Remote Sensing of Atmospheric CO and O3 Anomalies before and after Two Yutian MS7.3 Earthquakes

Liang, Haodong; Xin, Cunlin; Liu, Haibo; Di, Guoyun; Liu, Songxin; Zhang, Liang

doi:https://doi.org/10.1155/2021/1747705

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Abstract Introduction Data and Methods Results Discussion Conclusions Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2021 | Article ID 1747705 | https://doi.org/10.1155/2021/1747705

Remote Sensing of Atmospheric CO and O₃ Anomalies before and after Two Yutian M_S7.3 Earthquakes

Haodong Liang,¹Cunlin Xin,¹Haibo Liu,¹Guoyun Di,¹Songxin Liu,¹and Liang Zhang¹

Academic Editor: Orlando Vaselli

Received02 May 2021

Revised04 Aug 2021

Accepted14 Aug 2021

Published01 Sept 2021

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 M_S7.3 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 . 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.

1. Introduction

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]. However, 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]. Satellite hyperspectral technology has the advantages of wide coverage and short observation period and is not affected by the underlying surface [2]. The technology can identify different gases, invert their concentration distributions, and predict earthquakes [3]. 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]. However, the mechanisms for the abnormal changes remain unclear because of a lack of research. The C–H–O–S system of the earth is rich and includes CO₂, CH₄, H₂, CO, O₃, water vapor, and other gases [6–8]. These gases escape to the atmosphere from seismic fault and rupture zones before and after earthquakes and thus can change atmospheric composition and concentrations [9–12]. After the Gujarat M_S7.7 (2001) and M_S5.2 (2006) earthquakes, high-altitude O₃-rich air was transported to the epicenter area by the atmosphere, which increased its O₃ concentration [13]. Similarly, before and after two 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]. Before and after the Wenchuan M_S8.0 earthquake in 2008 and the Lushan M_S7.0 earthquake in 2013, there were abnormal spatiotemporal changes in CH₄ and CO, and Cui et al. [15] proposed that they were caused by the two major earthquakes and the accompanying fault tectonic activities. Similarly, Singh et al. [16] suggest that abnormal change in CO concentration before the Gujarat M_S7.7 earthquake in India in 2010 was precursor information on the earthquake. Thus, satellite hyperspectral remote sensing data can be used in seismic monitoring.

The Yutian 2008 M_S7.3 earthquake (35.6°N, 81.6°E) occurred in Yutian, Xinjiang, China, at 0633 on March 21, 2008, with a focal depth of 19 km. The earthquake rupture was primarily extensional and strike-slip, and the epicenter was the intersection of the Kangxiwa fault zone and the southwest end of the Arerjin fault zone in the West Kunlun Mountains. The main seismogenic fault structure is the Arerjin fault [17]. Before this earthquake, there were two (excluding aftershocks) earthquakes within 500 km of the 2008 Yutian earthquake epicenter. One was a 6.1 earthquake in Rutog County, Tibet, on May 5, 2007 (140 km from the 2008 Yutian earthquake epicenter), and the other was a 6.9 earthquake in Gêrzê County, Tibet, on January 9, 2008 (480 km from the 2008 Yutian earthquake epicenter). Since then, the extension of the fault zone in the region has increased. On August 12, 2012, another M_S6.2 earthquake occurred 90 km from the 2008 Yutian earthquake, resulting in long-term crustal instability and accumulation of strain energy in the region. As a consequence, a M_S7.3 earthquake (36.1°N, 82.5°E) occurred at 1719 on February 12, 2014, in Yutian, Xinjiang. The focal depth of the 2014 Yutian earthquake was 12 km, and the mechanism was a strike-slip type. The tail of the large strike-slip Arerjin fault zone, which is an extension zone in the southwest section of the fault zone, was the epicenter. Atmospheric infrared sounder (AIRS) data were obtained, and the difference and anomaly index methods were used to analyze temporal and spatial variations in O₃ and CO gases before and after two earthquakes. The relations and the differences between the two earthquakes were also examined. Figure 1 shows the faults and seismic history of the research area.

