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Wind shear has important implications for Kelvin–Helmholtz instability (KHI) and gravity waves (GWs) in the mesosphere–lower thermosphere (MLT) region where its momentum transport process is dominated by short-period (<1 h) GWs. However, the sub-hourly variation in wind shear is still not well quantified. This study aims to improve current understanding of vertical wind shear by analyzing multi-year meteor radar measurements at the Mohe (MH, 53.5°N, 122.3°E), Beijing (BJ, 40.3 ° N , 116.2 ° E ), Wuhan (WH, 30.5 ° N , 114.6 ° E ), and Fuke (FK, 19.5°N, 109.1°E) stations in China. The wind field is estimated by a new algorithm, e.g., the damped least squares fitting. Taking the wind shear estimated by normal products as a criterion, the shear produced by the new algorithm has more statistical convergence as compared to the traditional algorithm, e.g., the least squares fitting. Therefore, we argue that the 10 min DLSA wind probably produces a more reasonable vertical shear. Both intensive wind shears and GW kinetic energy can be simultaneously captured during the 0600–1600 UTs of May at MH and during the 1300–2400 UTs of March at FK, possibly implying that the up-propagation of GWs could contribute to the production of large wind shears. The sub-hourly variation in wind shears is potentially valuable for understanding the interrelationship between shear (or KHI) and GWs. [ABSTRACT FROM AUTHOR]

The utilization of remote sensing soil moisture products in agricultural and hydrological studies is on the rise. Conducting a regional applicability analysis of these soil moisture products is essential as a preliminary step for their effective utilization. The triple collocation (TC) method enables the estimation of the standard deviation of errors in products when true soil moisture values are unavailable. It assesses data uncertainty and mitigates the influence of product errors on fusion, thereby enhancing product accuracy significantly. In this study, the TC uncertainty error analysis was employed to integrate Soil Moisture Active Passive (SMAP), the Advanced Microwave Scanning Radiometer 2 (AMSR-2), and the European Space Agency Climate Change Initiative (ESA CCI) active (ESA CCI A) and passive (ESA CCI P) products, with ground-based measurements serving as a reference. Traditional evaluation metrics, such as the correlation coefficient (R), bias, root mean square error (RMSE), and unin situed root mean square error (ubRMSE), were employed to evaluate the accuracy of the product. The findings indicate that SMAP and ESA CCI P products demonstrate strong spatiotemporal continuity within the research area and exhibit low uncertainty across various land types. The products derived from the Advanced Microwave Scanning Radiometer 2 (AMSR-2) exhibit a high level of temporal and spatial continuity; however, there is a requirement for enhancing their accuracy. The products of ESA CCI A exhibit notable spatiotemporal disjunction, contributing significantly to their elevated level of uncertainty. After fusion with TC analysis, the correlation coefficient (R = 0.7) of the TC-2 product derived from the fusion of SMAP, AMSR-2, and ESA CCI P products is significantly higher than the correlation coefficient of the TC-1 product (R = 0.65) obtained from the fusion of SMAP, AMSR-2, and ESA CCI A products at a 95% confidence level. The integration of data can efficiently mitigate the challenges associated with spatiotemporal gaps and inaccuracies in products, offering a dependable foundation for the subsequent utilization of remote sensing products. [ABSTRACT FROM AUTHOR]

Atmospheric gravity waves (GWs) in the mesosphere-lower thermosphere (MLT) are crucial for the understanding of general circulation. However, their dynamical characteristics are hardly retrieved due to the difficulty in the high-resolution observation of wind. Therefore, this paper uses eight years (2013–2020) of meteor radar measurements in the MLT region at Mohe station (53.5°N, 122.3°E), China, to retrieve high-temporal-resolution mesospheric wind data and further evaluate the temporal variation of GW kinetic energy. As the detected meteor trails exceed 6, the wind velocity is recalculated using the least square algorithm method, significantly increasing the temporal resolution of wind from 1 h up to 5 min. This resolution is sufficiently high for the investigation of GW kinetic energy, which exhibits a high spatial-temporal variability. For instance, it is enhanced in the winter season during the period of 0200–1400 UT and in the spring season during the period of 0800–1300 UT. The similarity between the climatological characteristics of GWs in MLT and the seasonal variation of GW total energy in the troposphere, determined from high-resolution radiosondes near to Mohe station, suggests that the meteorology in the lower atmosphere could be an important source of GWs in the MLT region. [ABSTRACT FROM AUTHOR]

