Shale gas is a relatively clean-burning fossil fuel, produced by hydraulic fracturing. This technology may be harmful to the environment; therefore, environmentally friendly methods to extract shale gas have attracted considerable attention from researchers. Unlike previous studies, this study is a comprehensive investigation that uses systematic analyses and detailed field data. The environmental challenges associated with shale gas extraction, as well as measures to mitigate environmental impacts from the source to end point are detailed, using data and experience from China’s shale gas production sites. Environmental concerns are among the biggest challenges in practice, mainly including seasonal water shortages, requisition of primary farmland, leakage of drilling fluid and infiltration of flowback fluid, oil-based drill cuttings getting buried underground, and induced seismicity. China’s shale gas companies have attempted to improve methods, as well as invent new materials and devices to implement cleaner processes for the sake of protecting the environment. Through more than 10-year summary, China’s clean production model for shale gas focuses on source pollution prevention, process control, and end treatment, which yield significant results in terms of resource as well as environmental protection, and can have practical implications for shale gas production in other countries, that can be duplicated elsewhere.

Evaluation of the river ecological environment can provide a basis for river management and ecological restoration. To conduct a comprehensive health assessment of the rivers in Tianjin, their biological, physical, and chemical indicators are investigated on the basis of 32 river monitoring sites from August to September 2018. The comprehensive pollution and ecological integrity indexes of the rivers are analyzed. Results of the two evaluations, compared to achieve the river ecological environment evaluation, are as follows. 1) Index of Ecological Integrity evaluation shows that among the sampling points, 18.8% are “healthy”, 28.1% are “sub-healthy”, 40.6% are “fair”, 6.3% are “poor”, and 6.3% are “very poor”. 2) The comprehensive evaluation of the chemical properties of the 32 river ecosystems in Tianjin shows severe overall river pollution and low standard water function area. Of the total sampling sites, 16 (50%) are heavily contaminated and 10 (31.3%) are moderately contaminated. Excessive chemical oxygen demand and ammonia nitrogen are the main causes of water pollution. 3) The Index of Ecological Integrity (IEI) has high correspondence with environmental factors. Pearson correlation analysis results show that the IEI index is significantly correlated with permanganate index (R= - 0.453; P = 0.023<0.05). Analysis results using BEST show that ammonia nitrogen is the best environmental parameter to explain the changes in IEI (R_ho= 0.154; P = 0.02<0.05) and those using RELATE show significant correlation between the biotic index and the environmental parameter matrices (R_ho= 0.154; P = 0.034<0.05).

Tight sandstone reservoirs are generally characterized by complex reservoir quality, non-Darcy flow, and strong heterogeneity. Approaches utilized for evaluating physical property cutoffs of conventional reservoirs maybe inapplicable. Thus, a comprehensive investigation on physical property cutoffs of tight sandstone reservoirs is crucial for the reserve evaluation and successful exploration. In this study, a set of evaluation approaches take advantage of field operations (i.e., core drilling, oil testing, and wireline well logging data), and simulation experiments (i.e., high-pressure mercury injection-capillary pressure (MICP) experiment, oil-water relative permeability experiment, nuclear magnetic resonance (NMR) experiment, and biaxial pressure simulation experiment) were comparatively optimized to determine the physical property cutoffs of effective reservoirs in the Upper Triassic Chang 6, Chang 8 and Chang 9 oil layers of the Zhenjing Block. The results show that the porosity cutoffs of the Chang 6, Chang 8, and Chang 9 oil layers are 7.9%, 6.4%, and 8.6%, and the corresponding permeability are 0.08 mD, 0.05 mD, and 0.09 mD, respectively. Coupled with wireline well logging, mud logging, and oil testing, the cut-off of the thickness of single-layer effective reservoirs are approximately 3.0 m, 3.0 m, and 2.0 m, respectively. Depending on the cutoffs of critical properties, a superimposed map showing the planar distribution of the prospective targets can be mapped, which may delineate the effective boundary of prospective targets for petroleum exploration of tight sandstone reservoirs.

China’s rapid economic development has initiated the deterioration of its ecological environment, posing a threat to the sustainable development of human society. As a result, an assessment of regional sustainability is critical. This paper researches China’s most forested province, Fujian Province, as the study area. We proposed a grid-based approach to assess the regional carbon footprint in accordance with the Intergovernmental Panel on Climate Change’s (IPCC) carbon emission guidelines. Our method of assessment also introduced carbon emission indicators with our improved and published Net Primary Production (NPP) based on process simulation. The carbon footprint in Fujian Province from 2005–2017 was calculated and examined from a spatiotemporal perspective. Ecological indicators were used in the sustainability assessment. The research draws the following conclusions: 1) the carbon footprint in the eastern regions of Fujian Province was higher due to rapid economic development; 2) that of the western regions was lower; 3) an uptrend in the carbon footprint of Fujian Province was observed. All five ecological indicators based on carbon emissions and economic and social data showed an ecologically unsustainable trend over 13 years in the research area due to unsustainable economic development. Therefore, it is urgent to balance the relationship between economic development and environmental protection. Our research provides scientific references for achieving ecological civilization and sustainability in a similar region.

