TianQin is a planned space-based gravitational wave (GW) observatory consisting of three Earth-orbiting satellites with an orbital radius of about $10^5 \, {\rm km}$. The satellites will form an equilateral triangle constellation the plane of which is nearly perpendicular to the ecliptic plane. TianQin aims to detect GWs between $10^{-4} \, {\rm Hz}$ and $1 \, {\rm Hz}$ that can be generated by a wide variety of important astrophysical and cosmological sources, including the inspiral of Galactic ultra-compact binaries, the inspiral of stellar-mass black hole binaries, extreme mass ratio inspirals, the merger of massive black hole binaries, and possibly the energetic processes in the very early universe and exotic sources such as cosmic strings. In order to start science operations around 2035, a roadmap called the 0123 plan is being used to bring the key technologies of TianQin to maturity, supported by the construction of a series of research facilities on the ground. Two major projects of the 0123 plan are being carried out. In this process, the team has created a new-generation $17 \, {\rm cm}$ single-body hollow corner-cube retro-reflector which was launched with the QueQiao satellite on 21 May 2018; a new laser-ranging station equipped with a $1.2 \, {\rm m}$ telescope has been constructed and the station has successfully ranged to all five retro-reflectors on the Moon; and the TianQin-1 experimental satellite was launched on 20 December 2019—the first-round result shows that the satellite has exceeded all of its mission requirements.

In three experiments, we manipulated procedural fairness (Experiment 1) and group-based anger and group efficacy (Experiments 2 and 3) to investigate the independent pathways of anger and efficacy for collective action in China. In Experiment 3 we also examined pathways to “soft” (low-cost) and “hard” (high-cost) collective action. Our results supported the dual-pathway model of collective action: group-based anger and perceived group efficacy independently predicted collective action intentions to protest against increased school fees and unhygienic cafeteria conditions for Chinese university students. Group-based anger predicted soft collective action intentions; both anger and efficacy predicted hard collective action intentions. Identification with the disadvantaged group was found to moderate the problem-focused coping pathway for hard collective action intentions. For high but not low identifiers, manipulated group efficacy predicted hard collective action intentions. We discuss our findings with specific reference to collective action research in China.

A good understanding of how meteorological conditions exacerbate or mitigate air pollution is critical for developing robust emission reduction policies. Thus, based on a multiple linear regression (MLR) model in this study, the quantified impacts of six meteorological variables on PM2.5 (i.e., particle matter with diameter of 2.5 µm or less) and its major components were estimated over the Yangtze River Basin (YRB). The 38-year (1980–2017) daily PM2.5 and meteorological data were derived from the newly-released Modern-Era Retrospective Analysis and Research and Application, version 2 (MERRA-2) products. The MERRA-2 PM2.5 was underestimated compared with ground measurements, partly due to the bias in the MERRA-2 Aerosol Optical Depth (AOD) assimilation. An over-increasing trend in each PM2.5 component occurred for the whole study period; however, this has been curbed since 2007. The MLR model suggested that meteorological variability could explain up to 67% of the PM2.5 changes. PM2.5 was robustly anti-correlated with surface wind speed, precipitation and boundary layer height (BLH), but was positively correlated with temperature throughout the YRB. The relationship of relative humidity (RH) and total cloud cover with PM2.5 showed regional dependencies, with negative correlation in the Yangtze River Delta (YRD) and positive correlation in the other areas. In particular, PM2.5 was most sensitive to surface wind speed, and the sensitivity was approximately −2.42 µg m−3 m−1 s. This study highlighted the impact of meteorological conditions on PM2.5 growth, although it was much smaller than the anthropogenic emissions impact.

A regional approach using Poisson wavelets is applied for gravity field recovery using the GOCE (Gravity Field and Steady‐State Ocean Circulation Explorer) gravity gradient tensor, heterogeneous gravimetry data, and altimetry measurements. The added value to the regional model introduced by GOCE data is validated and quantified. The performances of the solutions modeled with different diagonal components of GOCE data and their combinations are investigated. Numerical experiments in a region in Europe show that the effects introduced by GOCE data demonstrate long‐wavelength patterns on the centimeter scale in terms of quasi‐geoid heights, which may allow reducing the remaining long‐wavelength errors in ground‐based data, and improve the regional model. The accuracy of the gravimetric quasi‐geoid computed with a combination of three diagonal components is improved by 0.6 cm (0.5 cm) in the Netherlands (Belgium) compared to that derived from gravimetry and altimetry data alone, when GOCO05s is used as the reference model. Moreover, the added value from GOCE data reduces the mean values of the misfit between the gravimetric solution and GPS/leveling data. Performances of different components and their combinations are not identical, and the solution with vertical gradients is best when a single component is used. The incorporation of multiple components shows further improvements, and the combination of three components best fits the local GPS/leveling data. Further comparison shows that our solution is the highest quality and may be substituted for existing models for engineering purposes and geophysical investigations over the target area.

