Abstract
Satellite remote sensing data were used to extract concentrations and volume mixing ratios (VMR) of CO and O3 and Global Data Assimilation System (GDAS) data associated with Yutian MS7.3 earthquakes on March 21, 2008, and February 12, 2014. Difference value and anomaly index methods and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were used to simulate gas backward trajectories and analyze the relations between spatial and temporal variations in total columns of CO and O3 (TotCO and TotO3) and earthquakes. Then, the causes of abnormal changes were examined. Maximum anomalies in TotCO and TotO3 occurred one month before the 2008 earthquake and one month after the 2014 earthquake. Anomalies in TotCO and TotO3 were distributed along or were consistent with the fault zone. Furthermore, during the abnormal period, the coefficient of correlation between CO and O3 was 0.672 in 2008 and 0.638 in 2014, with both values significant at p < 0.05 . The correlation between TotCO and TotO3 was also significant. The abnormal phenomena of TotCO and TotO3 associated with the two earthquakes were attributed to underground gas escape, atmospheric chemical reactions, and atmospheric transportation caused by in situ stress in the generation of earthquakes.
Highlights
Understanding earthquake precursory anomalies is a worldwide concern [1]
Before and after two MS > 8:0 earthquakes in Sumatra in 2004 and 2005, abnormal changes were detected in CO and O3 concentrations, primarily caused by escape of underground gases during the earthquake and chemical reactions between underground and atmospheric gases [14]
The CO, CH4, and O3 concentration data and the volume mixing ratios (VMR) data were in National Aeronautics and Space Administration (NASA) standard disk storage format HDF-type
Summary
Understanding earthquake precursory anomalies is a worldwide concern [1]. At present, ground observations based on geophysics and crustal deformation are the typical focus of research [2]. It is difficult to obtain large-area dynamic and continuous information on seismic precursory anomalies because of limitations in ground observations, which restrict the ability to predict earthquakes [1]. With the development of satellite remote sensing technology, using abnormal changes in gas concentrations near epicenters to predict earthquakes has become a focus of research [4, 5]. The C–H–O–S system of the earth is rich and includes CO2, CH4, H2, CO, O3, water vapor, and other gases [6,7,8] These gases escape to the atmosphere from seismic fault and rupture zones before and after earthquakes and can change atmospheric composition and concentrations [9,10,11,12].
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