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Studying the formation and evolution mechanism of heavy pollution haze events is beneficial to control the regional scale air quality and to formulate the prevention policies of severe haze pollution.Based on the WRF-CMAQ model and actual observation data， a severe haze event which occurred in Chengdu of Sichuan Basin from December 23， 2016 to January 7， 2017 was reproduced.The distribution of temporal and spatial variations of PM2.5 concentration and ventilation coefficient， the physical and chemical processes and the distribution of potential pollution source areas were analyzed to study the formation and evolution mechanism of this severe pollution haze event.Major results were as follows： （1） The environmental conditions of low temperature and low wind speed during the haze event created favorable conditions for the accumulation of pollutants.（2） The northerly airflow in the north of the basin， the southwesterly airflow in the south and the lower ventilation coefficient value （weak turbulent diffusion capability of atmosphere） were the main reasons for the accumulation of pollutants.The PM2.5 concentration in Chengdu reached the peak under the influence of the northeast airflow.The dissipation of pollutants was mainly because of the strengthening of the northerly airflow and the higher ventilation coefficient value （strong turbulent diffusion capability of atmosphere）.（3） The positive contribution of the aerosol process and emission sources in this haze event was strengthened.And the increase in PM2.5 was mainly at night （the negative contribution of the advection process and the weak diffusion process） and the magnitude of the increase was greater relative to the decrease， resulting in an overall gradual increase in PM2.5.（4） PSCF and CWT analysis showed that the airflows with high PM2.5 concentration in Chengdu mainly came from its northeast and southwest directions during this haze event， and the potential pollution source areas were generally distributed in a northeast-southwest band.

China is a nation severely impacted by landslide disasters, which poses a great threat to the lives and properties of people in the disaster-affected areas. Landslide susceptibility assessment, as an important tool for landslide risk prediction, is of great significance for disaster mitigation and prevention. However, traditional landslide susceptibility assessment faces the issue of imbalanced data between landslide and non-landslide samples, leading to the inherent undersampling of non-landslide data in the training set. This results in the loss of important information features related to landslide events, thereby affecting the reliability of landslide susceptibility assessment. In this study, using the Zigui-Badong section of the Three Gorges Reservoir Area as an example, 14 evaluation factors, such as elevation and slope were chosen as landslide susceptibility assessment factors, and the original training set and the validation set were divided. In this study, the synthetic minority oversampling technique - Tomek Links (SMOTE-Tomek) method was employed to process the original training dataset, construct the input training set. A convolutional neural networks (CNN) was then trained using this input data, resulting in the SMOTE-Tomek-CNN coupling model. In addition, by intersecting the SMOTE-Tomek method with undersampling methods (random undersampling, RUS), they were separately coupled with the CNN model and support vector machine model (SVM) to form three coupled models: SMOTE-Tomek-SVM, RUS-CNN, and RUS-SVM. These were compared with the SMOTE-CNN coupled model. The results indicate that, among the four coupling models, the SMOTE-CNN coupled model has higher specific class accuracy and area under the ROC curve, with values of 73.60% and 0.965, respectively. This indicates that this method's predictive ability is superior to that of traditional methods, making it a reliable resource for landslide prediction in the studied area.

Objective Enhancing the heat transfer performance of heat transfer media is an effective means of efficiently exploiting geothermal resources. Numerous studies have shown that the addition of nanoscale metals or metal oxides to fluids can effectively improve the heat transfer capacity of the fluid. The physical parameters that can impact the heat transfer performance of nanofluids are type, mass fraction, size of the nanoparticle, dispersant mass fraction. Additionally, the flow rate can have an important effect on the heat transfer performance of nanofluids. Methods In this study, spherical nano-CuO and spherical nano-Al2O3 were used as nanomaterials for configuring nanofluids. The particle size of nanomaterials ranges from 20 nm to 50 nm. Sodium dodecylbenzene sulfonate was selected as the dispersant for configuring the nanofluids. Basic heat transfer experiments are performed on nanofluids by utilizing a self-constructed basic heat transfer experimental setup. The physical parameters of the nanofluids were also optimized. In addition, a self-designed experimental setup for recirculating heat exchange was established. This experimental system uses geothermal water from hydrothermal geothermal wells as the heat source. The experimental system was also utilized for field testing in a hydrothermal-type geothermal well in Yingshan County, Hubei Province. The preferred nanofluid and deionized water from the basic heat transfer experiments were subjected to on-site circulating heat transfer experiments. Comparison of the circulating heat transfer performance of nanofluids and water under actual heat source conditions in the field. The effect of the flow rate on the heat transfer performance of nanofluids and water under real heat source boundary conditions in the field is also discussed. Results The results show that (1) the heat transfer performance of CuO nanofluids is better than that of Al2O3 nanofluids. (2) There is a negative correlation between the heat transfer performance of nanofluids and the nanoparticle mass fraction. (3) The nanofluid warming efficiency was highest at a 1% mass fraction of CuO nanoparticles. The nanofluid temperature increased from 25 ℃ to 79.2 ℃ in 150 s. The nanofluid temperature increased by 4.1 ℃ more than that of deionized water in the same amount of time. Moreover, the wettability of the nanofluid-heat source interface decreases with increasing nanoparticle mass fraction. The heat transfer performance of nanofluids increases and then decreases with increasing particle size. The best heat transfer performance of the nanofluid was achieved when the nanoparticle size was 40 nm. (4) The heat transfer performance of nanofluids is negatively correlated with the dispersant mass fraction. The best heat transfer performance of the nanofluid was achieved when the dispersant mass fraction was 1%. (5) The heat transfer performance of the nanofluid is negatively correlated with the flow rate when the fluid is in laminar flow. The motion of nanoparticles is progressively more intense when the fluid is in a turbulent state. This phenomenon can effectively enhance the heat transfer performance of nanofluids. Conclusion The research results can provide a basis for the application of nanofluids in geothermal heat transfer to improve the heat transfer efficiency of geothermal systems. It also provides theoretical references for the selection of nanofluid parameters as well as fluid flow rate parameters applied to geothermal heat transfer.

Abstract Landslides, recognized as a significant global natural disaster, necessitate an exploration of the impact of various resolution types in sampling strategies on Landslide Susceptibility Mapping (LSM) results. This study focuses on the segment from Zigui to Badong within the Three Gorges Reservoir Area, utilizing two resolution types: sampling resolution and spatial resolution, The Support Vector Machine (SVM) is employed to obtain LSM results, which are then analyzed using Receiver Operating Characteristic (ROC) curve, specific category accuracy and statistical methods. Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) were used to verify the reliability of the results. Additionally, five common machine learning models, including Logistic Regression (LR), are used to conduct experiments on four sampling resolutions (10 m,30 m,50 m and 70 m) to further investigate the effect of sampling resolution on LSM results. These are evaluated using a comprehensive quantitative method. The results reveal that increasing spatial resolution improves the prediction accuracy, while increasing sampling resolution produces a contrary effect. Furthermore, the impact of spatial resolution on LSM results is more pronounced than that of sampling resolution. Finally, Fanjiaping landslide and Huangtupo landslide are selected as references for comparative analysis, with the results aligning with engineering reality.

The Qinghai-Xizang （Tibetan） Plateau is known as the Asian water tower.The change of its water resources has an important impact on the weather and climate in the lower reaches.Precipitation is a key role in the water cycle.Therefore， it is of great significance to accurately simulate plateau precipitation for water resources security in China.In recent years， some studies have found that the convection-permitting model （the cumulus parameterization scheme could be turned off when grid scale is less than 4 km） could improve the precipitation simulation over the Qinghai-Xizang （Tibetan） Plateau.However， the previous studies only selected 1~3 cumulus parameterization schemes for comparison.It is still unknown whether convection-permitting model is superior to any cumulus parameterization scheme.In this paper， the ability of nine cumulus parameterization schemes in WRF and convection-permitting model （CPM） in simulating the precipitation over the Qinghai-Xizang （Tibetan） Plateau in the summer of 2009 was evaluated.The results showed that the simulations overestimate the summer precipitation over Qinghai-Xizang （Tibetan） Plateau in 2009， and the error was about 0.4~2 mm·d-1.The over simulation of CAPE and latent heat flux in Qinghai-Xizang （Tibetan） Plateau may be one of the reasons for the overestimations.Among all simulations， the G3 cumulus parameterization scheme has the best simulation of the mean precipitation the mean precipitation and the dinural cycles precipitation and it can can better capture the precipitation intensity， spatial distribution， precipitation area and diurnal cycles of the mean precipitation.CPM showed overall the second best precipitation simulation following G3 cumulus parameterization scheme， which can not effectively improve the simulation of diurnal cycles of precipitation， but can improve the simulation of precipitation frequency.In different plateau ecological regions， all simulations cannot reasonably simulate the precipitation in the desert area and the southern foot of the Himalaya， but compared with the cumulus parameterization schemes， CPM can greatly reduce the error in the desert area.In other regions， CPM and Tiedtke cumulus parameterization scheme performed well.Considering the mean precipitation and precipitation frequency， the CPM， Tiedtke and G3 cumulus parameterization scheme have the minimum simulation error for precipitation in different regions and intensity.Therefore， we recommend to adopt G3 or Tiedtke cumulus parameterization schemes in simulating summer precipitation over the Qinghai-Xizang （Tibetan） Plateau， and when the computational resources are allowed， the high-resolution CPM can be considered to improve the precipitation frequency simulations.