Petrophysics of coals directly affects the development of coalbed methane (CBM). Based on the analysis of the representative academic works at home and abroad, the recent progress on petrophysics characteristics was reviewed from the aspects of the scale-span pore-fracture structure, permeability, reservoir heterogeneity, and its controlling factors. The results showed that the characterization of pore-fracture has gone through three stages: qualitative and semiquantitative evaluation of pore-fracture by various techniques, quantitatively refined characterization of pore-fracture by integrating multiple methods including nuclear magnetic resonance analysis, liquid nitrogen, and mercury intrusion, and advanced quantitative characterization methods of pore-fracture by high-precision experimental instruments (focused-ion beam-scanning electron microscopy, small-angle neutron scattering and computed tomography scanner) and testing methods (m-CT scanning and X-ray diffraction). The effects of acoustic field can promote the diffusion of CBM and generally increase the permeability of coal reservoirs by more than 10%. For the controlling factors of reservoir petrophysics, tectonic stress is the most crucial factor in determining permeability, while the heterogeneity of CBM reservoirs increases with the enhancement of the tectonic deformation and stress field. The study on lithology heterogeneity of deep and high-dip coal measures, the spatial storage-seepage characteristics with deep CBM reservoirs, and the optimizing production between coal measures should be the leading research directions.

Water is the essential resource of the 21st century where innovative water management strategies are needed to improve water security. This paper examines three case studies that exemplify the global water crisis, situated in rapidly urbanizing watersheds: Nairobi River Basin, Kenya; Citarum River Basin, Indonesia; and Addis Ababa River Basin, Ethiopia. Each of these watersheds are implementing large-scale water management strategies inclusive of local communities and regional governments to address water quality and waste management issues. The hydrosocial cycle (Linton, 2010) provides a framework to investigate the social, technical and physical aspects of water flows. Using the hydrosocial cycle as an organizing framework, these watersheds are examined to highlight how water security underpins water justice. The issues of gender and inequity are often overlooked in larger policy, development, and infrastructure discussions where technical requirements, restoration management, and engineering solutions obscure power inequities. Projects are compared to assess the implementation of the hydrosocial cycle through a discussion of social power and structure, technology and infrastructure, and the materiality of water in each location. This comparison reveals a dependence on large-scale technical projects with limited community engagement, and a need for science-based river restoration management. Recommendations are provided to improve and address holistic water management.

High- and low-rank coalbed methane (CBM) are both important fields of CBM development in China, but their formation and production mechanisms differ considerably. The adsorption/desorption behavior of high- and low-rank coals under the coupling of coal–water–gas was investigated using two series of samples. Coal samples from Zhangjiamao (ZJM) coal mine, Ordos basin, and Sihe (SH) coal mine, Qinshui basin, were tested by isothermal adsorption–desorption experiment, natural imbibition experiment, nuclear magnetic resonance, mercury injection porosimetry, contact angle test, and permeability test. Isothermal adsorption and desorption experiments under dry, equilibrium water, and saturated water, were performed to explore the differences between the adsorption and desorption characteristics. The results show that the wettability and permeability of the ZJM low-rank coal sample was considerably higher than that of the SH high-rank coal sample. The imbibition process of the ZJM sample exhibited a high imbibition rate and high total-imbibition volume, whereas the SH sample exhibited a slow imbibition rate and low total-imbibition volume. The ZJM sample had a complex pore structure and diverse pore-size distribution with a lower mercury withdrawal efficiency at 59.60%, whereas the SH sample had a relatively uniform pore-size distribution with a higher mercury withdrawal efficiency at 97.62%. The response of adsorption and desorption of the ZJM sample to water was more significant than that of the SH sample. The desorption hysteresis of the ZJM sample was stronger than that of the SH sample and was more prominently affected by water, which was consistent with its strong wettability and complex pore-throat configuration. A comprehensive adsorption and desorption mode was constructed for high- and low-rank coal samples under coal–water–gas coupling condition. The research results are important to enrich the geological theory of high- and low-rank CBM and to guide efficient CBM recovery.

A multidisciplinary approach using the integrated field of geosciences (e.g., geomorphology, geotectonics, geophysics, and hydrology) is established to conduct groundwater recharge potential mapping of the Kunur River Basin, India. The relative mean error (RME) calculation of the results of three applied techniques and water table data from twenty-four observation wells in the basin over the 2000-2010 period are presented. Nine sub-basins were identified and ranked for the RME calculation, where the observation wells-based ranking was taken as standard order for comparison. A linear model has been developed using six factors (drainage density, surface slope, ruggedness index, lineament density, Bouguer gravity anomaly, and potential maximum water retention capacity) and a grid-wise weighted index. In a separate comparative approach, the sub-basin and grid-wise analyses have been conducted to identify the suitable spatial unit for watershed level hydrological modeling.