In space gravitational-wave-detection missions, inertial sensors are used as the core loads, and their acceleration noise needs to reach 3 × 10 − 15   ms − 2 / Hz at a frequency of 0.1   mHz , which corresponds to the capacitive sensing system; the capacitive sensing noise on the sensitive axis needs to reach 1   aF / Hz . Unlike traditional circuit noise evaluation, the noise in the mHz frequency band is dominated by the thermal noise and the 1 / f noise of the device, which is a challenging technical goal. In this paper, a low-frequency, high-precision resonant capacitor bridge method based on a planar transformer is used. Compared with the traditional winding transformer, the developed planar transformer has the advantages of low temperature drift and low 1 / f noise. For closed-loop measurements of capacitive sensing circuits and sensitive structures, the minimum capacitive resolution in the time domain is about 3   aF , which is far lower than the scientific measurement resolution requirement of 5.8   fF for gravitational wave detection. The capacitive sensing noise is converted to 1.095   aF / Hz in the frequency band of 10   mHz – 1   Hz . Although there is a gap between the closed-loop measurement results and the final index, the measurement environment is an experimental condition without temperature control on the ground; additionally, in China, the measurement integrity and actual measurement results of the capacitive sensing function have reached a domestic leading level. This is the realization of China's future space gravitational wave exploration. [ABSTRACT FROM AUTHOR]

The ruling Chinese Communist Party (CCP) abolished its total ban on religious activities in 1982. However, the distrust that the CCP feels for religions remains obvious today, and the religious restrictions in contemporary China remain tight. Conventional wisdom tells us that the official atheist ideology of Marxism-Leninism is the main reason behind the CCP's distrust for, and restriction of, religion. However, taking a historical institutionalist perspective, this paper argues that the religious restrictions in contemporary China are in fact rooted in the fierce political struggles of the country's two major revolutions in the first half of the twentieth century. Without the support of religious groups, the Nationalist Republicans would have found it difficult to survive and succeed in overthrowing the Qing Dynasty during the Chinese Republican Revolution in the first decade of the twentieth century. Likewise, without cooperating with a wide range of religious groups, the CCP would have struggled to defeat the Nationalist regime and the Japanese invaders in the Chinese Communist Revolution between 1920s and 1940s. Thanks to the collaborations and struggles with various religious groups during the two revolutions which lead to its eventual ascent to power, the CCP thoroughly understands the organisational strength and mobilising capability embedded within religious groups. The tight restrictions on religious affairs in contemporary China is therefore likely to stem from the CCP's worry that prospective competitors could mobilise religious groups to challenge its rule through launching, supporting, or sponsoring collective actions. [ABSTRACT FROM AUTHOR]

The arid terrestrial ecosystem carbon cycle is one of the most important parts of the global carbon cycle, but it is vulnerable to external disturbances. As the most direct factor affecting the carbon cycle, how land cover change affects vegetation carbon sources/sinks in arid terrestrial ecosystems remains unclear. In this study, we chose the arid region of northwest China (ARNWC) as the study area and used net ecosystem productivity (NEP) as an indicator of vegetation carbon source/sink. Subsequently, we described the spatial distribution and temporal dynamics of vegetation carbon sources/sinks in the ARNWC from 2001–2018 by combining the Carnegie-Ames-Stanford Approach (CASA) and a soil microbial heterotrophic respiration (RH) model and assessed the effects of land cover change on them through modeling scenario design. We found that land cover change had an obvious positive impact on vegetation carbon sinks. Among them, the effect of land cover type conversion contributed to an increase in total NEP of approximately 1.77 Tg C (reaching 15.55% of the original value), and after simultaneously considering the effect of vegetation growth enhancement, it contributed to an increase in total NEP of approximately 14.75 Tg C (reaching 129.61% of the original value). For different land cover types, cropland consistently contributed the most to the increment of NEP, and the regeneration of young and middle-aged forests also led to a significant increase in forest carbon sinks. Thus, our findings provide a reference for assessing the effects of land cover change on vegetation carbon sinks, and they indicated that cropland expansion and anthropogenic management dominated the growth of vegetation carbon sequestration in the ARNWC, that afforestation also benefits the carbon sink capacity of terrestrial ecosystems, and that attention should be paid to restoring and protecting native vegetation in forestland and grassland regions in the future. [ABSTRACT FROM AUTHOR]

