Search Results (10)

The Arxan Volcanic Field (AVF) is an active volcanic region in Northeast Asia, and its last eruption occurred approximately 2000 years ago. Its eruption mechanism remains unknown. To investigate the shallow magma system beneath the volcanic cones in the AVF, we deployed a dense seismic array consisting of 227 portable seismographs and conducted high-resolution ambient noise tomography (ANT). The results of checkerboard test (CRT) and restoring resolution test (RRT) demonstrate that our imaging results are reliable. These results reveale significant slow-velocity anomalies at depths of 5~9 km below the Tianchi caldera and GD1213 volcano in Arxan, with the highest anomaly reaching up to approximately 15%. These anomalies suggest partial melting in a shallow magma chamber, indicating ongoing volcanic activity in the AVF. The velocity of the magma chamber corresponding to a melt fraction of approximately 7.4~12.9%. Therefore, the presence of the magma chamber poses potential hazards to the Arxan region, including volcanic eruptions and their associated risks. Full article

The Changbai volcano, a globally recognized hotspot of volcanic activity, has garnered significant attention due to its persistent seismicity and ongoing magma activity. The volcano’s discontinuities and magma dynamics have raised concerns about the likelihood of future eruptions, which would likely result in substantial ecological, climatic, and economic impacts. Consequently, a comprehensive understanding of the Changbai volcanic system is essential for mitigating the risks associated with volcanic activity. In recent years, the P-wave coda autocorrelation method has gained popularity in lithosphere exploration as a reliable technique for detecting reflection coefficients. Additionally, the Common Reflection Point stacking approach has been employed to superimpose reflection signals in a spatial grid, enabling continuous observation of reflection coefficients in the study area. However, the accuracy of this approach is heavily reliant on better spatial data coverage. To better understand the internal dynamics of the Changbai volcano, we applied this approach to a densely packed short-period seismic array with an average station spacing of less than 1 km. Our results were constrained using waveform data of reflection coefficients and Moho dip angles. Our findings revealed a discontinuity in the Moho, which may indicate a conduit for mantle magma entering the crust. Furthermore, we identified two low-velocity anomalies within the crust, likely representing a magma chamber comprising molten and crystallized magma. Notably, our results also provided a clear definition of the lithosphere–asthenosphere boundary. Full article

Exploring the deformation mechanism of the 2021 Mw 7.4 Maduo Earthquake is crucial for better understanding the seismic hazard of the faults with low strain rates inside the Bayan Har block. This study leverages deformation information derived from Sentient-1 A/B images and GPS data to investigate in detail the co- and postseismic deformation mechanisms using multiple methods. The main results are as follows. First, the postseismic InSAR time series robustly identified the reactivation of the Changmahe fault, indicating the impact of the Maduo event on surrounding active faults. Second, the joint inversion of Interferometric Synthetic Aperture Radar and GPS revealed that (1) there was a complementary and partially overlapping relationship between the coseismic slip and postseismic afterslip of the main rupture; and (2) the Changmahe fault exhibited thrust compression dislocation in the early stage and experienced a sustained compressive effect from afterslip in the one year after the mainshock. Third, modeling the processes of viscoelastic relaxation and poroelastic rebound revealed that the postseismic deformation was probably caused by a combination of afterslip (near-field) and viscoelastic relaxation (near and far field). Fourth, the stress changes driven by the Maduo event revealed that the seismic gaps inside the Maqin-Maqu segment and the Kunlun Pass-Jiangcuo fault will be potential seismic risks in the future. Full article

Monitoring the surface deformation is of great significance, in order to explore the activity and geophysical features of the underground deep pressure source in the volcanic regions. In this study, the time series surface deformation of the Changbaishan volcano is retrieved via Sentinel-1B SAR data, using the SBAS-InSAR method. The main results are as follows. (1) The mean surface deformation velocity in the Changbaishan volcano is uplifted as a whole, while the uplift is locally distributed, which shows a strong correlation with faults. (2) The time series surface deformation of the Changbaishan volcano indicates an apparently seasonal change. (3) The cumulative surface deformation shows a strong correlation with the maximal magnitude and number of annual earthquakes, and it is likely dominated by the maximal magnitude of the annual earthquakes. (4) The single Mogi source model is appropriate to evaluate the deep pressure source in the Changbaishan volcano, constrained by the calculated surface deformation. The optimal estimated depth of the magma chamber is about 6.2 km, and the volume is increased by about 3.2 × 10⁶ m³. According to the time series surface deformation, it is concluded that the tectonic activity and faults, related to the deep pressure source, are pretty active in the Changbaishan volcano. Full article

The Julong high-altitude volcanic hot springs in northeast China are of undeniable interest for microbiological studies due to their unique, extreme environmental conditions. The objective of this study was to provide a comprehensive analysis of the unexplored fungal and bacterial community composition, structure and networks in sediments and water from the Julong hot springs using a combination of culture-based methods and metabarcoding. A total of 65 fungal and 21 bacterial strains were isolated. Fungal genera Trichoderma and Cladosporium were dominant in sediments, while the most abundant fungi in hot spring water were Aspergillus and Alternaria. Bacterial communities in sediments and water were dominated by the genera Chryseobacterium and Pseudomonas, respectively. Metabarcoding analysis revealed significant differences in the microorganism communities from the two hot springs. Results suggested a strong influence of pH on the analyzed microbial diversity, at least when the environmental conditions became clearly alkaline. Our analyses indicated that mutualistic interactions may play an essential role in shaping stable microbial networks in the studied hot springs. The much more complicated bacterial than fungal networks described in our study may suggest that the more flexible trophic strategies of bacteria are beneficial for their survival and fitness under extreme conditions. Full article