2. Data and Methods

2.1. Data

Column concentration data of CO, O₃, and CH₄ (TotCO, TotO₃, and TotCH₄) and volume mixing ratio data of CO and O₃ (VMR) were all derived from the 8-day data, monthly average standard product deorbit data, and daily data of the AIRS level 3 of the National Aeronautics and Space Administration (NASA). The data were downloaded from NASA’s Goddard Earth Sciences Data and Information Services Center (http://disc.sci.gsfc.nasa.gov/). The 2008 Yutian earthquake epicenter area was 35.6°N, and the average value of a gas was that in a space at 81.6°E. The 2014 Yutian earthquake epicenter area was 36.1°N, and the average value of a gas was that in a space at 82.5°E. For spatial distributions, gas concentrations were determined from 33°N to 39°N and 79°E to 85°E. Because AIRX3STD data (AIRS+AMSU) were used in this paper, sensor data were only available to 2016. Therefore, data from 2003 to 2015 were used. The AIRS is a hyperspectral sensor mounted on the Aqua satellite launched by NASA on May 4, 2002. The satellite can cover 85% of the earth twice a day. The AIRS has 2,378 continuous infrared spectral channels, which can provide hyperspectral resolution data in the wavelength range from 3.7 to 15.4 μm with a spatial resolution of . The spectral resolution was nominal. It can monitor the physical parameters pressure, temperature, and humidity and the chemicals CH₄, CO, and O₃ [18, 19]. The meteorological data used for backward trajectory were from atmospheric assimilation products and model reanalysis data of the National Centers for Environmental Prediction (NCEP) in the US and were obtained through the GDAS, which assimilates a variety of conventional data and satellite observation data. The data set included air temperature, humidity, near-surface wind speed, and near-surface pressure, with a time resolution of 3 h and a spatial resolution of . The data were downloaded from the official website of the NCEP of the National Meteorological Administration (https://www.noaa.gov/ [20]).

2.2. Methods

Data were extracted by MATLAB, and the abnormal index method and the difference method were used to subtract the average value of the gas background field in nonseismic years and eliminate the influence of seasonal changes. The HYSPLIT model was used to examine transport and diffusion trajectories of O₃. (1)Extraction of CO, CH₄, and O₃ data. The CO, CH₄, and O₃ concentration data and the VMR data were in NASA standard disk storage format HDF-type (hierarchical data format). MATLAB (2021a) software was used to extract the data, and ArcGIS (10.5) software was used for interpolation processing.(2)Abnormal index method. This method is similar to the definition of thermal anomaly [21, 22], and the (equation (2)) is the ratio of the difference (equation (3)) to the standard deviation () (equation (1)) [15]. The anomaly index is used to assess the reliability of anomalies. When the , the anomaly reliability reaches 95.44%.(3)Difference method. This method directly reflects the absolute variation in a gas by using the abnormal difference value and highlighting the abnormal degree by which a gas concentration value deviates from the background value. The anomaly difference is the difference between the current gas concentration () and the background gas concentration () at one point. The monthly background value was the average value of each month corresponding to the nonearthquake years from 2003 to 2015 and was obtained using equation (4). [15]

In the formulas, , , and are the longitude, latitude, and month, respectively; is the gas column concentration value at the current point (longitude , latitude ) in month ; and is, for the time in years (, 2003 to 2015), the arithmetic mean value of the gas column concentration at the same point (longitude , latitude ) in month . The value is the standard deviation at the point (longitude , latitude ) in month . (4)HYSPLIT model

The HYSPLIT model is a professional model used to calculate and analyze transport and diffusion trajectory of atmospheric pollutants [23]. The model has two primary forms: backward transport and forward diffusion. Of the two, backward simulation is another form of simulating the flow direction of the target area and has been primarily used to explain the gas source in a target area [23, 24]. In this paper, HYSPLIT backward trajectory was used to simulate the transmission path of O₃ on the day of an earthquake and the maximum concentration day, as well as the O₃ contribution rate to the air mass.

3. Results

Characteristics of TotCO and TotO₃ anomalies associated with the two M_S7.3 earthquakes in Yutian in 2008 and 2014 obtained by difference value and anomaly index methods are shown in Table 1.

3.1. Spatial Anomaly Features

The difference method indicated the anomaly of TotCO before the 2008 Yutian earthquake that occurred primarily in the northwest direction of the epicenter, appearing along the NWW (west-northwest) trending the Tekrick fault (Figure 2(a)). The results obtained by the anomaly index method were similar to those obtained by the difference method, and the maximum anomaly index was (Figure 2(b)). The results indicated that it might be associated with the 2008 Yutian earthquake. Figure 3(a) shows that TotO₃ anomalies before the 2008 Yutian earthquake were primarily distributed in a double ring, with the line between the extreme value centers of the two abnormal rings stretching in an EW direction. The distribution of abnormal bands shown in Figure 3(b) was consistent with that in Figure 3(a), and the maximum anomaly index was approximately .