The climate of Southwest China is wet all year round， but the frequent drought disasters in recent years have caused huge economic losses such as crop yield reduction and forest fire.In order to fully understand the anomalies of water vapor transport in drought years in Southwest China and provide reference for early warning of drought disasters in this area in the future， this study used TRMM and APHRODITE precipitation data to analyze the interannual variation of precipitation and the interannual variation of precipitation in various seasons in Southwest China from 1998 to 2019， selected the summer dry year （2011）， autumn dry year （2009） and 2008， which were relatively wet in summer and autumn.Using Lagrangian transport model FLEXPART， we tracked the paths of water vapor transport and water vapor sources in the two extreme dry seasons （the autumn of 2009 and the summer of 2011）， and compared with the summer and autumn of the wet year （2008）， respectively.The results showed that： （1） The paths of water vapor transport in dry and wet year are consistent， and the paths in southwest China in summer can be divided into three main paths： the southwest path， the southeast path and the northwest path， among which the most dominant is the southwest path， so the main water vapor source area are the Arabian Sea——the Bay of Bengal.In autumn， the main paths can be divided into two： the southeast path and the northwest path， of which the most important is the southeast path， so the main source of water vapor is South China Sea——the Pacific Northwest.（2） There are differences in the strength of water vapor transport between dry and wet years.The reason for the drought in Southwest China in summer is that the water vapor transported by the southwest route is weak， while the reason for the drought in Southwest China in autumn is that the water vapor transported by southeast route is weak.

CO2 geological storage in low-permeability sandstone reservoirs is one of the effective means to realize CO2 capture, utilization and storage (CCUS). As CO2 continues to be injected into the absorbing layer, some weakly cemented sandstone particles will migrate with CO2 in pores and fractures. Particle accumulation is formed, which affects the stability of CO2 injection. In order to reveal the dynamic accumulation and microscopic mechanism of polymorphic sandstone particles, a discrete element fluid-solid coupling injection plugging model based on polymorphic sand particles was established. The model considers mineral particle parameters, such as multi-level particle size, irregular shape, and rotation, and fluid physical properties, such as fluid density and fluid velocity. The model can realize the dynamic prediction of the transient accumulation process of injected fluid and mineral particles. The quantitative relationship among CO2 physical properties, weakly cemented irregular sand parameters and injection plugging efficiency was revealed. The results indicate that: ① the highest factor affecting the accumulation of mineral particles is the concentration of mineral particles. The particle concentration of 5% increases the accumulation of mineral particles in pores by 52.06% compared with the particle concentration of 3%. There is a negative correlation between the increase rate of particle accumulation and the increase rate of mineral particle concentration; ② In the case of the same amount of injected CO2 and mineral particles, the accumulation is the highest when the average size of particles is 1/3 of the pore diameter. Small changes in mineral grain density have less impact on the CO2 injection. ③ The CO2 injection reduces the density of multiphase fluid in the sandstone pores, reduces the blockage of irregular mineral particles in the pores. ④ The CO2 injection rate increases by 60%, and the accumulation of mineral particles in the pores increases by 1.2%. The increase of injection velocity increases the plugging ratio of mineral particles in the pores, which is not conducive to the injection of CO2.

Abstract The Zigui–Badong section of the Three Gorges Reservoir area is used as the research area in this study to research the impact of unbalanced sample sets on Landslide Susceptibility Mapping (LSM) and determine the sample ratio interval with the best performance for different models. We employ 12 LSM factors, five training sample sets with different sample ratios (1:1, 1:2, 1:4, 1:8, and 1:16), and C5.0, Support Vector Machine (SVM), Logistic Regression (LR), and one-dimensional Convolution Neural Network (CNN) models are used to obtain landslide susceptibility index and landslide susceptibility zoning in the study area, respectively. The prediction performance of the model is evaluated by the receiver operating characteristic curve area under the curve value, five statistical methods, and specific category precision. The results show that the CNN, SVM, and LR models in the sample ratio of 1:2 achieve better performance than on the balanced sample set, which indicates the importance of the unbalanced sample set in training the LSM modeling. The C5.0 model is always in a state of overfitting in this study and needs to be further studied. The conclusions put forward in this study help improve the scientificity and reliability of LSM.

Based on the gale-concentration degree and gale-concentration period， the temporal and spatial distribution characteristics of gale frequency and its influence on sandstroms are analyzed with the observation gale and sandstroms data for the peiod from 1961 to 2015 from surface meteorological stations.The following conclusions were drawn： （1） There is a good positive correlation between the frequency of sandstroms weather and the frequency of gale weather.The interannual variation trend of sand and sandstroms weather in southern Xinjiang is basically the same as that of gale weather.The frequency of sandstroms decreased abruptly after 1979 and stabilized after 2000.（2） The duration of the gale season was relatively fixed （April-August）， and the frequency of gale in each month was more than 20， during the year， the gale weather occurred mainly between mid-late May and early June， and there is a tendency to appear in advance.（3） Northern Tarim Basin is the area with frequent gale， and the inter-annual changes in gale days are more intense.Southern Tarim Basin is a region with fewer gale， and the frequency of gale varies little from year to year.Among them， the northern part of the South Xinjiang Basin （Kashgar， northern Bayingolin Mongol Autonomous Prefecture） has more concentrated gale weather during the year， the gale season is shorter， and the outbreak period is after late May； the southern regions （Hotan， Kizilsu Kirghiz Autonomous Prefecture， etc.） have gale windy weather during the year The situation is more dispersed， the gale season is longer， and the outbreak period is mainly before mid-May.

Due to increasing anthropogenic pressure, over half of the world’s tropical forests are reforested or afforested secondary forests or plantations. The recovery pace and potential of these forests depend largely on soil microbially-mediated biogeochemical cycling. Here we measured soil extracellular enzyme activities and quantified microbial metabolic limitations using a vector analysis in a bare land (BL, representing the original state before restoration), two afforested sites [i.e. a restored secondary forest (MF) and a managed Eucalyptus exserta plantation (EP)] and a nearby undisturbed forest (UF) in south China. Results showed that soil microbial metabolisms were co-limited by carbon (C) and phosphorus (P) across the four forests. Both microbial C and P limitations were higher in BL than UF. Microbial C limitation significantly reduced after restoration only in MF when compared to BL, but it was still higher than that in UF. Interestingly, microbial P limitation significantly enhanced after restoration in both EP and MF when compared to BL, and it did not differ between the two restored forests. Structural equation modeling (SEM) showed that microbial C limitation was primarily attributed to microbial C use efficiency, while microbial P limitation was co-driven by plant biomass, microbial C use efficiency and soil P availability. These findings suggest microbial C limitation could be gradually recovered after forest restoration in southern China, which would facilitate soil organic carbon accumulation. However, the enhanced microbial P limitation after forest restoration underlines the necessity to develop optimal P management in these restored forests.

Apicomplexan protozoa, which are a group of specialized intracellular parasitic protozoa, infect humans and other animals and cause a variety of diseases. The lack of research on the interaction mechanism between Apicomplexan protozoa and their hosts is a key factor restricting the development of new drugs and vaccines. In the early stages of infection, cell apoptosis is inhibited by Apicomplexan protozoa through their interaction with the host cells; thereby, the survival and reproduction of Apicomplexan protozoa in host cells is promoted. In this review, the key virulence proteins and pathways are introduced regarding the inhibition of cell apoptosis by the interaction between the protozoa and their host during the early stage of Apicomplexan protozoa infection. It provides a theoretical basis for the development of drugs or vaccines for protozoal diseases.