During temporal gravity field model determination, the kinematic empirical parameters are mainly designed to remove the strong bias, drift, and 1‐cycle per revolution variations in range‐rates. In practice, two different strategies are commonly used to process these empirical parameters. One is to determine the empirical parameters before solving spherical harmonic coefficients, called Pure Predetermined Strategy (PPS). The other is to simultaneously determine the empirical parameters and spherical harmonic coefficients, called Pure Simultaneous Strategy (PSS). In this study, apart from these two strategies, a novel processing strategy called Filter Predetermined Strategy (FPS) is also discussed. These different processing strategies may result in different solutions. With the Gravity Recovery and Climate Experiment Level 1B data spanning 2005 to 2010, the impacts of different kinematic empirical parameters processing strategies were assessed in detail. The numerical results indicate that (1) using three different processing strategies and their hybrids can determine the temporal gravity field model, while (2) the solutions via PPS present apparent temporal signal attenuation, which is approximately 15% lower in annual amplitude in Amazon River Basin, and 15% lower in yearly trend in Greenland, and (3) the signal‐to‐noise ratios of the solutions via PPS are generally smaller than those of the solutions via FPS and PSS, and (4) the performance of FPS is superior in terms of postfit range‐rates, but compatible with PSS in terms of other cross comparisons. According to comprehensive comparison results in terms of temporal signals and noise, the performance of our Huazhong University of Science and Technology models determined via FPS is in excellent accordance with other representative temporal gravity field models, such as CSR RL05, GFZ RL05a, and JPL RL05.

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Accurate terrestrial water storage (TWS) estimation is important to evaluate the situation of the water resources over the Yangtze River Basin (YRB). This study exploits the TWS observation from the new temporal gravity field model, HUST-Grace2016 (Huazhong University of Science and Technology), which is developed by a new low-frequency noise processing strategy. A novel GRACE (Gravity Recovery and Climate Experiment) post-processing approach is proposed to enhance the quality of the TWS estimate, and the improved TWS is used to characterize the drought and flood events over the YRB. The HUST-Grace2016-derived TWS presents good agreement with the CSR (Center for Space Research) mascon solution as well as the PCR-GLOBWB (PCRaster Global Water Balance) hydrological model. Particularly, our solution provides remarkable performance in identifying the extreme climate events e.g., flood and drought over the YRB and its sub-basins. The comparison between GRACE-derived TWS variations and the MODIS-derived (Moderate Resolution Imaging Spectroradiometer) inundated area variations is then conducted. The analysis demonstrates that the terrestrial reflectance data can provide an alternative way of cross-comparing and validating TWS information in Poyang Lake and Dongting Lake, with a correlation coefficient of 0.77 and 0.70, respectively. In contrast, the correlation is only 0.10 for Tai Lake, indicating the limitation of cross-comparison between MODIS and GRACE data. In addition, for the first time, the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) vertical velocity data is incorporated with GRACE TWS in the exploration of the climate-induced hydrological activities. The good agreement between non-seasonal NCEP/NCAR vertical velocities and non-seasonal GRACE TWSs is found in flood years

Based on tensor theory, three Invariants of the Gravitational Gradient Tensor (IGGT) are independent of the Gradiometer Reference Frame (GRF). Compared to traditional methods for calculation of gravity field models based on the Gravity field and steady-state Ocean Circulation Explorer (GOCE) data, which are affected by errors in the attitude indicator, using IGGT and least squares method avoids the problem of inaccurate rotation matrices. The IGGT approach as studied in this paper is a quadratic function of the gravity field model's spherical harmonic coefficients. The linearized observation equations for the least squares method is obtained using a Taylor expansion, and the weighting equation is derived using the law of error propagation. We also investigate the linearization errors using existing gravity field models and find that this error can be ignored since the used a-priori model EIGEN-5C is sufficiently accurate. One problem when using this approach is that it needs all six independent Gravitational Gradients (GGs), but the components V xy and V yz of GOCE are worse due to the non-sensitive axes of the GOCE gradiometer. Therefore we use synthetic GGs for both inaccurate gravitational gradient components derived from the a-priori gravity field model EIGEN-5C. Another problem is that the GOCE GGs are measured in a band-limited manner. Therefore, a forward and backward finite impulse response band-pass filter is applied to the data, which can also eliminate filter caused phase change. The Spherical Cap Regularization Approach (SCRA) and the Kaula rule are then applied to solve the polar gap problem caused by GOCE's inclination of 96.7 0. With the techniques described above, a degree/order 240 gravity field model called IGGT R1 is computed. Since the synthetic components of V xy and V yz are not band-pass filtered, the signals outside the measurement bandwidth are replaced by the a-priori model EIGEN-5C. Therefore this model is practically a combined gravity field model which contains GOCE GGs signals and long wavelength signals from the a-priori model EIGEN-5C. Finally, IGGT R1's accuracy is evaluated by comparison with other gravity field models in terms of difference degree amplitudes, the geostrophic velocity in the Agulhas current area, gravity anomaly differences as well as by comparison to GNSS/Leveling data.