As one of the most devastating tropical cyclones over the western North Pacific Ocean, Super Typhoon Lekima (2019) has caused a wide range of heavy rainfall in China. Based on the CMA Multi-source merged Precipitation Analysis System (CMPAS)-hourly data set, both the temporal and spatial distribution of extreme rainfall is analyzed. It is found that the heavy rainfall associated with Lekima includes three main episodes with peaks at 3, 14 and 24 h after landfall, respectively. The first two rainfall episodes are related to the symmetric outburst of the inner rainband and the persistence of outer rainband. The third rainfall episode is caused by the influence of cold, dry air from higher latitudes and the peripheral circulation of the warm moist tropical storm. The averaged rainrate of inner rainbands underwent an obvious outburst within 6 h after landfall. The asymmetric component of the inner rainbands experienced a transport from North (West) quadrant to East (South) quadrant after landfall which was related to the storm motion other than the Vertical Wind Shear (VWS). Meanwhile the outer rainband in the vicinity of three times of the Radius of Maximum Wind (RMW) was active over a 12-h period since the decay of the inner rainband. The asymmetric component of the outer rainband experienced two significant cyclonical migrations in the northern semicircle.

Natural fractures are of crucial importance for oil and gas reservoirs, especially for those with ultralow permeability and porosity. The deep-marine shale gas reservoirs of the Wufeng and Longmaxi Formations are typical targets for the study of natural fracture characteristics. Detailed descriptions of full-diameter shale drill core, together with 3D Computed Tomography scans and Formation MicroScanner Image data acquisition, were carried out to characterize microfracture morphology in order to obtain the key parameters of natural fractures in such system. The fracture type, orientation, and their macroscopic and microscopic distribution features are evaluated. The results show that the natural fracture density appears to remarkably decrease in the Wufeng and Longmaxi Formations with increasing the burial depth. Similar trends have been observed for fracture length and aperture. Moreover, the natural fracture density diminishes as the formation thickness increases. There are three main types of natural fractures, which we interpret as (I) mineral-filled fractures (by pyrite and calcite), i.e., veins, (II) those induced by tectonic stress, and (III) those formed by other processes (including diagenetic shrinkage and fluid overpressure). Natural fracture orientations estimated from the studied natural fractures in the Luzhou block are not consistent with the present-day stress field. The difference in tortuosity between horizontally and vertically oriented fractures reveals their morphological complexity. In addition, natural fracture density, host rock formation thickness, average total organic carbon and effective porosity are found to be important factors for evaluating shale gas reservoirs. The study also reveals that the high density of natural fractures is decisive to evaluate the shale gas potential. The results may have significant implications for evaluating favorable exploration areas of shale gas reservoirs and can be applied to optimize hydraulic fracturing for permeability enhancement.

Malaysian Airlines Flight MH370 disappeared on 8 March 2014, while flying from Kuala Lumpur to Beijing. A flaperon from the flight was found on Reunion Island in July 2015. Two more confirmed pieces of debris were found in Mauritius and Tanzania, and 19 unconfirmed items were found off Mozambique, South Africa, and Madagascar. Drift buoys originating from the designated underwater search area arrived in Reunion Island, Mauritius, and Tanzania. Some of these buoys took a similarly long time as did real debris to reach these destinations, following a heading northeast and then west. For the present study, a maritime object drift prediction model was developed. “High resolution surface currents, Stokes drift, and winds” were processed, and a series of model experiments were constructed. The predicted trajectories of the modeled objects were similar to the observed trajectories of the drift buoys. Many modeled objects drifted northward then westward, ending up in Reunion Island, Mauritius, and Tanzania with probabilities of 5‰, 5‰, and 19‰, respectively. At the end of the simulation, most objects were located near 10°S in the western Indian Ocean. There were significant differences between experiments with different leeway factors, possibly because of the influence of southeast trade winds. The north part of the underwater search area is most likely to be the crash site, because the predicted trajectories of objects originating here are consistent with the many pieces of debris found along the east coast of Africa and the absence of such findings on the west coast of Australia.

The annual peak growth and trend shift of vegetation are critical in characterizing the carbon sequestration capacity of ecosystems. As the well-known area with the fastest vegetation growth in the world, the Loess Plateau (LP) lands find an enhanced greening trend in the annual and growing-season. However, the spatiotemporal dynamics of vegetation peak growth and breakpoints characteristics on time series still needs to be explored. Here, we performed tendency analysis to characterize recent variations in annual peak vegetation growth through a satellite-derived vegetation index (NDVI_max, Maximum Normalized Difference Vegetation Index) and then applied breakpoint analysis to capture abrupt points on the time series. The results demonstrated that the vegetation peak trend had been significantly increasing, with a growth rate at 0.68×10^–2·a^–1 during 2001–2018, and most pixels (70.81%) have a positive linear greening trend over the entire LP. In addition, about 83% of the breakpoint type on the monthly NDVI time series is a monotonic increase at the pixel level, and most pixels (57%) have detected breakpoints after 2010. Our results also showed that the growth rate accelerates in the northwest and decelerates in the southeast after the breakpoint. This study indicates that combining abrupt analysis with gradual analysis can describe vegetation dynamics more effectively and comprehensively. The findings highlighted the importance of breakpoint analysis for monitor timing and shift using time series satellite data at a regional scale, which may help stakeholders to make reasonable and effective ecosystem management policies.