Wetlands, which are composed of soil, vegetation and water, have sufficient water supply and are sensitive to climate change. This study analyzes the coupling degree between wetlands and atmosphere and discusses the influence of environmental factors (solar radiation and water vapor pressure deficit) on latent heat flux by using the experimental data from the Maduo Observatory of Climate and Environment of the Northwest Institute of Eco-Environment and Resource, CAS and WRF models. The results showed that, during the vegetation growing season, the average value of Ω (decoupling factor) is 0.38 in alpine wetlands, indicating that the coupling between wetlands and atmosphere is poor. Solar radiation is the main factor influencing the latent heat flux in the results of both observation data analysis and model simulation, and solar radiation and water vapor pressure deficit still have the opposite reaction to latent heat flux; when solar radiation increased by 30%, the average daily amount of latent heat flux increased from 5.57 MJ·m−2 to 7.50 MJ·m−2; when water vapor pressure deficit increased by 30%, the average daily amount of latent heat flux decreased to 5.17 MJ·m−2. This study provides a new research approach for the study of the parameterization of latent heat flux and evapotranspiration in the context of global climate change

Land subsidence is a serious problem that affects the construction of traffic engineering in the economic development zone in southwestern Shandong Province. This paper selects the range of 5 km on both sides of a linear project as the research area. The article collects RadarSAT-2(2017-2020), Sentinel-1A(2019-2020) archived data , geological data, hydrogeological data, and mineral development data, and uses time-series InSAR measurement to analyze the distribution characteristics and laws of land subsidence in the study area. The research indicates: the main causes of ground subsidence in the study area are coal mine goaf collapse and excessive groundwater mining; the former forms a settlement funnel with the mining area as the center, the change of settlement rate and the movement of the settlement center are closely related to the mining progress and transfer of the coal mining area; The latter’s settlement distribution law is related to the distribution of groundwater use areas, forming a subsidence zone that similar to the range of groundwater mining. The study area continued to experience subsidence during 2017 to 2020, with the maximum annual subsidence rate at 136.5 mm/a, and the cumulative maximum subsidence in a single year at 220 mm. After checking the observation results of CPI benchmarking points during the same period, the average error of InSAR data processing results is less than 1cm/a, and the correlation coefficient is more than 70%. The analysis method adopted in this paper can timely and accurately reflect the changes in land subsidence throughout the study area, provide effective and reasonable reference for route planning and geological disaster remediation.

Accurate characterization of land use and land cover changes (LULCC) is essential for numerical models to capture LULCC-induced effects on regional meteorology and air quality, while outdated LULC dataset largely limits model capability in reproducing land surface parameters, particularly for complex terrain. In this study, we incorporate land cover data from MODIS in 2019 into the Weather Research and Forecasting (WRF) model to simulate the impacts of LULC on meteorological parameters over the Sichuan Basin (SCB). Further, we conduct Community Multiscale Air Quality (CMAQ) simulations with WRF default LULC and MODIS 2019 to probe the effects on regional air quality. Despite consistency found between meteorological observations and WRF-CMAQ simulations, the default WRF land cover data does not accurately capture rapid urbanization over time compared with MODIS. Modeling results indicate that magnitude changes trigged by LULCC are highly varied across SCB and the impacts of LULCC are more pronounced over extended metropolitan areas due to alteration by urbanization, featured by elevating 2-m temperature up to 2°C and increased planetary boundary layer height (PBLH) up to 400 m. For air quality implications, it is found that LULCC leads to basin-wide O3 enhancements with maximum reaching 21.6 μg/m3 and 57.2 μg/m3 in the daytime and nighttime, respectively, which is mainly attributed to weakening NOx titration effects at night. This work contributes modeling insights into quantitative assessment for impacts of LULCC on regional meteorology and air quality which pinpoints optimization of the meteorology-air quality model.

As the source of the three major rivers of Yangtze River， Yellow River and Lancang River in China， Sanjiangyuan （SJY） and its water vapor source and transportation have an important impact on the weather and climate in the downstream area.According to the summer precipitation data in the Sanjiangyuan area from 1994 to 2019， the precipitation in July showed multiple positive and negative anomaly exchange characteristics.The strongest positive anomaly was in 2012 （+1290 mm）， and the strongest negative anomaly is 2015 （-802 mm）.In this study， the FLEXPART model based on the Lagrangian method was used to simulate this abnormal precipitation period.All the air parcels that reached the source area of the target area during the study period were traced backward， focusing on the analysis of the water vapor transport characteristics and potential source of water vapor of SJY.Besides， the contribution of different water vapor sources to the precipitation of SJY was also evaluated.The results show that the water vapor transmission channels of SJY were mainly divided into the north and the south paths.During the period of positive anomalous precipitation， air parcels mainly transported from the north， west and south of the Qinghai-Xizang Plateau into SJY through the south path.While during the period of negative precipitation anomaly， air parcels mainly transported from the north side of the Qinghai-Xizang Plateau to SJY through the northern path.When the precipitation of SJY was smaller， the southern branch's transport was weaker and the northern path's transport was stronger.Among the potential water vapor sources of SJY， the most important contribution to the precipitation in SJY was on the northern side of the Qinghai-Xizang Plateau， followed by the western side of the Qinghai-Xizang Plateau and the local area， as well as the southern side of the Qinghai-Xizang Plateau， the Arabian Sea and the Bay of Bengal.The contribution of the northern side of the Qinghai-Xizang Plateau to the precipitation of SJY increased during the negative anomaly of precipitation in SJY， while the contribution rate of other water vapor sources decreased.

Mangrove afforestation is considered an important measure in the “natural-based solution” for mitigating climate warming through sequestering massive carbon (C) into vegetation biomass, yet how the planted mangrove species facilitate soil C sequestration remains unclear. Here, we investigated the stock, source, and fraction of soil organic carbon (SOC) over 1 m depth after 20-year afforestation of five mangrove pure plantations (Acrostichum aureum, Acanthus ilicifolius, Aegiceras corniculatum, Kandelia obovate, and Excoecaria agallocha) on Qi’ao Island, South China. The results showed that SOC stocks did not significantly differ among the five plantations, with an average value of 16.7 kg C m−2. Based on the two-end-member mixing model with plant–soil C stable isotope signatures, the autochthonous (mangrove-derived) C source accounted for 20.2–34.1% of SOC but varied significantly among the plantations. The SOC stock in particulate fraction (1.2–2.0 g C kg−1) and mineral-associated fraction (14.3–16.0 g C kg−1) also significantly differed among the plantations. The similar SOC stock but different source contributions and C fractions among the plantations observed here may have important implications for mangrove afforestation to optimize stand structure and maximize C sequestration.

To explore the Characteristics of Land Surface Water-heat Zxchange over Gyaring Lake and Ngoring Lake in Summer， the new generation of mesoscale numerical model WRF（Weather Research and Forecasting Model）， developed by National Centers for Environmental Prediction（NCEP） and National Center for Atmospheric Research （NCAR） was used to simulate the characteristics of atmospheric boundary layer in Gyaring and Ngoring Lakes area.The results show that the WRF model can preferably simulate the diurnal variation characteristics of 2 m height temperature， sensible heat and latent heat flux.Gyaring and Ngoring Lakes have great cooling （heating） effect to the air above lakes during the day （night）， showing obvious cold （warm） lake effect， and producing temperature difference between lakes and land.Such a temperature difference will affect the local wind field.during the day， in the central area of Gyaring and Ngoring Lakes have the strength of 1.0 m·s-1 and 0.5 m·s-1 of downdrafts respectively， and an updraft of 2.5 m·s-1 in intensity appeared over the surrounding area.The effect of Gyaring and Ngoring Lakes on sensible heat and latent heat during the day and night varies greatly.The existence of the two lakes will make the sensible heat and latent heat value of the lake surface lower than the surrounding land during the day， while the effect of the two lakes on sensible heat and latent heat at night is opposite to that of the daytime.For the height of atmospheric boundary layer， the existence of Gyaring and Ngoring Lakes effectively reduces the height of atmospheric boundary layer over the lake area during the day， but the influence of Gyaring and Ngoring Lakes on the height of atmospheric boundary layer is not obvious at night.