Studying the spatial representativeness of carbon flux measurement data for typical land cover types can provide important information for benchmarking Earth system models and validating multiple-scale remote sensing products. In our study, daily gross primary productivity (GPP) was firstly derived from eddy covariance observation systems and seasonal variations in field GPP were analyzed at nine flux tower sites for typical land cover types in the Heihe River Basin, China. Then, the real-time footprint distance and climate footprint distance of the field GPP were obtained by using a footprint source area model. Lastly, multiple-scale GPP products were validated at footprint scale, and the impacts (measurement height, surface roughness and turbulent state of the atmosphere) on the footprint distance of field GPP were analyzed. The results of this paper demonstrated that climate footprint distances ranged from about 500 m to 1500 m for different land cover types in the Heihe River Basin. The accuracy was higher when validating MODIS GPP products at footprint scale (R2 = 0.56, RMSE = 3.07 g C m−2 d−1) than at field scale (R2 = 0.51, RMSE = 3.34 g C m−2 d−1), and the same situation occurred in the validation of high-resolution downscaled GPP (R2 = 0.85, RMSE = 1.34 g C m−2 d−1 when validated at footprint scale; R2 = 0.82, RMSE = 1.47 g C m−2 d−1 when validated at field scale). The results of this study provide information about the footprints of field GPP for typical land cover types in arid and semi-arid areas in Northwestern China, and reveal that precision may be higher when validating multiple-scale remote sensing GPP products at the footprint scale than at the field scale. [ABSTRACT FROM AUTHOR]

An inertial sensor is a crucial payload in China's Taiji program for space gravitational wave detection. The performance of the capacitive displacement sensing circuit in the low-frequency band (0.1 mHz to 1 Hz) is extremely important because it directly determines the sensitivity of the space gravitational wave detection missions. Therefore, significant, yet challenging, tasks include decreasing the low-frequency noise in capacitive displacement sensing circuits and improving the capacitive sensing resolution. This study analyzes the noise characteristics of the pre-amplifier circuit within the capacitive sensing circuit, achieves precise tuning of the transformer bridge, and examines how transformer parameters affect noise. In addition, this study introduces a method using a discrete JFET to reduce the operational amplifier current noise and analyzes how feedback resistance and capacitance in TIA circuits affect the overall circuit noise. The proportional relationship between different transformer noises and TIA noise before and after optimization was analyzed and experimentally verified. Finally, an optimized TIA circuit and a superior transformer were utilized to achieve an increase in the capacitive sensing resolution from 1.095 aF/rtHz @ 10 mHz to 0.84 aF/rtHz @ 10 mHz, while improving the performance by 23%. These findings provide valuable insights into further decreasing circuit noise and increasing the capacitive sensing resolution. [ABSTRACT FROM AUTHOR]

Fine classification of vegetation types has always been the focus and difficulty in the application field of remote sensing. Unmanned Aerial Vehicle (UAV) sensors and platforms have become important data sources in various application fields due to their high spatial resolution and flexibility. Especially, UAV hyperspectral images can play a significant role in the fine classification of vegetation types. However, it is not clear how the ultrahigh resolution UAV hyperspectral images react in the fine classification of vegetation types in highly fragmented planting areas, and how the spatial resolution variation of UAV images will affect the classification accuracy. Based on UAV hyperspectral images obtained from a commercial hyperspectral imaging sensor (S185) onboard a UAV platform, this paper examines the impact of spatial resolution on the classification of vegetation types in highly fragmented planting areas in southern China by aggregating 0.025 m hyperspectral image to relatively coarse spatial resolutions (0.05, 0.1, 0.25, 0.5, 1, 2.5 m). The object-based image analysis (OBIA) method was used and the effects of several segmentation scale parameters and different number of features were discussed. Finally, the classification accuracies from 84.3% to 91.3% were obtained successfully for multi-scale images. The results show that with the decrease of spatial resolution, the classification accuracies show a stable and slight fluctuation and then gradually decrease since the 0.5 m spatial resolution. The best classification accuracy does not occur in the original image, but at an intermediate level of resolution. The study also proves that the appropriate feature parameters vary at different scales. With the decrease of spatial resolution, the importance of vegetation index features has increased, and that of textural features shows an opposite trend; the appropriate segmentation scale has gradually decreased, and the appropriate number of features is 30 to 40. Therefore, it is of vital importance to select appropriate feature parameters for images in different scales so as to ensure the accuracy of classification. [ABSTRACT FROM AUTHOR]

In recent years, the energy performance of public buildings has attracted substantial attention due to the significant energy-saving potential. As a semi-open high-space building, the high-speed railway station is obviously different from other public buildings and even traditional stations in terms of energy consumption and internal environment. This paper investigates the current energy consumption situation and environmental quality of 15 high-speed railway passenger stations in China. Results show that the energy consumption of the high-speed railway station is between 117–470 kWh/(m2·a). The energy consumption of the station is related to the area and the passenger flow. The energy use of the station using district heating is higher than that of the station without district heating in the same region. The higher glazing ratio induces good natural lighting in the station, but the uniformity of the lighting in the station is not good. The acceptable temperature range of passengers in winter is larger than that in summer. The average air change rate of the high-speed railway station is 3.2 h−1 in winter and 1.8 h−1 in summer, which is the main reason of high energy consumption of the HVAC (Heating Ventilation Air Conditioning) system in this kind of building. [ABSTRACT FROM AUTHOR]