(a) Spatial distribution of CO anomalies obtained by the difference method

(b) Spatial distribution of CO anomalies obtained by the anomaly index method

(a) Spatial distribution of O3 anomalies obtained by the difference method

(b) Spatial distribution of O3 anomalies obtained by the anomaly index method

Figure 4(a) shows that the TotCO anomaly was linearly distributed in the NE (northeast) direction along the Arerjin fault-Xiaoerkule-Ashe Cooley fault after the 2014 Yutian earthquake. The CO anomaly distribution in Figure 4(b) was generally consistent with that in Figure 4(a), with a maximum anomaly index of approximately . However, the TotCO anomaly shown in Figure 4(b) was slightly weaker than that in Figure 4(a). Figure 5(a) shows that the anomalous concentration of TotO₃ after the 2014 Yutian earthquake was linear along the Ashkule-Guozhacuo fault zone. Similar results are shown in Figure 5(b), with an anomaly index of approximately . Theoretically, the anomaly centers of TotCO and TotO₃ should be near the epicentral fault zone and overlap each other. However, this expectation was not supported by the results, possibly because of the topographic conditions and the gas distribution height in Yutian County. Yutian County is ox leg-shaped, with the terrain higher in the south and lower in the north, with a height difference of approximately 3,500 m. The Kashtash and Kunlun mountains are in the south of Yutian County, and the Taklimakan Desert and the Tarim Basin are in the north. The CO was concentrated primarily near the surface. A downdraft prevails in the basin, and a pressure difference develops between the basin and the alpine region, forming a local atmospheric circulation that moves the CO release point northward to form an abnormal center. O₃ was concentrated primarily at high altitudes, where wind speeds are high and gas flow is fast. Affected by northerly wind, O₃ moves southward from the original release point to form an abnormal center [26]. Therefore, the TotCO and TotO₃ anomaly centers shifted and did not coincide with one another.

(a) Spatial distribution map of CO anomalies obtained by the difference method

(b) Spatial distribution map of CO anomalies obtained by the anomaly index method

(a) Spatial distribution map of CO anomalies obtained by the difference method

(b) Spatial distribution map of CO anomalies obtained by the anomaly index method

3.2. Temporal Anomaly Characteristics

The maximum anomalies of TotCO and TotO₃ occurred one month before the 2008 Yutian earthquake (Figures 2 and 3). A small-amplitude CO concentration anomaly occurred in December 2007 (Figure 2), which might be associated with the 6.9-magnitude earthquake in Gêrzê County, Tibet, on January 9, 2008 (480 km from the epicenter of the 2008 Yutian earthquake) [27]. Then, the maximum TotCO anomaly appeared in February and gradually recovered to a 5normal level of variation from March. The timing of anomalous change in TotO₃ (Figure 3) was generally consistent with that of TotCO. As shown in Figure 6(a), TotCO increased sharply from February 8, reached its maximum on February 10, and then decreased gradually. The TotCO also increased from February 28 to March 13, but the change in amplitude was small, consistent with periodic changes. After that increase, the TotCO returned to the level of periodic change. The TotO₃ began to increase from February 8, breaking the cycle of gradual change, but then decreased sharply on February 11 (Figure 6(a)). Then, TotO₃ began to increase sharply on February 23 and reached a maximum on February 27. After the maximum, TotO₃ decreased and returned to a cycle of gradual change. The VMR values of CO and O₃ at 700 hPa from 2003 to February 2015 were extracted and analyzed, and the values increased sharply at the beginning of February 2008, around February 4 (Figure 7(a)). Maximum values were reached on February 22, 2008. By contrast, in other nonseismic years, the VMR values of CO and O₃ did not change significantly. These results indicated that the abnormal changes in TotCO and TotO₃ in February 2008 were not seasonal. Thus, the cause of those changes was most likely associated with the earthquake.

(a) Changes in gas concentrations from January to April 2008

(b) Changes in gas concentrations from January to April 2014

(a) Gas VMR values from February 2003 to February 2015

(b) Gas VMR values from March 2003 to March 2015

The CO VMR values at 400 to 700 hPa increased significantly from January 5 to February 22 (Figure 8(a)). The CO VMR values increased rapidly above 600 hPa and reached a maximum value on February 22. Then, the values began to decline and returned to normal levels of annual change in April. The CO VMR values at 100 to 300 hPa also increased, but the changes were not obvious because of the height. The O₃ VMR values at 300 hPa, 100 hPa, and 150 hPa increased on December 28, 2007 (Figure 9(a)). The O₃ VMR value at 300 hPa reached a maximum on March 15, whereas at 100 hPa and 150 hPa, maximum values were reached on January 15. Among the pressure layers, the changes in O₃ VMR values were most obvious at 100 hPa and 300 hPa, which may be related to the main distribution height of O₃ in the atmosphere. The changes in TotCO and TotO₃ and VMR values were consistent whether they were obtained by the difference method or the abnormal index method.