The warming climate driven by global change has great potential in altering regional and global hydrologic cycles, thus leading to considerable changes in spatial variability and temporal pattern of precipitation. Northwest China (NW) has witnessed a significant wetting trend over the past decades, while the persistence of this wetting trend and potential changes in precipitation under future climate impacts remains elusive. In this study, long-term meteorological observations were used to probe historical variations of precipitation from 1951 to 2020, and the WRF model was employed as a regional climate model to examine future precipitation patterns over NW. Two 9-year downscaled WRF simulations were conducted comprising of historical (WRF-HIST; 2012–2020) and future climate change scenarios (WRF-SSP585; 2047–2055) using bias-corrected global climate model outputs from Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with ground observations, the WRF model exhibited strong capability in capturing the spatial pattern and temporal variations of precipitation across the NW. Intense precipitation was mainly found in stations located at northern NW and southeastern NW. Summertime precipitation substantially contributed to annual precipitation over the study region. Future precipitation projections suggest significant decreases of precipitation across the southern and eastern NW, with a stronger reduction magnitude in summer. Further, extreme precipitation events were projected to decrease in spring and summer, suggesting that the NW may become drier and the wetting trend may shift to another pattern in the 2050s under the SSP585 climate scenario. Overall, this study reveals historical and future potential changes in precipitation over NW through a high-resolution, dynamically downscaled dataset from WRF modeling, which in turn will help inform regional mitigation and adaption on potential impacts of future climate change on NW.

Abstract Background There is substantial evidence that Eucalyptus for nitrogen (N) absorption and increasing the growth benefit from the introduction of N-fixing species, but the underlying mechanisms for microbially mediated soil N cycling remains unclear. Methods We investigated the changes of soil pH, soil water content (SWC), soil organic carbon (SOC), total N (TN), inorganic N (NH4 +-N and NO3 −-N), microbial biomass and three N-degrading enzyme activities as well as the biomass and N productivity of Eucalyptus between a pure Eucalyptus urophylla × grandis plantation (PP) and a mixed Dalbergia odorifera and Eucalyptus plantation (MP) in Guangxi Zhuang Autonomous Region, China. Results Compared with the PP site, soil pH, SWC, SOC and TN in both seasons were significantly higher at the MP site, which in turn enhanced microbial biomass and the activities of soil N-degrading enzymes. The stimulated microbial activity at the MP site likely accelerate soil N mineralization, providing more available N (NH4 +-N in both seasons and NO3 −-N in the wet-hot season) for Eucalyptus absorption. Overall, the N productivity of Eucalyptus at the MP site was increased by 19.7% and 21.9%, promoting the biomass increases of 15.1% and 19.2% in the dry-cold season and wet-hot season, respectively. Conclusion Our results reveal the importance of microbially mediated soil N cycling in the N absorption on Eucalyptus. Introduction of D. odorifera enhances Eucalyptus biomass and N productivity, improve soil N availability and increased soil C and N concentration, which hence can be considered to be an effective sustainable management option of Eucalyptus plantations.

The alarming increase of ambient ozone (O3) levels across China raises an urgent need in understanding underlying mechanisms of regional O3 events for highly urbanized city clusters. Sichuan Basin (SCB) situated in southwestern China has experienced severe O3 pollution at times in summer from 2013 to 2020. Here, we use the WRF-CMAQ model with the Integrated Source Apportionment Method (ISAM) to investigate the evolution mechanism and conduct source attribution of an extreme O3 episode in the SCB from June 1 to 8, 2019. This typical summer O3 episode is associated with the synoptic-driven meteorological phenomenon and transboundary flow of O3 and precursors across the SCB. Weak ventilation in combination with stagnant conditions triggered the basin-wide high O3 concentrations and enhanced BVOC emissions substantially contribute up to 57.9 μg/m3 MDA8 O3. CMAQ-ISAM indicates that precursor emissions from industrial and transportation have the largest impacts on elevating ambient O3 concentrations, while power plant emissions exhibit insignificant contributions to basin-wide O3 episodes. These results improve the understanding of the summertime O3 episode in the SCB and contribute insights into designing O3 mitigation policy.

The Qinghai–Tibet Plateau (QTP) is a crucial component of the global climate system, influencing the regional and global climate through complex thermal and dynamic mechanisms. The high-altitude region, which is the largest part of the extra-polar cryosphere, encompasses extensive mountain glaciers, permafrost, and seasonally frozen land, making it highly sensitive to global climate change. However, the challenging environmental conditions, such as the harsh terrain and high altitude, coupled with sparse weather station distribution and weak observatory representation, make it difficult to accurately quantify the atmospheric conditions and land–atmosphere coupling systems and their effects on the surrounding areas. To address these challenges, we utilized the Weather Research and Forecasting (WRF) model and a three-dimensional variational (3DVAR) assimilation method to create a high-resolution assimilated dataset (HRAD). The QTP-HRAD, covering the spatial range of 70 to 110°E and 25 to 40°N, was validated using both surface weather station observations and the European Center for Medium-Range Weather Forecasts Reanalysis V5, and can now be utilized for further studies on land–atmosphere interactions, water cycling and radiation energy transfer processes, and extreme weather events in the region.

Abstract This study introduces four rock–soil characteristics factors, that is, Lithology, Rock Structure, Rock Infiltration, and Rock Weathering, which based on the properties of rock formations, to predict Landslide Susceptibility Mapping (LSM) in Three Gorges Reservoir Area from Zigui to Badong. Logistic regression, artificial neural network, support vector machine is used in LSM modeling. The study consists of three main steps. In the first step, these four factors are combined with the 11 basic factors to form different factor combinations. The second step randomly selects training (70% of the total) and validation (30%) datasets out of grid cells corresponding to landslide and non-landslide locations in the study area. The final step constructs the LSM models to obtain different landslide susceptibility index maps and landslide susceptibility zoning maps. The specific category precision, receiver operating characteristic curve, and 5 other statistical evaluation methods are used for quantitative evaluations. The evaluation results show that, in most cases, the result based on Rock Structure are better than the result obtained by traditional method based on Lithology, have the best performance. To further study the influence of rock–soil characteristic factors on the LSM, these four factors are divided into “Intrinsic attribute factors” and “External participation factors” in accordance with the participation of external factors, to generate the LSMs. The evaluation results show that the result based on Intrinsic attribute factors are better than the result based on External participation factors, indicating the significance of Intrinsic attribute factors in LSM. The method proposed in this study can effectively improve the scientificity, accuracy, and validity of LSM.

Biogenic volatile organic compounds (BVOCs) impact atmospheric oxidation capacity and regional air quality through various biogeochemistry processes. Accurate estimation of BVOC emissions is crucial for modeling the fate and transport of air pollutants in chemical transport models. Previous modeling characterizes the spatial variability of BVOCs while estimated BVOC emissions show large uncertainties, and the impacts of BVOC emissions on ozone (O3) air quality are not well understood. In this study, we estimate the BVOC emissions by model of emissions of gases and aerosols from nature (MEGAN) v2.1 and MEGAN v3.1 over the Sichuan Basin (SCB) situated in southwestern China for 2017. Further, the critical role of BVOC emissions on regional O3 pollution is illustrated with a CMAQ modeled O3 episode in summer 2017. Annual BVOC emissions over the SCB in 2017 are estimated to be 1.8 × 106 tons with isoprene emissions as high as 7.3 × 105 tons. Abundant BVOC emissions are depicted over the southern and southeastern SCB, in contrast to the relatively low emissions of BVOC over the Chengdu Plain and northeastern SCB. CMAQ simulations depict a strong influence of BVOC on ambient O3 formation over densely forested regions including southern SCB and Chongqing city, accounting for 10% of daily maximum hourly O3 concentration (DM1h O3) and 6% of daily maximum 8-h average O3 (MDA8h O3) concentrations in July 2017. Over the severe O3 episode in summer 2017, sensitivity experiments indicate that enhanced BVOC emissions contribute substantially to basin-wide O3 concentrations and elevate peak O3 levels by 36.5 and 31.2 μg/m3 for the southern SCB and Chengdu Plain, respectively. This work identifies robustly important effects of BVOC emissions on O3 exceedance events over the SCB and contributes insight into pursuing an O3 abatement strategy with full consideration of potential contributions from BVOC emissions.