To date, there are very few studies about the spectroscopy of lithium-containing minerals (LCMs) in the scientific community. The main objective of this study is to investigate the capability of Sentinel-2 image and FieldSpec3 spectro-radiometer in terms of mapping five important LCMs, including spodumene, lepidolite, amblygonite, petalite, and eucryptite. Therefore, first the FieldSpec3 spectro-radiometer was used to create the spectral curves of the LCMs. Then, accurate spectral analysis and comparison of the studied LCMs were performed using The Spectral Geologist (TSG) and the Prism software. These two software can show even slight difference in absorption features of different LCMs, which can discriminate and identify these minerals. Lithium-bearing rocks show absorption features at ~365, ~2200, and ~2350 nm and reflective features at ~550–770 nm. These features are consistent with Sentinel-2 bands. Therefore, the created spectral curves were utilized for calibration of Sentinel-2 optical image to detect and map the potential zones of the rock units containing minerals mentioned above in a part of the central Iranian terrane. By using the Spectral Angle Mapper (SAM) classifier module, the potential areas were demarcated. Out of the five LCMs, petalite and spodumene showed more extensive coverage in the study area. Generally speaking, the largest concentration of those LCMs can be seen in southern and centraleastern parts of the study area. The comparison between spectral curves of reference and classified minerals confirmed the high capability of Sentinel-2 image for LCMs mapping. ASTER image classification results also confirmed the presence of the LCMs, but it cannot distinguish the LCMs type successfully.

Poyang Lake, the largest freshwater lake in China, and its surrounding sub-basins have suffered frequent floods and droughts in recent decades. To better understand and quantitatively assess hydrological impacts of climate change in the region, this study adopted the Statistical Downscaling Model (SDSM) to downscale the outputs of a Global Climate Model (GCM) under three scenarios (RCP2.6, RCP4.5 and RCP8.5) as recommended by the fifth phase of the Coupled Model Inter-comparison Project (CMIP5) during future periods (2010–2099) in the Poyang Lake Basin. A semi-distributed two-parameter monthly water balance model was also used to simulate and predict projected changes of runoff in the Ganjiang sub-basin. Results indicate that: 1) SDSM can simulate monthly mean precipitation reasonably well, while a bias correction procedure should be applied to downscaled extreme precipitation indices (EPI) before being employed to simulate future precipitation; 2) for annual mean precipitation, a mixed pattern of positive or negative changes are detected in the entire basin, with a slightly higher or lower trend in the 2020s and 2050s, with a consistent increase in the 2080s; 3) all six EPI show a general increase under RCP4.5 and RCP8.5 scenarios, while a mixed pattern of positive and negative changes is detected for most indices under the RCP2.6 scenario; and 4) the future runoff in the Ganjiang sub-basin shows an overall decreasing trend for all periods but the 2080s under the RCP8.5 scenario when runoff is more sensitive to changes in precipitation than evaporation.

Nowadays, autonomous driving has been attracted widespread attention from academia and industry. As we all know, deep learning is effective and essential for the development of AI components of Autonomous Vehicles (AVs). However, it is challenging to adopt multi-source heterogenous data in deep learning. Therefore, we propose a novel data-driven approach for the delivery of high-quality Spatio-Temporal Trajectory Data (STTD) to AVs, which can be deployed to assist the development of AI components with deep learning. The novelty of our work is that the meta-model of STTD is constructed based on the domain knowledge of autonomous driving. Our approach, including collection, preprocessing, storage and modeling of STTD as well as the training of AI components, helps to process and utilize huge amount of STTD efficiently. To further demonstrate the usability of our approach, a case study of vehicle behavior prediction using Long Short-Term Memory (LSTM) networks is discussed. Experimental results show that our approach facilitates the training process of AI components with the STTD.