(a) 2008 Yutian earthquake

(b) 2014 Yutian earthquake

(a) 2008 Yutian earthquake

(b) 2014 Yutian earthquake

The TotCO changed slightly in November 2013 (Figure 4), and the TotO₃ changed abnormally in December 2013 (Figure 5), which may be associated with the M_S5.6 earthquake (36.8°N, 86.7°E) that occurred on November 24, 2013. Afterward, TotCO and TotO₃ increased gradually, and the maximum anomalies appeared in March 2014. As shown in Figure 6(b), TotO₃ increased sharply on March 1, 2014, and reached a maximum on March 5. From March 5 to 11, TotO₃ was higher than that in other months. There were two minimum values of TotCO on March 6 and March 20, which might have been caused by the northward drift of CO from the epicenter. This result indicated that the abnormal change in TotCO might be associated with the 2014 Yutian earthquake. As shown in Figure 7(b), the VMR value of CO began to increase sharply in early March 2014, peaked around March 20, 2014, and then declined and gradually returned to normal at the end of March. The O₃ VMR also began to increase sharply in early March 2014 and reached a maximum on March 10, 2014. Then, the values began to decline and gradually returned to normal at the end of March. There were no abnormal changes in CO and O₃ VMR values in March in nonseismic years. Thus, the abnormal changes in CO and O₃ VMR values in March 2014 were not related to seasonal changes and therefore were likely associated with the 2014 Yutian earthquake. As shown in Figure 8(b), the 850 hPa CO VMR value increased sharply after February 14th, reached a maximum value on March 10–18, and then began to decline. The 400 to 700 hPa CO VMR values also showed upward trends, but the magnitude of increase was small. Maximum values were reached around March 10, which then returned to normal levels in May. These results demonstrated that changes in the 400 to 850 hPa CO VMR values were because of contributions from near the ground. As shown in Figure 9(b), the O₃ VMR values at 300 hPa, 100 hPa, and 150 hPa gradually increased after November 18, 2013. The O₃ VMR values at 300 hPa began to increase on March 1 and reached a maximum before and after March 25. The O₃ VMR values at 100 hPa and 150 hPa reached a maximum around March 1, indicating that the increase in O₃ VMR values did not necessarily come from the near surface but might have come from atmospheric chemical reactions and atmospheric transport [28].

4. Discussion

4.1. Relations between TotCO and TotO₃ Anomalies and Earthquakes

The TotCO was abnormal three months before the 2008 Yutian earthquake and reached the maximum abnormality in February before that earthquake. The maximum abnormal value of TotCO occurred on February 10, and the degree of abnormality exceeded the background value of molecules/cm² (Figure 2(a)). Then, TotCO decreased abnormally and gradually returned to the level of periodic changes. During the abnormal period, the abnormal fluctuation range of TotCO was large at first and then small from the beginning of February 2008. In the month of the 2008 Yutian earthquake, TotCO also fluctuated, but the range of fluctuation was smaller than that in February (Figure 6(a)), which might be related to changes in underground gas emissions caused by changes in ground stress during earthquake buildup. In addition, TotCO showed a slight abnormality three months before the 2014 Yutian earthquake and then returned to normal, which might be associated with an M_S5.6 earthquake (36.8°N, 86.7°E) that occurred on November 24, 2013. In March 2014, TotCO reached the maximum abnormality, and the maximum abnormal value exceeded the background value of molecules/cm² during the same period, after which the abnormal degree of TotCO decreased. This result might be related to the release of ground stress during the earthquake in this area, which caused the fault zone near the epicenter to close before the earthquake and then open afterward. As shown in Figure 6(b), there were two extremely low TotCO values on March 6 and March 20. The low values might be because the gas in the epicenter area was evacuated to the northern area far from the epicenter under the influence of atmospheric circulation. This phenomenon was consistent with the results in Figure 4, which further illustrated that abnormal changes in TotCO might be associated with the 2014 Yutian earthquake.

The TotO₃ was abnormal one month before the earthquake on March 21, 2008. The maximum abnormal value of TotO₃ occurred on February 27, exceeding the background value of 22.67 DU during the same period. Then, the variation in values returned to normal (Figure 3(a)). In addition, TotO₃ began to appear abnormal two months before the earthquake on February 12, 2014, and reached the maximum abnormality in March 2014. The maximum abnormal value of TotO₃ occurred on March 5, exceeding the background value of 33 DU during the same period (Figure 5(a)), and then, the degree of abnormality decreased. The abnormal values of TotO₃ appeared later than those of TotCO, and their duration was longer than that of CO. The spatial correspondence of the two was relatively good, but their intensities were not consistent. The differences might be related to the multiple causes of O₃ abnormalities. In addition to underground gas escape and atmospheric chemical reactions, atmospheric transportation might also affect TotO₃ abnormalities. Moreover, the spatial distributions of the anomaly centers of TotO₃ and TotCO in 2014 did not correspond well (Figures 4 and 5) which might be related to the topography and gas distribution height in Yutian County.

