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Yan Lin,1,2,* Gaofeng Zhu,3,* Xiaoyong Li,4,* Huaxiao Yu,5 Yuhang Luo,5 Jiaqiong Lin,6 Renyuan Li,7 Zena Huang2 1Department of Nephrology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China; 2Yunkang School of Medicine and Health, Nanfang College, Guangzhou, People’s Republic of China; 3Department of General Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, People’s Republic of China; 4Department of General Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China; 5The Third Clinical School, Guangzhou Medical University, Guangzhou, People’s Republic of China; 6Affiliated Dongguan Maternal and Child Healthcare Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 7Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zena Huang, Yunkang School of Medicine and Health, Nanfang College, Guangzhou, People’s Republic of China, Tel +86-13570466614, Email huangzn@nfu.edu.cn Renyuan Li, Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China, Tel +86-18926146852, Email lirenyuan@gzhmu.edu.cnBackground: Icariin presents protective effect in several kidney diseases. However, the role of icariin in contrast-induced acute kidney injury (CIAKI) is still unclear. This study aimed to investigate the effect of icariin in CIAKI, as well as exploring the underlying mechanism from the aspect of interaction between protein-coding genes and non-coding RNAs.Methods: The effect of icariin was evaluated in both in vivo and in vitro CIAKI models. Rat kidneys were collected for genome-wide sequencing. The differentially expressed genes (DEGs) were screened and visualized by R software. The function annotation of DEGs was analyzed by Metascape. By Cytoscape software, the competing endogenous RNA (ceRNA) network was constructed, and hub genes were selected. Expressions of hub genes were validated by PCR. Association of hub genes in the ceRNA network and renal function was also examined.Results: Icariin protected against CIAKI in both in vivo and in vitro models. Based on DEGs in icariin pretreated CIAKI rats, lncRNA- and circRNA-associated ceRNA networks were constructed, respectively. Function annotation showed the ceRNA networks were enriched in ERK1 and ERK2 cascade, MAPK signaling and NF-κB signaling. Further, two circRNAs, six lncRNAs, four miRNAs and nine mRNAs were selected as hub genes of the ceRNA network. Among them, eight mRNAs (Acot1, Cbwd1, Ly6i, Map3k14, Mettl2b, Nyap1, Set and Utp20) were negatively correlated with renal function, while one mRNA (Tmem44) was positively correlated with renal function.Conclusion: Icariin presented a protective effect against CIAKI. The ceRNA network, involving Acot1, Cbwd1, Ly6i, Map3k14, Mettl2, Nyap1, Set, Tmem44 and Utp20, might partially contribute to the underlying mechanism of icariin protection by regulation of ERK1 and ERK2 cascade, MAPK signaling and NF-κB signaling.Keywords: icariin, contrast medium, acute kidney injury, competing endogenous RNA, non-coding RNA

Purpose STAT2 is both an effector and negative regulator of type I interferon (IFN-I) signalling. We describe the characterization of a novel homozygous missense STAT2 substitution in a patient with a type I interferonopathy. Methods Whole-genome sequencing (WGS) was used to identify the genetic basis of disease in a patient with features of enhanced IFN-I signalling. After stable lentiviral reconstitution of STAT2-null human fibrosarcoma U6A cells with STAT2 wild type or p.(A219V), we performed quantitative polymerase chain reaction, western blotting, immunofluorescence, and co-immunoprecipitation to functionally characterize the p.(A219V) variant. Results WGS identified a rare homozygous single nucleotide transition in STAT2 (c.656C > T), resulting in a p.(A219V) substitution, in a patient displaying developmental delay, intracranial calcification, and up-regulation of interferon-stimulated gene (ISG) expression in blood. In vitro studies revealed that the STAT2 p.(A219V) variant retained the ability to transduce an IFN-I stimulus. Notably, STAT2 p.(A219V) failed to support receptor desensitization, resulting in sustained STAT2 phosphorylation and ISG up-regulation. Mechanistically, STAT2 p.(A219V) showed defective binding to ubiquitin specific protease 18 (USP18), providing a possible explanation for the chronic IFN-I pathway activation seen in the patient. Conclusion Our data indicate an impaired negative regulatory role of STAT2 p.(A219V) in IFN-I signalling and that mutations in STAT2 resulting in a type I interferonopathy state are not limited to the previously reported R148 residue. Indeed, structural modelling highlights at least 3 further residues critical to mediating a STAT2-USP18 interaction, in which mutations might be expected to result in defective negative feedback regulation of IFN-I signalling.