Abstract Background The mixing of Eucalyptus with N2-fixing trees species (NFTs) is a frequently successful and sustainable cropping practice. In this study, we evaluated nitrogen (N) transfer and conducted a proteomic analysis of the seedlings of Eucalyptus urophylla × E. grandis (Eucalyptus) and an NFT, Dalbergia (D.) odorifera, from intercropping and monocropping systems to elucidate the physiological effects and molecular mechanisms of N transfer in mixed Eucalyptus and D. odorifera systems. Results N transfer occurred from D. odorifera to Eucalyptus at a rate of 14.61% in the intercropping system, which increased N uptake and growth in Eucalyptus but inhibited growth in D. odorifera. There were 285 and 288 differentially expressed proteins by greater than 1.5-fold in Eucalyptus and D. odorifera roots with intercropping vs monoculture, respectively. Introduction of D. odorifera increased the stress resistance ability of Eucalyptus, while D. odorifera stress resistance was increased by increasing levels of jasmonic acid (JA). Additionally, the differentially expressed proteins of N metabolism, such as glutamine synthetase nodule isozyme (GS), were upregulated to enhance N competition in Eucalyptus. Importantly, more proteins were involved in synthetic pathways than in metabolic pathways in Eucalyptus because of the benefit of N transfer, and the two groups of N compound transporters were found in Eucalyptus; however, more functional proteins were involved in metabolic degradation in D. odorifera; specifically, the molecular mechanism of the transfer of N from D. odorifera to Eucalyptus was explained by proteomics. Conclusions Our study suggests that N transfer occurred from D. odorifera to Eucalyptus and was affected by the variations in the differentially expressed proteins. We anticipate that these results can be verified in field experiments for the sustainable development of Eucalyptus plantations.

The developed karst caves may become the seepage channels of heavy metal to the soil and underground water in Southwest China. Therefore, it is necessary to apply effective seepage treatments to the base of heavy metal tailing reservoirs. This paper addressed the high-pressure rotary jet technology and slurry systems used in the seepage treatment of the deep tailing sand of the Shenxiandong tailing pond located in Southwest China. In this study, the factors of fluidity, initial and final setting times, compressive strength, and permeability coefficient of the slurry were conducted. The mechanism analysis was investigated by X-ray diffraction (XRD), scanning electron microscope (SEM), and inductively coupled plasma-mass spectrometry (ICP-MS). Three different types of slurry systems were proposed, and the permeability coefficients of the solidification body following 28 days of curing were less than 1 × 10−7 cm/s. The concentrations of Pb and Zn in the slurry system containing bentonite were reduced by 26.2% and 45.7%, respectively. In the presence of slaked lime and fly ash, the concentrations of Pb and Zn could be reduced by 26.8% and 30%, respectively. A total of 2142 high-pressure rotary jet piles were completed by the high-pressure rotary jet method in the field trial. The diffusion radius of these piles was over 1 m. Following 28 days of curing, the solidification body’s compressive strength was 7.45 MPa and the permeability coefficient was 6.27 × 10−8 cm/s. Both the laboratory and on-site trials showed that this method produced a good pollution barrier effect, which could prevent the diffusion of heavy metal into the adjacent underground water through the karst caves. It is also an effective way of engineering technology concerning heavy metal pollution control that occurs in tailing ponds.

As a unique climate phenomenon induced by the Tibetan Plateau (TP) heat flux, the TP monsoon is closely connected with the global climate, especially pertaining to the TP. However, the current research focuses more on the influence of the TP monsoon on the TP and eastern China, but not including Central Asia. This paper analyzed the relationship between the TP monsoon index and Central Asia summer precipitation by JRA55 reanalysis data and Global Precipitation Climatology Centre (GPCC) monthly precipitation. The results showed a significant positive relationship between the TP monsoon index and summer precipitation in Central Asia. When the TP monsoon was strong, there was cold advection in the upper troposphere over Central Asia, and the resulting thermal wind caused a cyclonic circulation anomaly in the mid-upper troposphere over Central Asia. This in turn led to a cyclonic circulation anomaly to water vapor transport in the lower troposphere. The abnormal upward movement also caused more precipitation in this area, which explains the positive correlation between the TP monsoon and the precipitation in Central Asia. Based on this physical mechanism, the temperature of the mid-upper troposphere over Central Asia was closely related to the TP monsoon, and it was a key factor that affected summer precipitation changes in Central Asia.

Based on the field observation and WRF-CLM model, the effects of Gyaring and Ngoring lakes on the short-term climate over the Yellow River source area during May to September have been studied through two experiments with and without the lakes. A backward water vapor transfer model was also employed to investigate the contribution of water vapor evapotranspiration from the Gyaring and Ngoring lakes and various surface types to the local precipitation. The results show that without the Gyaring and Ngoring lakes, the sensible heat is increased by 120%, whereas the latent heat is decreased by 58.5%, and the height of atmospheric boundary layer increases from 500 to 1,500–2,000 m during daytime over the lake area. The sum of sensible and latent heat fluxes in the lake area simulated by the experiment with and without the lakes is 185.8 and 130.3 W m−2, respectively. The precipitation amount over the lake area is significantly increased without considering the lake effect, generally by more than 20–40 mm. About 63.8% of the total precipitation in Gyaring and Ngoring lakes is contributed by the external water vapor sources. The evapotranspiration from the grassland is the secondary water vapor source for the precipitation in the Yellow River source area, and 25.2% of the total precipitation is contributed by this source. Around 4.2% of the total precipitation in the lake area is contributed by the evaporation from the Gyaring and Ngoring lakes.

The mining industry production is an important pillar industry in China, while its extensive production activities have led to several ecological and environmental problems. Earth observation technology using high-resolution satellite imagery can help us efficiently obtain information on surface elements, surveying and monitoring various land occupation issues arising from open-pit mining production activities. Conventional pixel-based interpretation methods for high-resolution remote sensing images are restricted by “salt and pepper” noise caused by environmental factors, making it difficult to meet increasing requirements for monitoring accuracy. With the Jingxiang phosphorus mining area in Jingmen Hubei Province as the studied area, this paper uses a multi-scale segmentation algorithm to extract large-scale main characteristic information using a layered mask method based on the hierarchical structure of the image object. The remaining characteristic elements were classified and extracted in combination with the random forest model and characteristic factors to obtain land occupation information related mining industry production, which was compared with the results of the Classification and Regression Tree model. 23 characteristic factors in three aspects were selected, including spectral, geometric and texture characteristics. The methods employed in this study achieved 86% and 0.78 respectively in overall extraction accuracy analysis and the Kappa coefficient analysis, compared to 79% and 0.68 using the conventional method.

Pioneer species are crucial for the ecological restoration of degraded forests, but what drives variation in their demographic performance is still unclear. Here, we studied three populations of the dominant tree, Pinus massoniana, corresponding to three levels (low, medium, high) of ecological restoration of secondary subtropical forests. Vital rates (growth, survival, and reproduction) were censused during 2019–2020, and integral projection models (IPMs) were parameterized to evaluate the population growth rate (λ) of P. massoniana. The results showed that the survival probability of large-sized individuals, stem growth, and λ of P. massoniana increased as the ecological restoration progressed. In contrast, the survival rate of seedlings declined substantially. The reproduction probability of small individuals was more likely at low than medium/high restoration levels. Elasticity analysis showed that survival contributes most to λ and fecundity the least. λ was primarily determined by the high survival of seedlings/small trees and large trees in the low- and high-restoration level populations, respectively. Life table response experiments showed that increases in survival were mostly responsible for augmented λ during ecological restoration; hence, the high-restoration population had the highest λ due to a higher survival rate. This work shows P. massoniana is capable of undergoing life-history strategy shifts. Its high recruitment and survival of small individuals make it a suitable species for restoring forests, whereby large-sized individuals eventually maintain populations at low risk of mortality.