In the past two decades, the strong earthquakes on the Qinghai-Tibet Plateau have generally been distributed on the periphery of the Bayan Har Block [29]. The 2008 Yutian earthquake occurred on the western boundary of the Bayan Har Block. Wan et al. [29] studied the regional structure of the fault zone around the 2008 Yutian earthquake. They found that under the NNE thrust of the Indian Plate against the Eurasian Plate, the Qaidam Basin in the northern margin of the Qinghai-Tibet Plateau moved eastward along the Arerjin fault, whereas the Xingdukush block moved NW along the Karakorum fault as a whole. The epicenter area was between the two blocks, resulting in slow, large-scale strain accumulation in the crust of the epicenter area. The EW-trending tension of the fault zone before the earthquake occurred under the bilateral dynamic interaction, and when the structure was unlocked, the in situ stress was released. The authors speculated that underground gas was released in large quantities, resulting in anomalies. After the earthquake, the structure was locked, and the anomaly gradually decreased. Afterward, the coseismic stress disturbance of the 2008 Yutian earthquake [27] triggered subsequent aftershocks and the M_S6.2 earthquake (90 km from the 2008 Yutian earthquake epicenter) that occurred on August 12, 2012. As a result, stress increased on the Kunlun fault in the northern segment of the Gonggacuo fault zone [29], such that the southwestern end of the Arerjin fault expanded along the NW tensile structural belt [30], which accelerated the 2014 Yutian earthquake. Because of the tectonic stress caused by the 2008 Yutian earthquake and its triggered aftershocks, the Xiaoerkule fault and the Ashe Cooley fault were locked before the earthquake. Therefore, the gas upward flow pores were closed, resulting in a decrease in normal overflow gas in the short term before and after the earthquake and a continuous decline in gas concentration. After the earthquake, the stress in this area was released. The tectonic stress of the Arerjin fault resulted in the SN-trending rupture of the Xiaoerkule Basin, which accelerated the sinistral dislocation of the Arerjin fault and formed a series of NE or NNE-trending plume fault systems, including the Ashe Cooley fault and the Guozhacuo fault. The underground gas channels were generally open, and gases were released, resulting in obvious anomalies in March after the earthquake [31].

4.2. Causes of Abnormal TotCO and TotO₃

According to previous studies [2, 14, 31], there are currently two primary explanations for the abnormal changes in TotCO and TotO₃ in the epicentral area. One explanation is the escape of underground gas along the fault zone, and the other is that the gas dissipating into the atmosphere reacts with original atmospheric gases. However, the contributions of these processes might not be large enough to produce an abrupt increase in total ozone in such a short period [13]. In addition, according to Ganguly [28], atmospheric transportation is also a cause of abnormal changes in TotO₃. The causes of abnormal TotCO and TotO₃ associated with the two Yutian earthquakes are discussed from these three aspects below.

First, the spatial (Figures 2–5) and temporal (Figures 6, 8, and 9) variations in TotCO and TotO₃ anomalies were most likely caused by geological processes in the lithosphere or crustal stress that resulted in the two Yutian M_S7.3 earthquakes in 2008 and 2014. Many gases remain deep in the earth’s crust, including CO₂, CO, CH₄, H₂, N₂, H₂O, and H₂S [1]. These gases are stored in the earth’s crust at higher than atmospheric pressure, and they tend to migrate upward and penetrate into shallow rock cracks and pores and escape to the atmosphere [15]. During an earthquake, the increase in ground stress causes many cracks, pores, and fissures to form in the fracture zone near the epicenter, and large amounts of carbon-containing gases (e.g., CH₄ and CO) escape into the atmosphere through these channels, causing abnormal changes in gas concentrations in the epicenter area [2]. In this study, the spatial distributions of TotCO and TotO₃ corresponded well with the fault zone. However, an earthquake is a complex process, and other factors such as topography, weather, and human activities in the epicenter area can also cause abnormal changes in gas concentrations. In this study, calculations were used during the processing of data to eliminate the influences of other factors, and therefore, underground gas emissions might be the largest cause of abnormal changes in TotCO and TotO₃ in the epicenter area.

Second, underground gases escape into the atmosphere and chemically react with atmospheric gases. Gas increments affect atmospheric concentrations in an epicenter area, resulting in abnormal changes in TotCO and TotO₃. Following escape from underground, CH4 forms the transition products CO and O₃ during oxidation, according to the reaction , which increases TotCO and TotO₃ [32, 33]. Because of the high background content of atmospheric CH₄, the increase in CH₄ from underground gas emissions is limited. Nevertheless, the oxidation of CH₄ contributes to CO and O₃ abnormalities [34–36]. O₃ is distributed primarily in the troposphere, and atmospheric photochemical reactions in the troposphere can also cause abnormal O₃ concentrations, according to the reaction . As shown in Table 2, the coefficients of correlation between CO and O₃ were 0.672 and 0.638 in 2008 and 2014, respectively, with both correlations significant at . The correlations between TotCO and TotO₃ were relatively weak in 2007, 2009, 2013, and 2015 but were significant in 2008 and 2014, indicating a good correlation between CO and O₃ during an earthquake. Sun et al. [14] studied the changes in TotCO and TotO₃ before and after two major earthquakes in Sumatra in 2004 and 2005. They found no correlation between TotCO and TotO₃ in 2004 to 2005 (), but the correlation was significant during earthquake activity (December 2004 to March 2005) () [14], which is consistent with the results of this study. As shown in Figure 6, the change in TotO₃ lagged behind that in TotCO, indicating that the earthquakes caused CO to be oxidized to O₃. The coefficients of correlation between CH₄ and CO in 2008 and 2014 were −0.731 and −0.370, respectively, with correlations significant at and 0.01, respectively. The coefficients of correlation between CH₄ and O₃ in 2008 and 2014 were −0.660 and −0.558, respectively, with both correlations significant at , indicating that part of TotCO and TotO₃ was also derived from CH₄ oxidation. In addition, during an earthquake, low-frequency electromagnetic radiation and ionospheric disturbances promote 14N decay to form CO [37, 38], accelerating the production of CO according to the reactions . These reactions are another reason for abnormal changes in TotCO.