Considering snowmelt in mountainous areas as the important source of streamflow, the snow accumulation/melting processes are vital for accurate simulation of the hydrological regimes. The lack of snow-related data and its uncertainties/conceptual ambiguity in snowpack modeling are the different challenges of developing hydro-climatological models. To tackle these challenges, Global Gridded Snow Products (GGSPs) are introduced, which effectively simplify the identification of the spatial characteristics of snow hydrological variables. This research aims to investigate the performance of multi-source GGSPs using multi-stage calibration strategies in hydrological modeling. The used GGSPs were Snow-Covered Area (SCA) and Snow Water Equivalent (SWE), implemented individually or jointly to calibrate an appropriate water balance model. The study area was a mountainous watershed located in Western Iran with a considerable contribution of snowmelt to the generated streamflow. The results showed that using GGSPs as complementary information in the calibration process, besides streamflow time series, could improve the modeling accuracy compared to the conventional calibration, which is only based on streamflow data. The SCA with NSE, KGE, and RMSE values varying within the ranges of 0.47–0.57, 0.54–0.65, and 4–6.88, respectively, outperformed the SWE with the corresponding metrics of 0.36–0.59, 0.47–0.60, and 5.22–7.46, respectively, in simulating the total streamflow of the watershed. In addition to the superiority of the SCA over SWE, the two-stage calibration strategy reduced the number of optimized parameters in each stage and the dependency of internal processes on the streamflow and improved the accuracy of the results compared with the conventional calibration strategy. On the other hand, the consistent contribution of snowmelt to the total generated streamflow (ranging from 0.9 to 1.47) and the ratio of snow melting to snowfall (ranging from 0.925 to 1.041) in different calibration strategies and models resulted in a reliable simulation of the model.

Estimating horizontal winds in and around typhoons is important for improved monitoring and prediction of typhoons and mitigating their damages. Here, we present a new algorithm for estimating typhoon winds using multiple satellite observations and its application to Typhoon Soulik (2018). Four kinds of satellite remote sensing data, along with their relationship to typhoon intensity, derived statistically from hundreds of historical typhoon cases, were merged into the final product of typhoon wind (MT wind): 1) geostationary-satellite-based infrared images (IR wind), 2) passive microwave sounder (MW wind), 3) feature-tracked atmospheric motion vectors, and 4) scatterometer-based sea surface winds (SSWs). The algorithm was applied to two cases (A and B) of Typhoon Soulik and validated against SSWs independently retrieved from active microwave synthetic aperture radar (SAR) and microwave radiometer (AMSR2) images, and vertical profiles of wind speed derived from reanalyzed data and dropsonde observations. For Case A (open ocean), the algorithm estimated the realistic maximum wind, radius of maximum wind, and radius of 15 m/s, which could not be estimated using the reanalysis data, demonstrating reasonable and practical estimates. However, for Case B (when the typhoon rapidly weakened just before making landfall in the Korean Peninsula), the algorithm significantly overestimated the parameters, primarily due to the overestimation of typhoon intensity. Our study highlights that realistic typhoon winds can be monitored continuously in real-time using multiple satellite observations, particularly when typhoon intensity is reasonably well predicted, providing timely analysis results and products of operational importance.

Lacustrine shale oil resources in China are abundant, with remarkable exploration breakthroughs being achieved. Compared to marine shale oil in North America, efficient exploration of lacustrine shale oil is more difficult; thus, selecting favorable layer and optimization zone for horizontal wells is more important. In this study, based on systematic coring of approximately 500 m fine-grained deposits of the Kong 2 Member, combining laboratory tests and log data, source rock geochemistry and reservoir physical properties, the favorable rock fabric facies for oil accumulation was analyzed and classified. First, the dominant lithologic facies, organic facies, and bed combination facies were determined based on mineral composition from logging, total organic content (TOC), and sedimentary structure. Secondly, 10 fabric facies were classified by combining these three facies, with 4 fabric facies were found to have high TOC content, high total hydrocarbon, and strong fluorescence features, indicating good shale oil enrichment. Thirdly, the distribution of the upon good fabric facies was identified to be located at the top of the Kong 2 Member, with evidences of seismic resistivity inversion, thermal maturity, structure depth, and strata thickness. And the favorable facies were found to be stably distributed lateral at the area of about 100 km². High oil flow has been detected at this layer within this area by several wells, including horizontal wells. The exploratory study of fabric facies classification and evaluation provides a new research idea for lacustrine shale oil exploration and effectively promotes breakthroughs in lacustrine shale oil exploration in Bohai Bay Basin.

The stability of dawsonite is an important factor affecting the feasibility evaluation of CO₂ geological storage. In this paper, a series of experiments on the interaction of CO₂-water-dawsonite-bearing sandstone were carried out under different CO₂ pressures. Considering the dissolution morphology and element composition of dawsonite after the experiment and the fluid evolution in equilibrium with dawsonite, the corrosion mechanism of dawsonite led by CO₂ partial pressure was discussed. The CO₂ fugacity of the vapor phase in the system was calculated using the Peng–Robinson equation of state combined with the van der Waals 1-fluid mixing rule. The experimental results indicated that the thermodynamic stability of dawsonite increased with the increase of CO₂ partial pressure and decreased with the increase of temperature. The temperature at which dawsonite dissolution occurred was higher at higher f_{{\mathrm{C}\mathrm{O}}_2}. There were two different ways to reduce dawsonite’s stability: the transformation of constituent elements and crystal structure damage. Dawsonite undergoes component element transformation and crystal structure damage under different CO₂ pressures with certain temperature limits. Based on the comparison of the corrosion temperature of dawsonite, three corrosion evolution models of dawsonite under low, medium, and high CO₂ pressures were summarized. Under conditions of medium and low CO₂ pressure, as the temperature continued to increase and exceeded its stability limit, the dawsonite crystal structure was corroded first. Then the constituent elements of dawsonite dissolved, and the transformation of dawsonite to gibbsite began. At high CO₂ pressure, the constituent elements of dawsonite dissolved first with the increase of temperature, forming gibbsite, followed by the corrosion of crystalline structure.