As a dominant and active component across ecological restoration processes, the population dynamics of pioneer tree species significantly affect species composition and community assemblage. To assess the effect of pioneer populations on species diversity, this study investigated species diversity and population characteristics in five secondary forests dominated by Pinus massoniana in southeastern China. For 40 years, all anthropogenic activities (e.g., logging, farming, etc.) have been banned on the hillsides of these five secondary forests to promote afforestation, for which these forests have thereafter been left to grow naturally. We found that: (1) the basal area (BA) of P. massoniana drove changes in species diversity across forest plots, explaining 31.6% of total variation. The species richness of the herb layer was negatively correlated to BA, while the diversity and evenness of the tree and shrub layers were both positively correlated to the BA. (2) As the size of individual P. massoniana specimens increased, the trend in species richness of the shrub layer and the diversity indexes of both the tree and shrub layer was first to increase and then to decrease once again, while the species richness of the tree layer stabilized after reaching a certain threshold. (3) Species diversity of the forest plots did not improve over time along with an increase in the density of the pioneer species. When the P. massoniana population density was low, the diversity indexes of both the tree and shrub layer increased with an increase in population density. Conversely, when the P. massoniana population density reached 2800 plants/ha, species diversity began to decline. However, when the P. massoniana population density increased to 3733 plants/ha, species diversity of the plant community exhibited an upward trend. Our results indicated that forest species diversity was extremely sensitive to P. massoniana population dynamics during the pioneer stage of ecological succession. Moreover, the pioneer population was the driving factor for both development and change in species diversity, and it did so through habitat adjustment of its ecological relationships.

Cloud microphysical processes significantly impact the time variation and intensity of precipitation. However, due to the high altitude of the Tibetan Plateau (TP) and the lack of observational data, the understanding of cloud microphysical processes on the TP is relatively insufficient, affecting the accuracy of precipitation simulations around the TP. To further reveal the characteristics of convective precipitation and cloud microphysical structure over the TP, the mesoscale numerical model, WRF, and various observational data were used to simulate and evaluate typical convective precipitation in the Yushu area, which was recorded from 11 to 12 August 2020. The results showed that the combination of the Lin scheme in the WRF model could effectively reproduce this case’s characteristics and evolution process. In the simulation process, the particles of each phase were distributed at different altitudes, and their mass and density over time reflected the characteristics of surface precipitation changes. Among the particles mentioned above, rainwater contributed the most to the initiation and growth of graupel particles. Further research established that the initiation of graupel was mainly affected by the freezing effect of rainwater and cloud ice, while the growth of graupel was influenced primarily by the collision of graupel particles and rainwater. On the whole, from the evolution characteristics of microphysical processes over time, it was found that the ice phase process plays an essential role in this typical convective precipitation.

In August-September 2021, the western Pacific subtropical high (WPSH) showed significant anomalies, with some areas between the Yangtze and Yellow River basins in China suffering from heavy rainfall and flooding, while extreme heat occurred in Southern China. Using the 6 h reanalysis data of NCEP/NCAR and the daily precipitation observation data, this paper studied the abnormal characteristics and the thermal mechanism of the three-dimensional ridge of the WPSH during the seasonal transition from late summer to early autumn in August-September 2021, and explored its connection with the precipitation in the areas between the Yangtze and Yellow River basins in China during the same period. The results showed that, in August-September 2021, the three-dimensional ridge of the WPSH appeared to be southward at the lower troposphere and tilted northward with height. According to the diagnosis of the atmospheric heat source, it was found that the center of atmospheric cold source in the low latitudes at 850 hPa enhanced the surface high pressure, corresponding to the WPSH ridge shifting southward at the lower troposphere, which led to more water vapor convergence and more precipitation between the Yangtze and Yellow River basins. The latent heat of condensation released by the increased precipitation between the Yangtze and Yellow River basins in China heated the middle and upper troposphere, increasing the intensity of the high pressure in the upper troposphere, corresponding to the WPSH ridge northward at the upper troposphere. This anomalous tilt of the WPSH ridge in August-September 2021 and the intense precipitation processes between the Yangtze and Yellow River basins in China during the same period established a reciprocal feedback mechanism through diabatic heating. Further studies also showed that the anomalous tilt of the WPSH ridge is one of the important modes of its three-dimensional structural anomalies, and that, in years when the ridge tilts from south to north with height anomalously in August-September, the areas between the Yangtze and Yellow River basins are characterized by high precipitation.

To better predict and understand land–atmospheric interactions in the Tibetan Plateau (TP), we used Moderate Resolution Imaging Spectroradiometer (MODIS)-based land-use data and the MODIS-derived green vegetation fraction (GVF) to analyze the variation trend over the TP. The in situ observations from six flux stations (“BJ” (the BJ site of Nagqu Station of Plateau Climate and Environment), “MAWORS” (the Muztagh Ata Westerly Observation and Research Station), “NADORS” (the Ngari Desert Observation and Research Station), “NAMORS” (the Nam Co Monitoring and Research Station for Multisphere Interactions), “QOMS” (the Qomolangma Atmospheric and Environmental Observation and Research Station), and “SETORS” (the Southeast Tibet Observation and Research Station for the Alpine Environment)) at the Chinese TP Scientific Data Center were used to study the surface energy variation characteristics and energy distribution over different underlying surfaces. Finally, we used observation data to verify the applicability of the ERA-5 land reanalysis data to the TP. The results showed that the annual GVF steadily declined from the southeast parts to the northwest parts of the TP, and the vegetation coverage rate was highest from June to September. The sensible heat flux (H), latent heat flux (LE), net surface radiation (Rn), and four-component radiation (solar downward shortwave radiation (Rsd), surface upward shortwave radiation (Rsu), atmospheric downward longwave radiation (Rld), and surface upward longwave radiation (Rlu)) reached their maxima in summer at each station. Rld did not change significantly with time; all other variables increased during the day and decreased at night. The interannual variation in H and LE shows that latent heat exchange was the dominant form of energy transfer in BJ, MAWORS, NAMORS, and SETORS. By contrast, sensible heat exchange was the main form of energy transfer in NADORS and QOMS. The Bowen ratio was generally low in summer, and some sites had a maximum in spring. The surface albedo exhibited a “U” shape, decreasing in spring and summer, and increasing in autumn and winter, and reaching the lowest value at noon. Except for SETORS, ERA-5 Land data and other flux stations had high simulation accuracy and correlation. Regional surface energy changes were mainly observed in the eastern and western parts of the TP, except for the maximum of H in spring; the maximum values of other heat fluxes were concentrated in summer.

The diurnal variation in precipitation and cloud parameters and their influencing factors during summer over the Tibetan Plateau (TP) and Sichuan Basin (SB) were investigated using the Hydro-Estimator satellite rainfall estimates, ground observations, and ERA5 dataset. The precipitation and cloud parameters show diurnal propagation over the SB during the mei-yu period in contrast to such parameters over the TP. The diurnal maximum precipitation from the Hydro-Estimator satellite and cloud ice and liquid water content (cloud LWC and IWC) from the ERA5 dataset are concentrated in the early evening, while their diurnal minimums manifest in the morning. Cloud LWC accounts for more than 60% of the total water during almost the entire diurnal cycle over the inner TP and SB during the mei-yu period. The IWC accounts for more than 60% of the total water in the late afternoon over the edge of the SB and TP. The cloud base height (CBH) above ground level (AGL), the lifting condensation level (LCL) AGL, and the zero degree level AGL are almost equal over the TP during the summer period. The zero degree level AGL over the SB is higher than that over the TP because the air temperature lapse rate over the TP is larger. The thickness of liquid water cloud over the SB is larger than that over the TP. The correlation analysis shows that the CBH AGL and LCL AGL over the TP are related to the dewpoint spread, but less so over the SB because of the stronger turbulence and lower air density over the TP than the SB. Convective available potential energy has a larger impact on precipitation over the TP than the SB. The cloud LWC makes a larger contribution to the precipitation over the SB than over the TP, which is related to the mean zonal wind and diurnal cycle of low-level winds. The precipitation at the edge of the TP and SB (i.e., the steep downstream slope) is largely influenced by the ice water contained within clouds owing to the convergence rising motion over the slopes.

