An Observing System Simulation Experiment Framework for Air Quality Forecasts in Northeast Asia: A Case Study Utilizing Virtual Geostationary Environment Monitoring Spectrometer and Surface Monitored Aerosol Data

Prior knowledge of the effectiveness of new observation instruments or new data streams for air quality can contribute significantly to shaping the policy and budget planning related to those instruments and data. In view of this, one of the main purposes of the development and application of the Observing System Simulation Experiments (OSSE) is to assess the potential impact of new observations on the quality of the current monitoring or forecasting systems, thereby making this framework valuable. This study introduces the overall OSSE framework established to support air quality forecasting and the details of its individual components. Furthermore, it shows case study results from Northeast Asia and the potential benefits of the new observation data scenarios on the PM2.5 forecasting skills, including the PM data from 200 virtual monitoring sites in the Gobi Desert and North Korean non-forest areas (NEWPM) and the aerosol optical depths (AOD) data from South Korea’s Geostationary Environment Monitoring Spectrometer (GEMS AOD). Performance statistics suggest that the concurrent assimilation of the NEWPM and the PM data from current monitoring sites in China and South Korea can improve the PM2.5 concentration forecasts in South Korea by 66.4% on average for October 2017 and 95.1% on average for February 2018. Assimilating the GEMS AOD improved the performance of the PM2.5 forecasts in South Korea for October 2017 by approximately 68.4% (~78.9% for February 2018). This OSSE framework is expected to be continuously implemented to verify its utilization potential for various air quality observation systems and data scenarios. Hopefully, this kind of application result will aid environmental researchers and decision-makers in performing additional in-depth studies for the improvement of PM air quality forecasts.

Molecular Identification of Keratinase DgokerA from Deinococcus gobiensis for Feather Degradation

Keratin is a tough fibrous structural protein that is difficult to digest with pepsin and trypsin because of the presence of a large number of disulfide bonds. Keratin is widely found in agricultural waste. In recent years, especially, the development of the poultry industry has resulted in a large accumulation of feather keratin resources, which seriously pollute the environment. Keratinase can specifically attack disulfide bridges in keratin, converting them from complex to simplified forms. The keratinase thermal stability has drawn attention to various biotechnological industries. It is significant to identify keratinases and improve their thermostability from microorganism in extreme environments. In this study, the keratinases DgoKerA was identified in Deinococcus gobiensis I-0 from the Gobi desert. The amino acid sequence analysis revealed that DgoKerA was 58.68% identical to the keratinase MtaKerA from M. thermophila WR-220 and 40.94% identical to the classical BliKerA sequence from B. licheniformis PWD-1. In vitro enzyme activity analysis showed that DgoKerA exhibited an optimum temperature of 60 °C, an optimum pH of 7 and a specific enzyme activity of 51147 U/mg. DgoKerA can degrade intact feathers at 60 °C and has good potential for industrial applications. The molecular modification of DgoKerA was also carried out using site-directed mutagenesis, in which the mutant A350S enzyme activity was increased by nearly 30%, and the results provide a theoretical basis for the development and optimization of keratinase applications.

Mobile on-Road Measurements of Aerosol Optical Properties during MOABAI Campaign in the North China Plain

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 PM2.5 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.

Statistical Modeling for PM10, PM2.5 and PM1 at Gangneung Affected by Local Meteorological Variables and PM10 and PM2.5 at Beijing for Non- and Dust Periods

Multiple statistical prediction modeling of PM10, PM2.5 and PM1 at Gangneung city, Korea, was performed in association with local meteorological parameters (air temperature, wind speed and relative humidity) and PM10 and PM2.5 concentrations of an upwind site in Beijing, China, in the transport route of Chinese yellow dusts which originated from the Gobi Desert and passed through Beijing to the city from 18 March to 27 March 2015. Before and after the dust periods, the PM10, PM2.5 and PM1 concentrations showed as being very high at 09:00 LST (the morning rush hour) by the increasing emitted pollutants from vehicles and flying dust from the road and their maxima occurred at 20:00 to 22:00 LST (the evening departure time) from the additional pollutants from resident heating boilers. During the dust period, these peak trends were not found due to the persistent accumulation of dust in the city from the Gobi Desert through Beijing, China, as shown in real-time COMS-AI satellite images. Multiple correlation coefficients among PM10, PM2.5 and PM1 at Gangneung were in the range of 0.916 to 0.998. Multiple statistical models were devised to predict each PM concentration, and the significant levels through multi-regression analyses were p < 0.001, showing all the coefficients to be significant. The observed and calculated PM concentrations were compared, and new linear regression models were sequentially suggested to reproduce the original observed PM values with improved correlation coefficients, to some extent.

