Seismicity patterns before the 2021 Fin (Iran) doublet earthquakes using the region-time-length and time-to-failure methods

Knowledge regarding earthquake hazards and seismicity is crucial for crisis management, and the occurrence of foreshocks, seismic activity patterns, and spatiotemporal variations in seismic activity have been studied. Furthermore, the estimation of the region-time-length (RTL) parameter has been proposed to detect seismic quiescence before the occurrence of a large earthquake. In addition, the time-to-failure method has been used to estimate the time occurrence of large earthquakes. Hence, in this study, to gain deeper insight into seismic activity in the southern Zagros region, we utilized the RTL algorithm to identify the quiescence and activation phases leading to the Fin doublet earthquakes. Temporal variations in the RTL parameter showed two significant anomalies. One corresponded to the occurrence time of the first earthquake (2017-12-12);the other anomaly was associated with the occurrence time of the second event (2021-11-14). Based on a negative value of the RTL parameter observed in the vicinity of the Fin epicenters (2021), seismic quiescence (a decrease in seismicity compared to the preceding background rate) was identified. The spatial distribution of the RTL prognostic parameters confirms the appearance of seismic quiescence surrounding the epicenter of the Fin doublet earthquakes (2021). The time-to-failure method was designed using precursory events that describe the acceleration of the seismic energy release before the mainshock. Using the time-to-failure method for the earthquake catalog, it was possible to estimate both the magnitude and time of failure of the Fin doublet. Hence, the time-tofailure technique can be a useful supplementary method to the RTL algorithm for determining the characteristics of impending earthquakes.

Variation of XCO_(2) anomaly patterns in the Middle East from OCO-2 satellite data

The anthropogenic CO_(2) emission is contributed to the rapid increase in CO_(2) concentration.In the current study the anthropogenic CO_(2) emission in the Middle East(ME)is investigated using 6 years columnaveraged CO_(2) dry air mole fraction(XCO_(2))observation from Orbiting Carbon Observatory-2(OCO-2)satellite.In this way,the XCO_(2) anomaly(DXCO_(2))as the detrended and deseasonalized term of OCO-2XCO_(2) product,was computed and compared to provide the direct spacebased anthropogenic CO_(2) emission monitoring.As a result,the high positive and negative DXCO_(2) values have corresponded to the major sources such as oil and gas industries,and growing seasons over ME,respectively.Consequently,the Open-source Data Inventory for Anthropogenic CO_(2)(ODIAC)emission and the gross primary productivity(GPP)were utilized in exploring the DXCO_(2) relation with human and natural driving factors.The results showed the capability of DXCO_(2) maps in detecting CO_(2) emission fluctuations in defined periods were detectible in daily to annual periods.The simplicity and accuracy of the method in detecting the man-made and natural driving factors including the main industrial areas,megacities,or local changes due to COVID-19 pandemic or geopolitical situations as well as the vegetation absorption and biomass burning is the key point that provides the environmental managers and policymakers with valuable and accessible information to control and ultimately reduce the CO_(2) emission over critical regions.