Soil organic carbon (SOC) plays an essential role in the carbon cycle and global warming mitigation, and it varies spatially in relation to other soil and environmental properties. But the national distributions and the impact mechanisms of SOC remain debated in China. Therefore, how soil texture and climate factors affect the SOC content and the regional differences in SOC content were explored by analyzing 7857 surface soil samples with different land-use. The results showed that the SOC content in China, with a mean value of 11.20 g·kg⁻¹, increased gradually from north to south. The SOC content of arable land in each geographical area was lower than in grassland and forest-land. Although temperature also played a specific role in the SOC content, precipitation was the most critical climate factor. The SOC content was positively correlated with the silt and clay content. The lower the temperature, the greater the effect of environmental factors on SOC. In contrast, the higher the temperature, the more significant impact of soil texture on SOC. The regional difference in SOC highlights the importance of soil responses to climate change. Temperature and soil texture should be explicitly considered when predicting potential future carbon cycle and sequestration.

A nonlinear artificial intelligence ensemble forecast model has been developed in this paper for predicting tropical cyclone (TC) tracks based on the deep neural network (DNN) by using the 24-h forecast data from the China Meteorological Administration (CMA), Japan Meteorological Agency (JMA) and Joint Typhoon Warning Center (JTWC). Data from a total of 287 TC cases over the Northwest Pacific Ocean from 2004 to 2015 were used to train and validate the DNN based ensemble forecast (DNNEF) model. The comparison of model results with Best Track data of TCs shows that the DNNEF model has a higher accuracy than any individual forecast center or the traditional ensemble forecast model. The average 24-h forecast error of 82 TCs from 2016 to 2018 is 63 km, which has been reduced by 17.1%, 16.0%, 20.3%, and 4.6%, respectively, compared with that of CMA, JMA, JTWC, and the error-estimation based ensemble method. The results indicate that the nonlinear DNNEF model has the capability of adjusting the model parameter dynamically and automatically, thus improving the accuracy and stability of TC prediction.

As the major primary energy importer in the world, China has engaged in considerable efforts to ensure energy security. However, little attention has been paid to China’s embodied primary energy exports. Separating the international export from regional final demand, this paper focuses on quantifying provincial primary energy requirement arising from China’s exports, and tracing its concrete interprovincial supply chains using multi-regional input-output analysis and structural path analysis. Results show that China’s embodied primary energy uses in exports (EEE) reached 633.01 Mtce in 2012, compared to 565.15 Mtce in 2007. Four fifths of the EEE were supplied through interprovincial trade. Eastern coastal provinces accounted for nearly 70% of the national total EEE, while their primary energy supply mainly sourced from the central and western provinces. Most interprovincial supply chain paths of embodied primary energy exports were traced to the coal mining sectors of Shanxi, Inner Mongolia and Shaanxi. Critical receiving sectors in the final export provinces were Chemical industry, Metallurgy, Electronic equipment, Textile and other manufacturing sectors. Important transmission sectors were Electricity and hot water production and supply and Petroleum refining, coking, etc. In view of the specific role of exports in primary energy requirements, provincial energy uses are largely dependent on its domestic trade position and degrees of industrial participation in the global economy. Managing critical industrial sectors and supply chain paths associated with the international exports provide new insights to ensure China’s energy security and to formulate targeted energy policies.

Diagenesis exerts an important control on porosity evolution, and research of diagenesis and diagenetic minerals provides insights into reservoir quality evaluation and CO₂ storage. Thin section, XRD (X-ray diffraction), CT (Computed Tomography), scanning electron microscopy (SEM), and NMR (Nuclear Magnetic Resonance) tests were used to investigate composition, texture, pore spaces, and diagenesis of sandstones in Paleogene Dongying Formation in Bohai Bay Basin, China, with special aims to unravel diagentic dissolution along bedding planes. The oversized pores, remnants in feldspar-hosted pores, and kaolinite within feldspar grains indicate a high degree of dissolution the framework grains experienced during burial. The CO₂-rich or organic acids are responsible for the feldspar dissolution. Grain size plays the primary role in enhancing bedding dissolution process, and bedding planes in fine-medium grained sandstones with high content of feldspars are frequently enlarged by dissolution. The CT scanning image confirms dissolution pores are distributed discontinuously along the bedding planes. The dissolution pores along bedding planes have large pore size, and correspond to the right peak of the bi-modal T₂ (transverse relaxation time) spectrum. The laminated sandstones and siltstones, or sandstones with cross beddings help improve framework grain dissolution. These new findings help improve the understanding of diagenetic models, and have implications in reservoir quality prediction and resource assessments in sandstones.