Plant leaf nutrient concentrations and resorption are sensitive to fertilization, yet their co-responses under different nutrient-limited conditions have not been well studied. We conducted a meta-analysis from a global dataset of 43 reports, including 130 observations of studies with plant leaf nitrogen (N) or phosphorus (P) concentrations and nitrogen resorption efficiency (NRE) or phosphorus resorption efficiency (PRE), in response to fertilization under different nutrient-limited conditions divided by the thresholds of leaf N:P ratio values of 10 and 20. The results showed that N fertilization generally increased leaf N concentration and decreased NRE, with greater magnitudes under N-limited conditions. P fertilization also generally increased leaf P concentration and decreased PRE, with greater magnitudes under P-limited conditions. N fertilization decreased leaf P concentration and increased PRE only under the N-limited condition. Under the P-limited or N and P co-limited conditions, however, N fertilization increased leaf P concentration and did not change PRE. Moreover, P fertilization did not change leaf N concentration under all nutrient-limited conditions but significantly increased NRE under the N-limited or N and P co-limited conditions. These findings suggest that plants cope with fertilization-induced N limitation vs. P limitation at the leaf level with different nutrient-use strategies.

China experiences frequent landslides, and therefore there is a need for landslide susceptibility maps (LSMs) to effectively analyze and predict regional landslides. However, the traditional methods of producing an LSM are unable to account for different spatial scales, resulting in spatial imbalances. In this study, Zigui-Badong in the Three Gorges Reservoir Area was used as a case study, and data was obtained from remote sensing images, digital elevation model, geological and topographic maps, and landslide surveys. A geographic weighted regression (GWR) was applied to segment the study area into different spatial scales, with three basic principles followed when the GWR model was applied for this propose. As a result, 58 environmental factors were extracted, and 18 factors were selected as LSM factors. Three of the most important factors (channel network basic level, elevation, and distance to river) were used as segmentation factors to segment the study area into 18 prediction regions. The particle swarm optimization (PSO) algorithm was used to optimize the parameters of a support vector machine (SVM) model for each prediction region. All of the prediction regions were merged to construct a GWR-PSO-SVM coupled model and finally, an LSM of the study area was produced. To verify the effectiveness of the proposed method, the outcomes of the GWR-PSO-SVM coupled model and the PSO-SVM coupled model were compared using three evaluation methods: specific category accuracy analysis, overall prediction accuracy analysis, and area under the curve analysis. The results for the GWR-PSO-SVM coupled model for these three evaluation methods were 85.75%, 87.86%, and 0.965, respectively, while the results for the traditional PSO-SVM coupled model were 68.35%, 84.44%, and 0.944, respectively. The method proposed in this study based on a spatial scale segmentation therefore acquired good results.

Ostrya rehderiana is a famous plant species with extremely small populations. With ongoing global climate change, the extremely small populations would face more uncertainties and risks, including the loss of genetic diversity and extirpation. Thus, assessing the impact of climate change on suitable habitat of O. rehderiana is particularly important for its conservation and restoration. Here, we built niche models with climate variables and soil and human footprint variables. Furthermore, new methods were applied to avoid confounding effects between climate and soil and human footprint variables to simulate the potential habitats of O. rehderiana in current and future climates. We found that the Hargreaves climatic moisture deficit, degree-days below 0 °C, chilling degree-days, and the temperature difference between mean warmest month temperature and mean coldest month temperature, or continentality, were the most important climate factors. The topsoil USDA texture classification, topsoil cation exchange capacity of (clay), and topsoil sodicity (ESP) were the key soil factors determining the suitable distribution of O. rehderiana. Compared with soil factors, human footprint has less influence on the suitable distribution of O. rehderiana. The niche range of this species was projected to expand and shift to north in the Representative Concentration Pathway (RCP) 4.5 scenario for the 2050s. Our study results could be referenced in further extremely small populations ecological restoration studies and provide the scientific strategies for the conservation and restoration of O. rehderiana.

Although combustion is considered a common source of ammonia (NH3) in the atmosphere, field measurements quantifying such emissions of NH3 are still lacking. In this study, online measurements of NH3 were performed by a cavity ring-down spectrometer, in the cold season at a rural site in Xianghe on the North China Plain. We found that the NH3 concentrations were mostly below 65 ppb during the study period. However, from 18 to 21 November 2017, a close burn event (~100 m) increased the NH3 concentrations to 145.6 ± 139.9 ppb. Using a machine-learning technique, we quantified that this burn event caused a significant increase in NH3 concentrations by 411%, compared with the scenario without the burn event. In addition, the ratio of ∆NH3/∆CO during the burn period was 0.016, which fell in the range of biomass burning. Future investigations are needed to evaluate the impacts of the NH3 combustion sources on air quality, ecosystems, and climate in the context of increasing burn events worldwide.

N2-fixing species play a crucial role in mixed-plantations as they improve stand productivity. To quantify the N transfer from N2-fixing species to Eucalyptus (Eucalyptus urophylla × E. grandis) in N2-fixing species/Eucalyptus plantations, we established a pot experiment and confirmed the occurrence of this process under natural conditions. The 15N was traced in labeled species as well as in neighboring tree species after labeling, and the growth was evaluated in short-term natural trials. Our results showed that a bidirectional N transfer occurred. The amount of net N transfer was 21.8–127.0 mg N plant−1, which was equal to 1.5–21.2% of the total nitrogen (TN) that accumulated in Eucalyptus plants under pot conditions, was transferred from Dalbergia odorifera to Eucalyptus. The amount of N transferred significantly decreased with the increasing N application rate but increased with time after labeling. Compared with the results for the Eucalyptus monocrop, the soil N concentration (including NO3−-N and NH4+-N) greatly improved when D. odorifera was introduced together with Eucalyptus under both field and pot conditions. Furthermore, the results under field conditions were consistent with the results of the pot experiment. The dry matter (DM) yield (14.5–16.4%) and the N content (5.1–9.6%) in Eucalyptus increased when mixed together with D. odorifera, but the N content in and DM yield of D. odorifera slightly decreased. It is concluded that the N transfer between Eucalyptus and D. odorifera is a much more important dynamic process than previously recognized, and Eucalyptus and legume intercropping is a successful management practice because N transfer provides a significant amount of N required for Eucalyptus productivity.

Co-gasification of biomass (rice straw) and polyethylene (PE) was conducted in a lab-scale entrained-flow gasifier. The influences of PE proportion, reaction temperature, and equivalence ratio on producer gas composition, gasification index, and tar yield were investigated. In addition, the effects of dolomite and sodium carbonate (Na2CO3) catalysts on the co-gasification process were also examined. Increased PE proportion led to an increased lower heating value (LHV) of producer gas as well as an increase in tar yield. In addition, a higher reaction temperature could improve both gas quality and gasification indices significantly. An equivalence ratio (ER) of 0.25 led to a relatively high LHV and low tar yield. Na2CO3 showed a better tar removal efficiency than dolomite. Dolomite increased the LHV of producer gas, while Na2CO3 decreased the LHV. The difference in the catalyst proportion did not cause any significant change in the gas composition and gasification indices. The producer gas with the highest LHV and lowest tar yield was obtained by the co-gasification of 80% (w/w) straw, 20% (w/w) PE, and 3% (w/w) dolomite.

Co-exploitation of coal measure gases (coalbed gas, shale gas, and tight sandstone gas) puts a higher requirement on drilling fluids. Conventional drilling fluids have disadvantages, such as causing problems of borehole collapse, formation damage, and water blockage. This paper proposes a set of high inhibitive and low-damage drilling fluids that function by electrical inhibition and neutral wetting. Zeta potential results showed that the negative electrical property of Longtan coal in Bijie, Guizhou, can be reversed by organic mixed metal hydroxide (MMH) and the cationic surfactant alkyl trimethylammonium bromide (CS-5) from −3.63 mV to 19.75 mV and 47.25 mV, respectively. Based on the contact angle and Fourier Transform Infrared Spectroscopy (FT-IR) results, it can be concluded that chemical adsorption dominates between the Longmaxi shale and surfactants, and physical adsorption between the Longtan coal and surfactants. A compound surfactant formula (0.001 wt% CS-4 + 0.001 wt% CS-1 + 0.001 wt% CS-3), which could balance the wettability of the Longmaxi shale and the Longtan coal, making them both appear weakly hydrophilic simultaneously, was optimized. After being treated by the compound surfactants, the contact angles of the Longmaxi shale and the Longtan coal were 89° and 86°, respectively. Pressure transmission tests showed that the optimized combination of compound surfactants and inorganic MMH (MMH-1) could effectively reduce permeability of the Longmaxi shale and the Longtan coal, thus retarding pore pressure transmission in coal measure strata. Then, the proposed water-based drilling fluid (WBDF) system (4 wt% sodium bentonite + 1.5 wt% sodium carboxymethyl cellulose + 2 wt% lignite resin + 5 wt% potassium chloride + 3 wt%MMH-1 + 0.001 wt% CS-4 + 0.001 wt% CS-1 + 0.001 wt% CS-3) was evaluated based on parameters including rheology, American Petroleum Institute (API) filtration, electrical property, wettability, inhibition capability, reservoir protection characteristics, and anti-pollution performance. It had an API filtration of 7 mL, reservoir damage rate of 10%, moderate and acceptable viscosity, strong inhibition capability to coal measure strata rocks, good tolerance to inorganic pollutants and drilling cuttings, and environmentally friendly properties. It could meet wellbore stability and reservoir protection requirements in the co-exploitation of coal measure gases.

