Fluids Triggered the 2021 Mw 6.1 Yangbi Earthquake at an Unmapped Fault: Implications for the Tectonics at the Northern End of the Red River Fault

On 21 May 2021 a magnitude Mw 6.1 earthquake occurred in Yangbi region, Yunan, China, which was widely felt and caused heavy casualties. Imaging of the source region was conducted using our improved double-difference tomography method on the huge data set recorded by 107 temporary stations of ChinArray-I and 62 permanent stations. Pronounced structural heterogeneities across the rupture source region are discovered and locations of the hypocenters of the Yangbi earthquake sequence are significantly improved as the output of the inversion. The relocated Yangbi earthquake sequence is distributed at an unmapped fault that is almost parallel and adjacent (∼15 km distance) to the Tongdian–Weishan fault (TWF) at the northern end of the Red River fault zone. Our high-resolution 3D velocity models show significant high-velocity and low-VP/VS ratios in the upper crust of the rupture zone, suggesting the existence of an asperity for the event. More importantly, low-VS and high-VP/VS anomalies below 10 km depth are imaged underlying the source region, indicating the existence of fluids and potential melts at those depths. Upward migration of the fluids and potential melts into the rupture zone could have weakened the locked asperity and triggered the occurrence of the Yangbi earthquake. The triggering effect by upflow fluids could explain why the Yangbi earthquake did not occur at the adjacent TWF where a high-stress accumulation was expected. We speculate that the fluids and potential melts in the mid-to-lower crust might have originated either from crustal channel flow from the southeast Tibet or from local upwelling related to subduction of the Indian slab to the west.

Margin Trading Program, External Profit Pressure and Enterprise Financialization—A Quasi-Natural Experiment Based on Double Difference Model

Based on the urgent need of the real economy to “get away from fictitious to substantial”, this paper constructs a quasi-natural experiment based on the margin trading program gradually implemented in China in 2010 and studies the influence of the margin trading program on the financialization level of the target company by using the difference-in-difference method. The results show that, because of the dominant role of financing transactions in margin trading programs in China’s capital market, financing transactions drive up the share prices of listed companies, which leads to an excessive easing of the financing constraints of listed companies and short-sighted behavior of executives, which has a significant role in promoting enterprise financialization. Moreover, the driving effect is more significant in state-owned enterprises, enterprises with a high degree of financing constraint, and enterprises with a low degree of marketization. Economic policy uncertainty will restrain the positive effect of margin trading programs on enterprise financialization through information and governance mechanisms. In contrast, the “branding” effect caused by the financial connection of senior executives will intensify the positive relationship between margin trading programs on enterprise financialization levels. When considering the intermediary effect, we find that the margin trading program will result in the optimistic deviation of analysts’ earnings forecasts and cause the external profit pressure of enterprises, thus increasing the financialization trend. This study is of great theoretical significance and practical value for evaluating the policy effect of the margin trading program, improving this policy, investigating the influencing factors of enterprise financialization, and promoting the real economy to move from fictitious to substantial.

The Impact of Green Credit on the Green Innovation Level of Heavy-Polluting Enterprises—Evidence from China

This article uses the “Green Credit Guidelines” promulgated in 2012 as an example to construct a quasi-natural experiment and uses the double difference method to test the impact of the implementation of the “Green Credit Guidelines” on the green innovation activities of heavy-polluting enterprises. The study found that, in comparison to non-heavy polluting enterprises, the implementation of green credit policies inhibited the green innovation of all heavy-polluting enterprises. In the analysis of heterogeneity, this restraint effect did not differ significantly due to the nature of property rights and the company’s size. The mechanism test showed that green credit policy limits the efficiency of business investment and increases the cost of financing business debt. Eliminating corporate credit financing, particularly long-term borrowing, negatively impacts the green innovation behavior of listed companies.

Using VIIRS nightlights to estimate the impact of the 2015 Nepal earthquakes

We use Visible Infrared Imaging Radiometer Suite (VIIRS) nightlight data to model the impact of the 2015 Nepal earthquakes. More specifically, the data—showing nightlight emissions—are used to examine the extent to which there is a difference in nightlight intensity between cells damaged in the earthquake versus undamaged cells based on (1) mean comparisons; and (2) fixed effect regression models akin to the double difference method. The analysis is carried out for the entire country as well as smaller regions in and around the Central area and Kathmandu, which were the hardest hit areas. Overall, the regressions find a significant and negative effect from the initial shock, followed by a positive net effect from aid and relief efforts, which is consistent with what one would expect to find. However, the mean analysis results are inconclusive and there is substantial noise in the nightlight measurements due to how the values are produced and persistent cloud cover over Nepal.

The Dynamic Value of China’s High-Tech Zones: Direct and Indirect Influence on Urban Ecological Innovation

China’s High-tech Industrial Development Zones (HTZ) are industrial agglomeration areas established by the local government to foster economic innovation. As springboards for cities to implement innovation-driven development strategies, HTZs have significant spillover and driving effects on urban ecological innovation. Based on panel data taken from 215 cities between 2003 and 2016, this paper empirically analyzes the impact of HTZ construction and its mechanisms as they pertain to urban ecological innovation. This analysis is framed by the double difference model and the intermediary effect model. It found that HTZ construction can effectively enhance urban ecological innovation, and formidably promote ecological innovation in central and eastern cities, as well as cities with superior scientific and educational resources. The intermediary mechanism analysis revealed that HTZs result in a policy depression effect, which may promote the agglomeration of urban innovation factors (including high-quality talents and investment), thereby bolstering urban ecological innovation. Moreover, HTZs’ investment agglomeration effect is primarily responsible for driving urban ecological innovation. Indeed, the HTZ construction may not only promote the local ecological innovation, but also have a significant spillover effect on the ecological innovation activities of other cities in the province.