Crystallinity, polytype, and morphology of clay minerals in the Luochuan loess-palaeosols in Shaanxi Province, northwest China were studied in order to have an insight into their origin using X-ray diffraction (XRD) analysis and scanning electron microscopy (SEM) methods. The SEM observations showed that the morphology of some illites seems to be lath-shaped crystals. An analysis of illite crystallinity (IC) on the Luochuan section indicated that the origin of illite was related to the rocks of an anchizone. Most illite in the Luochuan loess-palaeosol section were of 2M₁ polytype, but some were of 1M polytype formed by weathering of feldspar in the process of pedogenesis. Illite in the Luochuan section has undergone both physical and chemical weathering. These results revealed that most illite were of detrital origin related to the source area of an anchizone, but parts of the illite were of an authigenic origin formed during pedogenesis after sedimentation. Chlorites in the samples of the Luochuan section were mainly composed of irregular flaky grains and their crystallinity was good. These showed that chlorite had the detrital origin formed by physical weathering. Kaolinite crystallinity was relatively good. The value of CIA on the Luochuan section ranges from 61.9 to 69, and therefore kaolinite could not be formed during weathering and pedogenesis. These results indicated that the kaolinite had a detrital origin. Morphology of smectite seems to be capillaceous. The XRD patterns of all samples contained diffraction peaks at 1.5218 Å (nontronite) and 1.5052 Å (montmorillonite), thus indicating an intermediate composition between trioctahedral and dioctahedral smectite. The smectite crystallinity was very poor. These results revealed that smectite in the study area was authigenic rather than detrital origin.

The sharp increase in the demand for lithium (Li) for high-energy-storage battery materials due to its high specific energy and low negative chemical potential render Li a geopolitically significant resource. It is urgent to develop a low-cost, efficient method to improve lithium extraction. Herein, Li ion (Li⁺) adsorption in coal-bearing strata kaolinite (CSK) was studied. The effects of pre-activation acid leaching (meta-kaolinite/H₂SO₄, MK-HS) and dimethyl sulfoxide intercalation (coal-bearing strata kaolinite/dimethyl sulfoxide, CSK-DMSO) on the Li⁺ adsorption capacity were studied under the same adsorption conditions. The results indicated that the adsorption was completed in 60 min under alkaline conditions (pH = 8.5), a high solution concentration (400 mg/L), and a low dosage (1 g/100 mL); and the comprehensive adsorption capacity is MK-HS > CSK-DMSO > CSK. Furthermore, the DMSO intercalation caused the interlayer spacing of the CSK to increase, which provided more space for Li⁺ to enter and increase the adsorption capacity. After thermal pre-activation and acid leaching, structural failure and lattice collapse resulted in the presence of more micropores in the MK-HS, which resulted in a 10-fold increase in its specific surface area and caused coordination bond changes (Al(VI) to Al(IV)) and leaching of aluminum (Al) from the lattice. It is proposed that these structural changes greatly improve the activity of CSK so that Li⁺ cannot only adsorb onto the surface and between the layers but can also enter the lattice defects, which results in the MK-HS having the best adsorption performance. Combined with the adsorption kinetics analysis, the adsorption methods of CSK and two modified materials include physical adsorption and chemical adsorption. In this study, the adsorption capacity of CSK and its modified products to Li were explored, providing a new option for the reuse of CSK and the extraction of Li.

The demand for efficient and cost-effective renewable energy is increasing as traditional sources of energy such as oil, coal, and natural gas, can no longer satisfy growing global energy demands. Among renewable energies, wind energy is the most prominent due to its low, manageable impacts on the local environment. Based on meteorological data from 2006 to 2014 and multi-source satellite data (i.e., Advanced Scatterometer, Quick Scatterometer, and Windsat) from 1999 to 2015, an assessment of the onshore and offshore wind energy potential in Jiangsu Province was performed by calculating the average wind speed, average wind direction, wind power density, and annual energy production (AEP). Results show that Jiangsu has abundant wind energy resources, which increase from inland to coastal areas. In onshore areas, wind power density is predominantly less than 200 W/m², while in offshore areas, wind power density is concentrates in the range of 328–500 W/m². Onshore areas comprise more than 13,573.24 km², mainly located in eastern coastal regions with good wind farm potential. The total wind power capacity in onshore areas could be as much as 2.06 × 10⁵ GWh. Meanwhile, offshore wind power generation in Jiangsu Province is calculated to reach 2 × 10⁶ GWh, which is approximately four times the electricity demand of the entire Jiangsu Province. This study validates the effective application of Advanced Scatterometer, Quick Scatterometer, and Windsat data to coastal wind energy monitoring in Jiangsu. Moreover, the methodology used in this study can be effectively applied to other similar coastal zones.