Simple Summary: The history of oyster culture consists of a succession of developmental phases using different species, followed by collapses associated with infectious diseases. The Pacific oyster (Crassostrea gigas), native to the northwest Pacific Ocean, was characterized by wide adaptability, and translocated to support major aquaculture industries in many countries around the world. A deadly herpesvirus, Ostreid herpesvirus-1 (OsHV-1), has hit the superior oyster since 1991. OsHV-1 infection, combined with subsequent bacteraemia by opportunistic bacteria, has brought heavy losses to the main production regions of the Pacific oyster. Because of the considerable economic importance of Pacific oysters, there is a wealth of information available on diseases that affect them around the world. Little comprehensive information is available about the epidemiology status of major disease-causing agents in China. On the other hand, the scale and yields of Pacific oyster increased rapidly in recent years, as a result of the introduction and popularization of triploid oysters. In the present study, a comprehensive survey of potential pathogens associated with mortality events of Pacific oysters was carried out. Our results highlight the potential risks of OsHV-1, Vibrio natriegens, and Vibrio alginolyticus to the aquaculture industry of the Pacific oyster in China. The Pacific oyster (Crassostrea gigas) aquaculture industry increased rapidly in China with the introduction and promotion of triploid oysters in recent years. Mass mortalities affecting different life stages of Pacific oysters emerged periodically in several important production areas of Northern China. During 2020 and 2021, we conducted a passive two-year investigation of infectious pathogens linked to mass mortality. Ostreid herpesvirus-1 (OsHV-1) was detected to be associated with mass mortalities of hatchery larvae, but not juveniles and adults in the open sea. Protozoan parasites, such as Marteilia spp., Perkinsus spp. and Bonamia spp. were not detected. Bacterial isolation and identification revealed that Vibrio natriegens and Vibrio alginolyticus were the most frequently (9 out of 13) identified two dominant bacteria associated with mass mortalities. Pseudoalteromonas spp. was identified as the dominant bacteria in three mortality events that occurred during the cold season. Further bacteriological analysis was conducted on two representative isolates of V. natriegens and V. alginolyticus, designated as CgA1-1 and CgA1-2. Multisequence analysis (MLSA) showed that CgA1-1 and CgA1-2 were closely related to each other and nested within the Harveyi clade. Bacteriological investigation revealed faster growth, and more remarkable haemolytic activity and siderophore production capacity at 25 °C than at 15 °C for both CgA1-1 and CgA1-2. The accumulative mortalities of experimental immersion infections were also higher at 25 °C (90% and 63.33%) than at 15 °C (43.33% and 33.33%) using both CgA1-1 and CgA1-2, respectively. Similar clinical and pathological features were identified in samples collected during both naturally and experimentally occurring mortalities, such as thin visceral mass, discolouration, and connective tissue and digestive tube lesions. The results presented here highlight the potential risk of OsHV-1 to hatchery production of larvae, and the pathogenic role of V. natriegens and V. alginolyticus during mass mortalities of all life stages of Pacific oysters in Northern China. [ABSTRACT FROM AUTHOR]

Forest dynamics, including forest loss and gain, are long-term complex ecological processes affected by nature and human activities. It is particularly important to understand the long-term forest dynamics of protected areas to evaluate their conservation efforts. This study adopted the Landsat tree-canopy cover (TCC) method to derive annual TCC data for the period 1984–2020 for the protected areas of northeast China, where protection policies have been carried out since the end of the 20th century, e.g., the Natural Forest Conversion Program (NFCP). A strong correlation was found between the TCC estimates derived from Landsat and LiDAR observations, suggesting the high accuracy of TCC. Forest loss and gain events were also identified from the time series of TCC estimates. High correlations were reported for both forest loss (Producer's accuracy = 85.21%; User's accuracy = 84.26%) and gain (Producer's accuracy = 87.74%; User's accuracy = 88.31%), suggesting that the approach can be used for monitoring and evaluating the effectiveness of the NFCP and other forest conservation efforts. The results revealed a fluctuating upward trend of the TCC of the protected area from 1986 to 2018. The increased area of TCC was much larger than the decreased area, accounting for 59.68% and 40.34%, respectively, suggesting the effectiveness of protection policies. Since the NFCP was officially implemented in 1998, deforestation was effectively curbed, the area of forest loss was significantly reduced (slope: −14.24%/year), and the area of forest gain significantly increased (slope: 4.13%/year). We found that regional forest changes were mainly manifested in "forest gain after loss (forest recovery)" and "forest gain with no loss (forest newborn)", accounting for 40.29% and 37.28% of the total area of forest change, respectively. Moreover, the forest gain area far exceeds the forest loss area, reaching 11.24 million hectares, suggesting a successful forest recovery due to forest protection. [ABSTRACT FROM AUTHOR]