Q estimation based on the logarithmic spectral area double difference

The Q factor is an essential parameter describing the characteristics of medium absorption within a material during wave propagation. When a seismic wave propagates within the attenuating media, its amplitude decreases and frequency band narrows, resulting in a variation in its logarithmic spectral area. Based on these effects, we calculate the logarithmic spectral area difference (LSAD) before and after attenuation and set a division point to divide the LSAD into two parts. We then compute the difference between the two LSADs to derive a new Q-estimation formula based on computation of the logarithmic spectral area double difference (LSADD). To improve the noise robustness of the Q estimation, we select multiple different division points to calculate the Q factors and consider their average value as our final estimate. We then compare and analyze the noise robustness and bandwidth sensitivity of our technique with other commonly used methods. These results demonstrate that our approach is the most accurate and robust, and least sensitive to the frequency band when processing noisy synthetic seismograms. Finally, we apply our methodology to field vertical seismic profile (VSP) and seismic reflection data, further illustrating the effectiveness of this method to estimate the Q factor.

Differencing strategies for SLR observations at the Wettzell observatory

The precise estimation of geodetic parameters using single- and double-differenced SLR observations is investigated. While the differencing of observables is a standard approach for the GNSS processing, double differences of simultaneous SLR observations are practically impossible to obtain due to the SLR basic principle of observing one satellite at a time. Despite this, the availability of co-located SLR telescopes and the use of the alternative concept of quasi-simultaneity allow the forming of SLR differences under certain assumptions, thus enabling the use of these processing strategies. These differences are in principle almost free of both, satellite- and station-specific error sources, and are shown to be a valuable tool to obtain relative coordinates and range biases, and to validate local ties. Tested with the two co-located SLR telescopes at the Geodetic Observatory Wettzell (Germany) using SLR observations to GLONASS and LAGEOS, the developed differencing approach shows that it is possible to obtain single- and double-difference residuals at the millimetre level, and that it is possible to estimate parameters, such as range biases at the stations and the local baseline vector with a precision at the millimetre level and an accuracy comparable to traditional terrestrial survey methods. The presented SLR differences constitute a valuable alternative for the monitoring of the local baselines and the estimation of geodetic parameters.

Improvement of Multi-GNSS Precision and Success Rate Using Realistic Stochastic Model of Observations

With the advancement of multi-constellation and multi-frequency global navigation satellite systems (GNSSs), more observations are available for high precision positioning applications. Although there is a lot of progress in the GNSS world, achieving realistic precision of the solution (neither too optimistic nor too pessimistic) is still an open problem. Weighting among different GNSS systems requires a realistic stochastic model for all observations to achieve the best linear unbiased estimation (BLUE) of unknown parameters in multi-GNSS data processing mode. In addition, the correct integer ambiguity resolution (IAR) becomes crucial in shortening the Time-To-Fix (TTF) in RTK, especially in challenging environmental conditions. In general, it is required to estimate various variances for observation types, consider the correlation between different observables, and compensate for the satellite elevation dependence of the observable precision. Quality control of GNSS signals, such as GPS, GLONASS, Galileo, and BeiDou can be performed by processing a zero or short baseline double difference pseudorange and carrier phase observations using the least-squares variance component estimation (LS-VCE). The efficacy of this method is investigated using real multi-GNSS data sets collected by the Trimble NETR9, SEPT POLARX5, and LEICA GR30 receivers. The results show that the standard deviation of observations depends on the system and the observable type in which a particular receiver could have the best performance. We also note that the estimated variances and correlations among different observations are also dependent on the receiver type. It is because the approaches utilized for the recovery techniques differ from one type of receiver to another kind. The reliability of IAR will improve if a realistic stochastic model is applied in single or multi-GNSS data processing. According to the results, for the data sets considered, a realistic stochastic model can increase the computed empirical success rate to 100% in multi-GNSS as well as a single system. As mentioned previously, the realistic precision of the solution can be achieved with a realistic stochastic model. However, using the estimated stochastic model, in fact, leads to better precision and accuracy for the estimated baseline components, up to 39% in multi-GNSS.

Earthquake Relocation Studies near Local Scale Sources using Double-Difference Technique

Determination of the location of the hypocenter is very necessary to monitor the potential for seismic hazard. Positioning and seismic energy can help safety workers determine which areas can be mined or temporarily halted. Earthquakes in underground mines are caused by seismic induction due to mining activities such as blasting processes, hydrofracturing, vehicle activities, etc. Earthquakes that occur are generally clustering. Earthquake events generally occur in mine openings, this is caused by mass compensation taken. The data used in this study are synthetic micro-earthquake data around the mining area. To obtain a high level of accuracy and precision, especially in determining the location and depth in determining the hypocenter using the Double-Difference (DD) method. The results of the microseismic relocation in the study area are well covered, as evidenced by the residual histogram and shift distribution. The shift of the microseismic before and after being relocated spread in all directions with the dominant direction in the NE – SW direction. The value of the microseismic shift before and after being relocated ranged from 0.5 meters to 150 meters.