Global maps of bioclimatic variables currently exist only at very coarse spatial resolution (e.g. WorldClim). For ecological studies requiring higher resolved information, this spatial resolution is often insufficient. The aim of this study is to estimate important bioclimatic variables of Mongolia from Earth Observation (EO) data at a higher spatial resolution of 1 km. The analysis used two different satellite time series data sets: land surface temperature (LST) from Moderate Resolution Imaging Spectroradiometer (MODIS), and precipitation (P) from Climate Hazards Group Infrared Precipitation with Stations (CHIRPS). Monthly maximum, mean, and minimum air temperature were estimated from Terra MODIS satellite (collection 6) LST time series product using the random forest (RF) regression model. Monthly total precipitation data were obtained from CHIRPS version 2.0. Based on this primary data, spatial maps of 19 bioclimatic variables at a spatial resolution of 1 km were generated, representing the period 2002–2017. We tested the relationship between estimated bioclimatic variables (SatClim) and WorldClim bioclimatic variables version 2.0 (WorldClim) using determination coefficient (R²), root mean square error (RMSE), and normalized root mean square error (nRMSE) and found overall good agreement. Among the set of 19 WorldClim bioclimatic variables, 17 were estimated with a coefficient of determination (R²) higher than 0.7 and normalized RMSE (nRMSE) lower than 8%, confirming that the spatial pattern and value ranges can be retrieved from satellite data with much higher spatial resolution compared to WorldClim. Only the two bioclimatic variables related to temperature extremes (i.e., annual mean diurnal range and isothermality) were modeled with only moderate accuracy (R² of about 0.4 with nRMSE of about 11%). Generally, precipitation-related bioclimatic variables were closer correlated with WorldClim compared to temperature-related bioclimatic variables. The overall success of the modeling was attributed to the fact that satellite-derived data are well suited to generated spatial fields of precipitation and temperature variables, especially at high altitudes and high latitudes. As a consequence of the successful retrieval of the bioclimatic variables at 1 km spatial resolution, we are confident that the estimated 19 bioclimatic variables will be very useful for a range of applications, including species distribution modeling.

Long-chain n-alkanes are one of the most common organic compounds in terrestrial plants and they are well-preserved in various geological archives. n-alkanes are relatively resistant to degradation and thus they can provide high-fidelity records of past vegetation and climate changes. Nevertheless, previous studies have shown that the interpretation of n-alkane proxies, such as the average chain length (ACL), is often ambiguous since this proxy depends on more than one variable. Both vegetation and climate could exert controls on the n-alkane ACL, and hence its interpretation requires careful consideration, especially in regions like the Qinghai-Tibet Plateau (QTP) where topography, biome type and moisture source are highly variable. To further evaluate the influences of vegetation and climate on the ACL in high-elevation lakes, we examined the n-alkane distributions of the surface sediments of 55 lakes across the QTP. Our results show that the ACL across a climatic gradient is significantly affected by precipitation, rather than by temperature. The positive correlation between ACL and precipitation may be because of the effect of microbial degradation during deposition. Finally, we suggest that more caution is needed in the interpretation of ACL data in different regions.

Gaofen-3 (GF-3) is the first Chinese spaceborne multi-polarization synthetic aperture radar (SAR) instrument at C-band (5.43 GHz). In this paper, we use data collected from GF-3 to observe Super Typhoon Lekima (2019) in the East China Sea. Using a VH-polarized wide ScanSAR (WSC) image, ocean surface wind speeds at 100m horizontal resolution are obtained at 21:56:59 UTC on 8 August 2019, with the maximum wind speed, 38.9 m·s⁻¹. Validating the SAR-retrieved winds with buoy-measured wind speeds, we find that the root mean square error (RMSE) is 1.86 m·s⁻¹, and correlation coefficient, 0.92. This suggests that wind speeds retrieved from GF-3 SAR are reliable. Both the European Centre for Medium-Range Weather Forecasts (ECMWF) fine grid operational forecast products with spatial resolution, and China Global/Regional Assimilation and Prediction Enhance System (GRAPES) have good performances on surface wind prediction under weak wind speed condition (<24 m·s⁻¹), but underestimate the maximum wind speed when the storm is intensified as a severe tropical storm (>24 m·s⁻¹). With respect to SAR-retrieved wind speeds, the RMSEs are 5.24 m·s⁻¹ for ECMWF and 5.17 m·s⁻¹ for GRAPES, with biases of 4.16 m·s⁻¹ for ECMWF and 3.84 m·s⁻¹ for GRAPES during Super Typhoon Lekima (2019).