The 2011 Tohoku earthquake and the following enormous tsunami caused great disturbances in the ionosphere that were observed in various regions along the Pacific Ocean. In this study, the oblique-incidence ionosonde detection network located in North China was applied to investigate the inland ionospheric disturbances related to the 2011 tsunamigenic earthquake. The ionosonde network consists of five transmitters and 20 receivers and can monitor regional ionosphere disturbances continuously and effectively. Based on the recorded electron density variations along the horizontal plane, the planar middle-scale ionospheric disturbances (MSTIDs) associated with the 2011 Tohoku tsunamigenic earthquake were detected more than 2000 km west of the epicenter about six hours later. The MSTIDs captured by the Digisonde, high-frequency (HF) Doppler measurement, and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellite provided more information about the far-field inland propagation characteristics of the westward propagating gravity waves. The results imply that the ionosonde network has the potential for remote sensing of ionospheric disturbances induced by tsunamigenic earthquakes and provide a perspective for investigating the propagation process of associated gravity waves. [ABSTRACT FROM AUTHOR]

This paper proposes a combined approach comprising a set of methods for the high-precision mapping of soil moisture in a study area located in Jiangsu Province of China, based on the Chinese C-band synthetic aperture radar data of GF-3 and high spatial-resolution optical data of GF-1, in situ experimental datasets and background knowledge. The study was conducted in three stages: First, in the process of eliminating the effect of vegetation canopy, an empirical vegetation water content model and a water cloud model with localized parameters were developed to obtain the bare soil backscattering coefficient. Second, four commonly used models (advanced integral equation model (AIEM), look-up table (LUT) method, Oh model, and the Dubois model) were coupled to acquire nine soil moisture retrieval maps and algorithms. Finally, a simple and effective optimal solution method was proposed to select and combine the nine algorithms based on classification strategies devised using three types of background knowledge. A comprehensive evaluation was carried out on each soil moisture map in terms of the root-mean-square-error (RMSE), Pearson correlation coefficient (PCC), mean absolute error (MAE), and mean bias (bias). The results show that for the nine individual algorithms, the estimated model constructed using the AIEM (mv1) was significantly more accurate than those constructed using the other models (RMSE = 0.0321 cm³/cm³, MAE = 0.0260 cm³/cm³, and PCC = 0.9115), followed by the Oh model (m_v5) and LUT inversion method under HH polarization (mv2). Compared with the independent algorithms, the optimal solution methods have significant advantages; the soil moisture map obtained using the classification strategy based on the percentage content of clay was the most satisfactory (RMSE = 0.0271 cm³/cm³, MAE = 0.0225 cm³/cm³, and PCC = 0.9364). This combined method could not only effectively integrate the optical and radar satellite data but also couple a variety of commonly used inversion models, and at the same time, background knowledge was introduced into the optimal solution method. Thus, we provide a new method for the high-precision mapping of soil moisture in areas with a complex underlying surface. [ABSTRACT FROM AUTHOR]

Increasing emissions of ambient pollutants have caused considerable air pollution and negative health impact for human in various regions of China over the past decade. The resulting premature mortality and excessive morbidity caused huge human economic losses to the entire society. To identify the differences of health economic losses in various regions of China and help decision-making on targeting pollutants control, spatial assessment of health economic losses due to ambient pollutants in China is indispensable. In this study, to better represent the spatial variability, the satellite-based retrievals of the concentrations of various pollutants (PM10, PM2.5, O3, NO2, SO2 and CO) for the time period from 2007 to 2017 in China are used instead of using in-situ data. Population raster data were applied together with exposure-response function to calculate the spatial distribution of health impact and then the health impact is further quantified by using amended human capital (AHC) approach. The results which presented in a spatial resolution of 0.25° × 0.25°, show the signification contribution from the spatial assessment to revealing the spatial distribution and variance of health economic losses in various regions of China. Spatial assessment of overall health economic losses is different from conventional result due to more detail spatial information. This spatial assessment approach also provides an alternative method for losses measurement in other fields. [ABSTRACT FROM AUTHOR]