High-altitude volcanoes, typical examples of extreme environments, are considered of particular interest in biology as a possible source of novel and exclusive microorganisms. We analyzed the crater soil microbial diversity of Tianchi Volcano, northeast China, by combining molecular and morphological analyses of culturable microbes, and metabarcoding based on Illumina sequencing, in order to increase our understanding of high-altitude volcanic microbial community structure. One-hundred and seventeen fungal strains belonging to 51 species and 31 genera of Ascomycota, Basidiomycota and Mucoromycota were isolated. Penicillium, Trichoderma, Cladosporium, Didymella, Alternaria and Fusarium dominated the culturable fungal community. A considerable number of isolated microbes, including filamentous fungi, such as Aureobasidium pullulans and Epicoccum nigrum, yeasts (Leucosporidium creatinivorum), and bacteria (Chryseobacterium lactis and Rhodococcus spp.), typical of high-altitude, cold, and geothermal extreme environments, provided new insights in the ecological characterization of the investigated environment, and may represent a precious source for the isolation of new bioactive compounds. A total of 1254 fungal and 2988 bacterial operational taxonomic units were generated from metabarcoding. Data analyses suggested that the fungal community could be more sensitive to environmental and geographical change compared to the bacterial community, whose network was characterized by more complicated and closer associations. Full article

The aim of this project was to produce an earthquake–landslide debris flow disaster chain susceptibility map for the Changbai Mountain region, China, by applying data-driven model series and parallel model and Bayesian Networks model. The accuracy of these two models was then compared. Parameters related to the occurrence of landslide and debris flow disasters, including earthquake intensity, rainfall, elevation, slope, slope aspect, lithology, distance to rivers, distance to faults, land use, and the normalized difference vegetation index (NDVI), were chosen and applied in these two models. Disaster chain susceptibility zones created using the two models were then contrasted and verified using the occurrence of past disasters obtained from remote sensing interpretations and field investigations. Both disaster chain susceptibility maps showed that the high susceptibility zones are situated within a 10 km radius around the Tianchi volcano, whereas the northern and southwestern sections of the study area comprise primarily very low or low susceptibility zones. The two models produced similar and compatible results as indicated by the outcomes of basic linear correlation and cross-correlation analyses. The verification results of the ROC curves were found to be 0.7727 and 0.8062 for the series and parallel model and BN model, respectively. These results indicate that the two models can be used as a preliminary base for further research activities aimed at providing hazard management tools, forecasting services, and early warning systems. Full article

Severe natural disasters and related secondary disasters are a huge menace to society. Currently, it is difficult to identify risk formation mechanisms and quantitatively evaluate the risks associated with disaster chains; thus, there is a need to further develop relevant risk assessment methods. In this research, we propose an earthquake disaster chain risk evaluation method that couples Bayesian network and Newmark models that are based on natural hazard risk formation theory with the aim of identifying the influence of earthquake disaster chains. This new method effectively considers two risk elements: hazard and vulnerability, and hazard analysis, which includes chain probability analysis and hazard intensity analysis. The chain probability of adjacent disasters was obtained from the Bayesian network model, and the permanent displacement that was applied to represent the potential hazard intensity was calculated by the Newmark model. To validate the method, the Changbai Mountain volcano earthquake–collapse–landslide disaster chain was selected as a case study. The risk assessment results showed that the high-and medium-risk zones were predominantly located within a 10 km radius of Tianchi, and that other regions within the study area were mainly associated with very low-to low-risk values. The verified results of the reported method showed that the area of the receiver operating characteristic (ROC) curve was 0.817, which indicates that the method is very effective for earthquake disaster chain risk recognition and assessment. Full article

Tianchi volcano is a dormant active volcano with a risk of re-eruption. Volcanic soil and volcanic ash samples were collected around the volcano and the concentrations of 21 metals (major and trace elements) were determined. The spatial distribution of the metals was obtained by inverse distance weight (IDW) interpolation. The metals’ sources were identified and their pollution levels were assessed to determine their potential ecological and human health risks. The metal concentrations were higher around Tianchi and at the north to the west of the study area. According to the geo-accumulation index (I_geo), enrichment factor (EF) and contamination factor (CF) calculations, Zn pollution was high in the study area. Pearson’s correlation analysis and principal component analysis showed that with the exception of Fe, Mn and As, the metals that were investigated (Al, K, Ca, Na, Mg, Ti, Cu, Pb, Zn, Cr, Ni, Ba, Ga, Li, Co, Cd, Sn, Sr) were mostly naturally derived. A small proportion of Li, Pb and Zn may have come from vehicle traffic. There is no potential ecological risk and non-carcinogenic risk because of the low concentrations of the metals; however, it is necessary to pay attention to the carcinogenic risk of Cr and As in children. Full article

The impacts of earthquakes and secondary disasters on ecosystems and the environment are attracting increasing global attention. Development of uncertainty reasoning models offers a chance to research these complex correlations. The primary aim of this research was to construct a disaster chain hazard assessment model that combines a Bayesian Network model and the ArcGIS program software for Changbai Mountain, China, an active volcano with a spate of reported earthquakes, collapses, and landslide events. Furthermore, the probability obtained by the Bayesian Networks was used to determine the disaster chain probability and hazard intensity of the earthquake events, while ArcGIS was used to produce the disaster chain hazard map. The performance of the Bayesian Network model was measured by error rate and scoring rules. The confirmation of the outcomes of the disaster chain hazard assessment model shows that the model demonstrated good predictive performance on the basis of the area under the curve, which was 0.7929. From visual inspection of the produced earthquake disaster chain hazard map, highly hazardous zones are located within a 15 km radius from the Tianchi center, while the northern and the western parts of the studied area are characterized mainly by “very low” to “low” hazard values. Full article