Third, atmospheric transmission might also be a cause of abnormal gas concentrations in epicentral areas. The 5-day backward trajectories on the day of the 2008 Yutian earthquake (Figure 10(a)) showed that in the air masses from the NWW direction in the 100 hPa pressure layer, the O₃ contribution rate was the largest at 28.57%. In the remaining air masses, the contribution was relatively small. The 5-day backward trajectories of the maximum O₃ concentration day (Figure 10(b)) showed that the O₃ contribution rate in the air mass from the NWW direction increased to 34.43%. Although the O₃ contribution rate in the other air masses also increased, the magnitude of increase was small. The 5-day backward trajectories on the day of the 2014 Yutian earthquake (Figure 11(a)) showed that among the air masses from the SWW direction, the two air masses closest to the south had the largest contributions of O₃, reaching 20.68% and 20.78%. The 5-day backward trajectories of the day with the maximum O₃ concentration (Figure 11(b)) showed that in the air mass from the SWW direction, the maximum contribution rate of O₃ increased to 40.26%. For the source of the air mass, these results were consistent with those obtained by the difference and abnormal index methods, indicating that atmospheric transportation was also a cause of abnormal changes in TotO₃. Ganguly [28] studied the increase in TotO₃ after the Gujarat M_S7.7 and M_S5.2 earthquakes in 2001 and 2006, respectively, and found that the increase in TotO₃ after the earthquake was due to atmospheric transmission between the upper troposphere and lower stratosphere. The upper O₃-rich air was transported to the epicenter. The results of this study were similar.

(a) Five-day backward trajectories on the day of the earthquake (March 21)

(b) Five-day backward trajectories of the day of maximum gas concentration (February 27)

(a) Five-day backward trajectories on the day of the earthquake (February 12)

(b) Five-day backward trajectories of the day of maximum gas concentration (March 10)

5. Conclusions

(1)AIRS hyperspectral remote sensing data were analyzed, and TotCO and TotO₃ changed abnormally before and after two M_S7.3 earthquakes in the study area. Abnormal gas concentrations associated with the 2008 Yutian earthquake occurred in February before the earthquake, and those associated with the 2014 Yutian earthquake occurred in March after the earthquake. Before and after the two earthquakes, the anomalies of TotCO and TotO₃ were distributed along the fault zone or the anomaly trend was consistent with the fault zone trend.(2)The release of ground stress during earthquake buildup and occurrence causes the release of underground gases into the atmosphere along the rupture zone, which might be a cause of the abnormal changes in TotCO and TotO₃. The CO and O₃ released into the atmosphere chemically react with CH₄ and other original atmospheric gases, which may be another cause of the abnormal changes in TotCO and TotO₃. In addition, atmospheric transportation might also contribute to abnormal changes in TotO₃.(3)The abnormal changes in TotCO and TotO₃ before and after earthquakes may be anomalies that can predict impending earthquakes. The CO and O₃ anomaly indexes of the two Yutian M_S7.3 earthquakes obtained by the anomaly index method were 2.0 and 2.2 and 2.0 and 2.2, respectively, and the anomaly reliability exceeded 94%. Thus, satellite hyperspectral remote sensing data can be used to extract reliable seismic-related information from geochemical anomalies.

Data Availability

The data are available at http://disc.sci.gsfc.nasa.gov/https://www.noaa.gov/.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

The authors are grateful for the financial support from the National Natural Science Foundation of China (Grant No. 41262001).

