitude is introduced to reduce the interference of RL and cloud layer on ABLH determination. Cloud layers are identified by looking for the rapid increase and sharp attenuation of the signal combined with the relative increase in the signal. The cloud layers whether they overlay the ABL are classified or are decoupled from the ABL are classified by analyzing the continuity of the signal below the cloud base. For cloud layer capping of the ABL, the limiter is determined to be the altitude where a positive signal gradient first occurs above the cloud upper edge. For a cloud that is decoupled from the ABL, the cloud base is considered to be the altitude limiter. For RL in the morning, the altitude limiter is the greatest positive gradient altitude below the RL top. The ABLH will be determined below the top limiter altitude using Haar wavelet (HM) and the curve fitting method (CFM). Besides, the interference of local signal noise is eliminated through consideration of the temporal continuity. While comparing the lidar-determined ABLH by HM (or CFM) and nearby radiosonde measurements of the ABLH, a reasonable concordance is found with a correlation coefficient of 0.94 (or 0.96) and 0.79 (or 0.74), presenting a mean of the relative absolute differences with respect to radiosonde measurements of 10.5% (or 12.3%) and 22.3% (or 17.2%) for cloud-free and cloudy situations, respectively. The diurnal variations in the ABLH determined from HM and CFM on four selected cases show good agreement with a mean correlation coefficient higher than 0.99 and a mean absolute bias of 0.22 km. Also, the determined diurnal ABLH are consistent with surface turbulent kinetic energy (TKE) combined with the time-height distribution of the equivalent potential temperature.