Study of Crater in the Gobi Desert Induced by Ground Explosion of Large Amounts of TNT Explosive up to 10 Tons

Explosion craters on the ground surface induced by contact or near-field explosions have important implications, which can be used to assess blast consequences, guide the design of the explosion, or develop a protective strategy. In this study, to understand the crater characteristics induced by the contact explosion of large weight explosives, four field contact explosion tests were conducted on the surface of the Gobi Desert with large TNT charge weights of 1 ton, 3 tons, and 10 tons (test conducted twice). Cratering on the ground surface generated by large amounts of explosives was measured and evaluated, including the shape, depth, and diameter. A fine-mesh numerical model was developed and validated on the AUTODYN software platform, and a detailed parametric study was performed on the resulting craters. The effects of sand and gravel density, initiation method, shear modulus, and failure criteria were analyzed and discussed. An energy conversion coefficient was determined, and the corresponding theoretical equations were derived to predict the dimensions of the craters resulting from the large weight contact explosion. The calculated cratering characteristics were consistent with previous data and hence can be used in future engineering applications.

Application of the Fine-Grained Soil Prospecting Method in Typical Covered Terrains of Northern China

In recent years, mineral resources near the surface are becoming scarce, causing focused mineral exploration on concealed deposits in covered terrains. In northern China, covered terrains are widespread and conceal bedrock sequences and mineralization. These represent geochemical challenges for mineral exploration in China. As a deep-penetrating geochemical technology that can reflect the information of deep anomalies, the fine-grained soil prospecting method has achieved ideal test results in arid Gobi Desert covered terrain, semi-arid grassland covered terrain, and alluvium soil covered terrain of northern China. The anomaly range indicated by the fine-grained soil prospecting method is very good with the known ore body location. The corresponding relationship can effectively indicate deep ore bodies and delineate anomalies in unknown areas. Overall, the fine-grained soil prospecting method can be applied to geochemical prospecting and exploration in covered terrains.

Two mega sand and dust storm events over northern China in March 2021: transport processes, historical ranking and meteorological drivers

Although a remarkable reduction in the frequency of sand and dust storms (SDSs) in the past several decades has been reported over northern China (NC), two unexpected mega SDSs occurred on March 15–20, 2021 and March 27–29, 2021 (abbreviated as the “3.15” and “3.27” SDS events), which has reawakened widespread concern. This study characterizes the origins, transport processes, magnitudes of impact, and meteorological causes of these two SDS events using a long-term (2000–2021) dust optical depth (DOD) dataset retrieved from MODIS measurements and a comprehensive set of multiple satellite and ground-based observations combined with atmospheric reanalysis data. During the 3.15/3.27 event, the invasion of dust plumes greatly degraded the air quality over large areas of NC, reaching extremely hazardous levels, with the maximum daily mean PM10 concentration of 7058 µg m−3 (2670 µg m−3) recorded on March 15 (28). CALIOP observations show that during the 3.15 event the dust plume was lifted to an altitude of 4–8 km, and its range of impact extended from the dust source to the eastern coast of China. In contrast, the lifting height of the dust plume during the 3.27 event was lower than that during 3.15 event, which was also confirmed by ground-based Lidar observations. The MODIS-retrieved DOD data registered these two massive SDS events as the most intense episode in the same period in history over the past two decades. These two extreme SDS events were associated with both atmospheric circulation extremes and local meteorological anomalies that favored enhanced dust emissions in the Gobi Desert (GD) across southern Mongolia and NC. Meteorological analysis revealed that both SDS events were triggered by an exceptionally strong Mongolian cyclone generated at nearly the same location (along the central and eastern plateau of Inner Mongolia) in conjunction with a surface-level cold high-pressure system at the rear, albeit with differences in magnitude and spatial extent of impact. In the GD, the early melting of spring snow caused by near-surface temperature anomalies over dust source regions, together with negative soil moisture anomalies induced by decreased precipitation, formed drier and barer soil surfaces, which allowed for increased emissions of dust into the atmosphere by strongly enhanced surface winds generated by the Mongolian cyclone.

Aerodynamic Characteristics Over Fine-Grained Gravel Surfaces in a Wind Tunnel

Gravels can protect soil from wind erosion, however, there is little known about the effects of fine-grained gravel on aerodynamic characteristics of the near-surface airflow. Drag coefficient, wind-speed gradient, and turbulent transfer coefficient over different coverages of gravel surfaces were investigated in a compact boundary-layer wind tunnel. The drag coefficient of the fine-grained gravel surface reached the maximum value at 15% coverage and then tended to stabilize at gravel coverage 20% and greater. At a height of 4 cm, near-surface airflow on gravel surfaces can be divided clearly into upper and lower sublayers, defined as the inertial and roughness sublayers, respectively. The coefficient of variation of wind speed over gravel surfaces in the roughness sublayer was 8.6 times that in the inertial sublayer, indicating a greater effect of gravel coverage on wind-speed fluctuations in the lower layer. At a height of 4 cm, wind-speed fluctuations under the observed wind speeds were independent of changes in gravel coverage. In addition, an energy-exchange region, where sand particles can absorb more energy from the surrounding airflow, was found between the roughness and inertial sublayers, enhancing the erosional state of wind-blown sand. This finding can be applied to evaluate the aerodynamic stability of the gravel surface in the Gobi Desert and provide a theoretical basis for elucidation of the vertical distributions of wind-blown sand flux.