References

Y. Chen, R. S. Xu, R. Cai, J. Wang, and L. Miao, “Application progress of remote sensing technology in earthquake research,” Progress in Geophysics, vol. 23, no. 4, pp. 273–1281, 2008.
View at: Google Scholar
Y. J. Cui, J. Li, Y. Y. Wang, Y. M. Liu, Z. Chen, and J. G. Du, “Application of gas remote sensing technique to earthquake monitoring,” Advances in Earth Science, vol. 30, no. 2, pp. 284–294, 2015.
View at: Google Scholar
Y. J. Cui, J. G. Du, D. H. Zhang, and Y. T. Sun, “Application of remote gas geochemistry in earthquake prediction,” Advances in Earth Science, vol. 27, pp. 1173–1177, 2012.
View at: Google Scholar
Y. Li, J. G. Du, F. K. Wang, X. C. Zhou, X. D. Pan, and R. Q. Wei, “Geochemical characteristics of soil gas in the Yanhuai basin, northern China,” Earthquake Science, vol. 22, no. 1, pp. 93–100, 2009.
View at: Google Scholar
X. C. Zhou, J. G. Du, Z. Cheng, Y. J. Cui, and L. Liu, “Advance review of seismic geochemistry,” Bulletin of Mineralogy Petrology and Geochemistry, vol. 31, no. 4, pp. 340–346, 2012.
View at: Google Scholar
J. D. Pasteris, “Fluid inclusion in mantle xenoliths,” in Mantle Xenoliths, pp. 691–707, Wiley, New York, 1987.
View at: Google Scholar
J. D. Bergman, “Lamproites and other potassium-rich igneous rocks: a review of their occurrence, mineralogy and geochemistry,” in Alkaline Igneous Rocks, J. G. Fitton and B. G. J. Upton, Eds., pp. 103–190, Blackwell Scientific Publication, London, 1987.
View at: Google Scholar
S. Matveev, C. Ballhaus, K. Fricke, J. Truckenbrodt, and D. Ziegenben, “Volatiles in the Earth's mantle: I. Synthesis of CHO fluids at 1273 K and 2.4 GPa,” Geochimica et Cosmochimica Acta, vol. 61, no. 15, pp. 3081–3088, 1997.
View at: Publisher Site | Google Scholar
C. Y. King, “Gas geochemistry applied to earthquake prediction: an overview,” Journal of Geophysical Research: Solid Earth, vol. 91, no. B12, pp. 12269–12281, 1986.
View at: Publisher Site | Google Scholar
C. M. Wang and X. H. Li, “Applications of fracture-gas measurement to the earthquake studies in China,” Earthquake Research in China, vol. 2, pp. 38–53, 1994.
View at: Google Scholar
J. G. Du, X. Y. Si, Y. X. Chen, H. Fu, C. L. Jian, and W. S. Guo, “Geochemical anomalies connected with great earthquakes in China,” in Geochemistry Research Advances, pp. 57–92, Nova Science Publishers, New York, 2008.
View at: Google Scholar
X. C. Zhou, J. du, Z. Chen et al., “Geochemistry of soil gas in the seismic fault zone produced by the Wenchuan M_S 8.0 earthquake, southwestern China,” Geochemical Transactions, vol. 11, no. 1, pp. 1–10, 2010.
View at: Publisher Site | Google Scholar
N. D. Ganguly, “Variation in atmospheric ozone concentration following strong earthquakes,” International Journal of Remote Sensing, vol. 30, no. 2, pp. 349–356, 2009.
View at: Publisher Site | Google Scholar
Y. T. Sun, Y. J. Cui, Y. M. Liu et al., “Anomalies remote sensing geochemistry of CO and O3 and ground-based validation before and after two Sumatra M>8.0 earthquakes,” Journal of Seismological Research, vol. 37, no. 2, pp. 222–227, 2014.
View at: Google Scholar
Y. J. Cui, D. Ouzounov, N. Hatzopoulos, K. Sun, Z. Y. Zou, and J. du, “Satellite observation of CH₄ and CO anomalies associated with the Wenchuan M_S 8.0 and Lushan M_S 7.0 earthquakes in China,” Chemical Geology, vol. 469, pp. 185–191, 2017.
View at: Publisher Site | Google Scholar
R. P. Singh, J. Senthil Kumar, J. Zlotnicki, and M. Kafatos, “Satellite detection of carbon monoxide emission prior to the Gujarat earthquake of 26 January 2001,” Applied Geochemistry, vol. 25, no. 4, pp. 580–585, 2010.
View at: Publisher Site | Google Scholar
Z. H. Li, H. S. Ma, and Y. J. Qu, “Study on seismogenic structure and seismic activity characteristics before the Yutian Ms 7.3 earthquake on March 21, 2008, Xinjiang,” Earthquake Research in China, vol. 25, no. 2, pp. 199–205, 2009.
View at: Google Scholar
H. H. Aumann, M. T. Chahine, C. Gautier et al., “AIRS/AMSU/HSB on the aqua mission: design, science objectives, data products, and processing systems,” IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 2, pp. 253–264, 2003.
View at: Publisher Site | Google Scholar
B. J. Tian, M. Evan, and F. Eric, AIRS/AMSU/HSB Version 6 Level 3 Product User Guide, Jet Propulsion Laboratory and California Institute of Technology, Pasadena, CA, 2014.
G. Rolph, A. Stein, and B. Stunder, “Real-time environmental applications and display system: READY,” Environmental Modelling & Software, vol. 95, pp. 210–228, 2017.