The past decade has seen increased focus on nanoparticle (NP) based drilling fluid to promote wellbore stability in shales. With the plugging of NP into shale pores, the fluid pressure transmission can be retarded and wellbore stability can be improved. For better understanding of the interaction between shale and NP based drilling fluid based on previous pressure transmission tests (PTTs) on Atoka shale samples, this paper reports the numerical simulation findings of wellbore stability in the presence of NP based drilling fluid, using the 2D fluid-solid coupling model in FLAC3D™ software. The results of previous PTT are discussed first, where the steps of numerical simulation, the simulation on pore fluid pressure transmission, the distribution of stress and the deformation of surrounding rock are presented. The mechanisms of NP in reducing permeability and stabilizing shale are also discussed. Results showed that fluid filtrate from water-based drilling fluid had a strong tendency to invade the shale matrix and increase the likelihood of wellbore instability in shales. However, the pore fluid pressure near wellbore areas could be minimized by plugging silica NP into the nanoscale pores of shales, which is consistent with previous PTT. Pore pressure transmission boundaries could also be restricted with silica NP. Furthermore, the stress differential and shear stress of surrounding rock near the wellbore was reduced in the presence of NP. The plastic yield zone was minimized to improve wellbore stability. The plugging mechanism of NP may be attributed to the electrostatic and electrodynamic interactions between NP and shale surfaces that are governed by Derjaguin-Landau-Verwey-Overbeek (DLVO) forces, which allowed NP to approach shale surfaces and adhere to them. We also found that discretization of the simulation model was beneficial in distinguishing the yield zone distribution of the surrounding rock in shales. The combination of PTT and the 2D numerical simulation offers a better understanding of how NP-based drilling fluid can be developed to address wellbore stability issues in shales.

Filtering is one of the core post-processing steps for airborne LiDAR point cloud. In recent years, the morphology-based filtering algorithms have proven to be a powerful and efficient tool for filtering airborne LiDAR point cloud. However, most traditional morphology-based algorithms have difficulties in preserving abrupt terrain features, especially when using larger filtering windows. In order to suppress the omission error caused by protruding terrain features, this paper proposes an improved morphological algorithm based on multi-level kriging interpolation. This algorithm is essentially a combination of progressive morphological filtering algorithm and multi-level interpolation filtering algorithm. The morphological opening operation is performed with filtering window gradually downsizing, while kriging interpolation is conducted at different levels according to the different filtering windows. This process is iterative in a top to down fashion until the filtering window is no longer greater than the preset minimum filtering window. Fifteen samples provided by the ISPRS commission were chosen to test the performance of the proposed algorithm. Experimental results show that the proposed method can achieve promising results not only in flat urban areas but also in rural areas. Comparing with other eight classical filtering methods, the proposed method obtained the lowest omission error, and preserved protruding terrain features better.

Objective: This study aimed to explore the mediating roles of mindfulness and illness perception in the effects of a social media-based Mindfulness psyCho-behAvioRal intErvention (MCARE) on depressive and anxiety symptoms among patients with ACS., Methods: This study conducted a secondary longitudinal mediation analysis using data from a randomized controlled trial of the MCARE grogram in patients with ACS. Participants were recruited at two tertiary hospitals in Jinan, China. The MCARE program consisted of six weekly sessions addressing mindfulness training and disease management to facilitate understanding and management of emotions and illness. The analytical sample included participants who completed measures of the primary outcomes, i.e., depression (PHQ-9) and anxiety (GAD-7) and potential mediators, i.e., mindfulness (CAMS-R) and illness perception (Brief-IPQ) at baseline (T0), immediate post-intervention (T1), and 12-week after the commencement of the intervention (T2)., Results: This study included 146 participants (mean age 58.9 years (SD = 8.9), 69.2 % male), including both intervention and control groups. The mediation analysis revealed a significant mediating effect of T1 mindfulness in the relationship between the group and T2 depression symptoms (indirect effect: -0.109, 95 % CI: -0.191, -0.041; P = 0.004), accounting for 26 % of the effect. For T2 anxiety symptoms, T1 illness perception exhibited a significant mediating effect (indirect effect: -0.055, 95 % CI: -0.110, -0.005; P = 0.035), accounting for 22 % of the effect., Conclusions: This study found that mindfulness and illness perception played a mediating role in the effects of the MCARE program on depressive and anxiety symptoms among patients with ACS., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2024. Published by Elsevier Inc.)

The traditional lateral flow immunoassay (LFIA) with a single signal output mode may encounter challenges such as low sensitivity, poor detection range, and susceptibility to external interferences. These limitations hinder its ability to meet the growing demand for advanced LFIA. To address these issues, the rational development of multifunctional labels for multimodal LFIA emerges as a promising strategy. Herein, this study reports a multimodal LFIA using "four-in-one" multifunctional dandelion-like gold@platinum nanoparticles (MDGP). The inherent properties of MDGP, such as the broad absorption spectrum, porous dandelion-like nanostructure, and bimetallic composition with gold and platinum, endow them with capacities in dual spectral-overlapped fluorescence quenching, optical readout, catalytic activity, and photothermal effect. Benefiting from their multifunctional properties, the MDGP-LFIA enables multimodal outputs including fluorescent, colorimetric, and photothermal signals. This multimodal MDGP-LFIA allows for the detection of acetamiprid at a range of 0.01-50 ng mL -1 , with the lowest qualitative and quantitative detection results of 0.5 and 0.008 ng mL -1 , respectively, significantly better than the traditional gold nanoparticles-based LFIA. The diversity, complementarity, and synergistic effect of integrated output signals in this multimodal MDGP-LFIA improve the flexibility, practicability, and accuracy of detection, holding great promise as a point-of-care testing platform in versatile application scenarios., (© 2024 Wiley‐VCH GmbH.)

Argonaute (Ago) as a powerful enzyme has provided new insights into biosensing due to its programmability, high sensitivity, and user-friendly operation. However, current strategies mainly rely on phosphorylated guide DNA to modulate the cleavage activity of Ago, which is limited in versatility and simplicity. Herein, the authors report the Mn 2+ -enhanced cleavage activity of Ago and employ Mn-ions with variable valence to regulate the activity of Pyrococcus furiosus Ago (PfAgo) for biosensing applications. The conversion of Mn ions with different valence states through MnO 2 nanoflowers enables the sensitive detection of ascorbic acid, alkaline phosphatase, and arsenic with limits of detection of 2.5 nmol L -1 , 0.009 U L -1 , and 0.4 ng mL -1 , respectively. A PfAgo-based immunoassay is further developed that allows for the detection of diverse targets, thus providing a promising toolbox to broaden PfAgo-based sensors into versatile bioanalytical and biomedical applications., (© 2024 Wiley‐VCH GmbH.)

DNA has emerged as a promising tool to build logic gates for biocomputing. However, prevailing methodologies predominantly rely on hybridization reactions or structural alterations to construct DNA logic gates, which are limited in simplicity and diversity. Herein, we developed simple and smart DNA-based logic gates for biocomputing through the DNA-mediated growth of gold nanomaterials without precise structure design and probe modification. Capitalizing on their excellent plasmonic properties, the surface growth of gold nanomaterials enables distinct wavelength shifts and unique shapes, which are modulated by the composition, length, and concentration of the DNA sequences. Combined with a CRISPR-mediated reaction, we constructed DNA circuits to achieve complicated biocomputing to modulate the surface growth of gold nanomaterials. By implementing logic functions controlled by input-mediated growth of gold nanomaterials, we established YES/NOT, AND/NAND, OR/NOR, XOR, and INHIBIT gates and further constructed cascade logic circuits, parity checker for natural numbers, and gray code encoder, which are promising for DNA biocomputing.