View at: Publisher Site | Google Scholar
V. Tramutoli, G. D. Bello, N. Pergola, and S. Piscitelli, “Robust satellite techniques for remote sensing of seismically active areas,” Annals of Geophysics, vol. 44, no. 2, pp. 295–312, 2009.
View at: Publisher Site | Google Scholar
D. Ouzounov, D. Liu, K. Chunli, G. Cervone, M. Kafatos, and P. Taylor, “Outgoing long wave radiation variability from IR satellite data prior to major earthquakes,” Tectonophysics, vol. 431, no. 1-4, pp. 211–220, 2007.
View at: Publisher Site | Google Scholar
S. J. Nan, M. S. Liang, and J. H. Shi, “Analysis on heavy pollution weather in Taiyuan based on HYSPLIT backward trajectory mode,” Shanxi Science and Technology, vol. 33, no. 6, pp. 131–133, 2018.
View at: Google Scholar
Z. J. Zhao, Y. J. Wei, X. Z. Zhang, W. Qin, and H. F. Xie, “The correlation analysis of Nanjing haze days and meteorological factors,” China Environmental Science, vol. 35, no. 12, pp. 3570–3580, 2015.
View at: Google Scholar
G. H. Yin, J. X. Jiang, and G. D. Wu, “Tectonic background of the Ms 7.4 earthquake at Yutian on March 21, 2008,” Arid Land Geography, vol. 31, no. 4, pp. 543–549, 2008.
View at: Google Scholar
H. B. Liu, Y. J. Cui, and C. L. Xin, “Detecting anomalies of atmospheric total column CO and O₃ related to the 2014 Yutian Ms 7.3 earthquake,” Earthquake, vol. 40, no. 1, pp. 99–111, 2020.
View at: Google Scholar
X. Z. Chen, C. S. Jiang, and Y. E. Li, “The March 21, 2008 Yutian, Xinjiang Ms7.3 earthquake,” Recent Developments in World Seismology, vol. 4, pp. 20–30, 2008.
View at: Google Scholar
N. D. Ganguly, “The impact of transported ozone-rich air on the atmospheric ozone content following the 26 January 2001 and 7 March 2006 Gujarat earthquakes,” Remote Sensing Letters, vol. 2, no. 3, pp. 195–202, 2011.
View at: Publisher Site | Google Scholar
Y. G. Wan, Z. K. Shen, and S. Z. Sheng, “The mechanical effects of the 2008 Ms7.3 Yutian, Xinjiang earthquake on the neighboring faults and its tectonic origin of normal faulting mechanism,” Chinese Journal of Geophysics, vol. 53, no. 2, pp. 280–289, 2010.
View at: Google Scholar
J. J. Ren, X. W. Xu, S. M. Zhang, Y. Luo, O. B. Liang, and J. X. Zhao, “Tectonic transformation at the eastern termination of the Eastern Kunlun fault zone and seismogenic mechanism of the 8 August 2017 Jiuzhaigou M_S7.0 earthquake,” Chinese Journal of Geophysics, vol. 60, no. 10, pp. 4027–4045, 2017.
View at: Google Scholar
H. B. Liu, Y. J. Cui, and C. L. Xin, “Characteristics of CO changes before and after the Yutian Ms7.3 earthquake in Xinjiang based on AIRS data,” Bulletin of Mineralogy Petrology and Geochemistry, vol. 39, no. 2, pp. 327–335, 2020.
View at: Google Scholar
G. Martinelli and P. Plescia, “Carbon dioxide and methane emissions from calcareous-marly rock under stress: experimental tests results,” Annals of Geophysics, vol. 48, no. 1, pp. 167–173, 2009.
View at: Publisher Site | Google Scholar
Q. Y. Yang, Y. Zhang, L. Y. Fu et al., “Coupling mechanism of stress variation and groundwater (water level, water temperature, hydrochemistry, soil gas, etc.) and its application in earthquake precursors research in Sichuan and Yunnan regions,” Progress in Geophysics, vol. 35, no. 6, pp. 2124–2133, 2020.
View at: Google Scholar
B. Weinstock and H. Niki, “Carbon monoxide balance in nature,” Science, vol. 176, no. 4032, pp. 290–292, 1972.
View at: Publisher Site | Google Scholar
J. Fishman, S. Solomon, and P. J. Crutzen, “Observational and theoretical evidence in support of a significant in-situ photochemical source of tropospheric ozone,” Tellus, vol. 31, no. 5, pp. 432–446, 1979.
View at: Publisher Site | Google Scholar
J. Fishman and W. Seiler, “Correlative nature of ozone and carbon monoxide in the troposphere: implications for the tropospheric ozone budget,” Journal of Geophysical Research Oceans, vol. 88, no. C6, pp. 3662–3670, 1983.
View at: Publisher Site | Google Scholar
J. H. Ding, X. H. Shen, W. Y. Pan, J. Zhang, and H. P. Guan, “Seismo-electromagnetism precursor research progress,” Chinese Journal of Radio Science, vol. 21, no. 5, pp. 791–801, 2006.
View at: Google Scholar
X. M. Zhang, J. Liu, J. D. Qian, X. H. Shen, and S. F. Zhao, “Ionospheric electromagnetic disturbance before Gaize earthquake with Ms 6.9, Tibet,” Earth, vol. 28, no. 3, pp. 14–22, 2008.
View at: Google Scholar

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