Snow phenology, recurrent seasonal patterns in snow cover and snowfall, has been significantly affected by global warming. Through the interaction with the climate, the dynamic variability of snow phenology affects the regional climate environment, vegetation ecosystem, soil properties, agricultural water resources, snow disasters and animal migration. First, this study compares the advantages, disadvantages and applicability of different sources of observation data and the principal research methods involved in studying snow phenology. Then, this work discusses the spatiotemporal variability and changing trends of snow phenology in the Northern Hemisphere, and summarizes the relationship between climate, vegetation and snow phenology. Finally, this review highlights the key areas related to snow phenology that require further study. Overall, during the past 50 years in the Northern Hemisphere, the snow cover end date (SCED) has shown a significantly advanced trend, the snow cover onset date (SCOD) has also been occurring slowly earlier, and the snow cover days (SCD) has shortened, but these two trends are not significant. The snow phenology variation is closely related to climate factors, atmospheric circulation, vegetation status and some spatial factors. Snow cover impacts climate change through interactions with atmospheric circulation systems. The rise in temperature will delay the SCOD, and the SCED is closely related to the temperature of the snowmelt season. The interaction between seasonal snow cover and climate will either stimulate or impede vegetation growth. With the change in snow cover, especially the decrease in snow cover in the melting stage can impact the climate change, the rise in temperature will change the growth conditions and extend the vegetation growth season. The relationship between snow cover and vegetation is inconsistent in different elevations and latitudes. Snow phenology variation is very complex and is the result of the combined action of many factors. Additionally, snow phenology will also have a great impact on the cryosphere. Therefore, we must understand snow phenology variation and prepare for future changes.

TNFα-induced protein 1 (TNFAIP1) serve a role in neurovascular disease. However, the potential role and molecular mechanism of TNFAIP1 in cerebral ischemia-reperfusion (I/R) remains elusive. In the present study, reverse transcription-quantitative PCR and western blotting were used to assess TNFAIP1 mRNA and protein expression levels in PC12 cells. Furthermore, using Cell Counting Kit-8, flow cytometry and western blotting, cell viability and apoptosis were evaluated. Oxidative stress was evaluated using DCFH-DA staining and ELISA was used for assessment of inflammatory factors. Expression of components in the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway and ferroptosis were assessed using western blotting analysis and an iron assay kit. TNFAIP1 expression was significantly upregulated in oxygen glucose deprivation and reperfusion (OGD/R)-injured PC12 cells. However, knocking down TNFAIP1 expression restored PC12 cell viability and decreased apoptosis following OGD/R-challenge. Furthermore, TNFAIP1 silencing significantly suppressed OGD/R-induced oxidative stress and inflammatory damage in PC12 cells. TNFAIP1 knockdown inhibited ferroptosis via activation of the Nrf2 signaling pathway in OGD/R-injured PC12 cells. Erastin treatment reversed the beneficial effects of TNFAIP1 knockdown on PC12 cell viability, apoptosis alleviation, oxidative stress and inflammation following OGD/R treatment. These results suggested that TNFAIP1 knockdown could alleviate OGD/R-induced neuronal cell damage by suppressing Nrf2-mediated ferroptosis, which might lay the foundation for the investigation of targeted-therapy for cerebral I/R injury in clinic.

Grasslands are the basis for sustainable development in the northern farming-pastoral transition zone of China, with functions of human production, living, and ecology. Large-scale human activities inevitably lead to significant changes in grasslands, resulting in significant impacts on ecosystem services. To this end, we quantitatively estimated the ecosystem services value in each positive succession process (the improvement in the coverage or area of grasslands) and negative succession process (the degradation in the coverage or area of grasslands). The results indicated that (1) grasslands showed an improving trend from 2000 to 2015. The grassland improvement from low to high coverage dominated the positive succession process. Grassland degradation from high to low coverage dominated the negative succession process. (2) The total ecosystem services value increased by 25,294.87 × 104 yuan from 2000 to 2015. The grassland improvement from low to high coverage was the most important process that led to the increase in ecosystem service value. The degradation between grasslands and non-grasslands was the key process that led to the decrement in ecosystem services value. (3) The impact of grassland dynamics on the regional ecosystem service value showed significant spatial heterogeneity at the town scale. The results will provide some implications for the sustainable development of grassland ecosystem services to improve human well-being.

The ratio of plant transpiration to total terrestrial evapotranspiration (T/ET) captures the role of vegetation in surface-atmosphere interactions. However, several studies have documented a large variability in T/ET. In this paper, we present a new T/ET dataset (also including transpiration, evapotranspiration data) for China from 1981 to 2015 with spatial and temporal resolutions of 0.05° and 8 days, respectively. The T/ET dataset is based on a model-data fusion method that integrates the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model with multivariate observational datasets (transpiration and evapotranspiration). The dataset is driven by satellite-based leaf area index (LAI) data from GLASS and GLOBMAP, and climate data from the Chinese Ecosystem Research Network (CERN). Observational annual T/ET were used to validate the model, with R2 and RMSE values were 0.73 and 0.07 (12.41%), respectively. The dataset provides significant insight into T/ET and its changes over the Chinese terrestrial ecosystem and will be beneficial for understanding the hydrological cycle and energy budgets between the land and the atmosphere., Measurement(s) ratio of transpiration to total terrestrial evapotranspiration • evapotranspiration • transpiration Technology Type(s) model-data fusion • computational modeling technique • digital curation Factor Type(s) year of data collection Sample Characteristic - Environment terrestrial biome Sample Characteristic - Location China Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12917642

CuxMnxFe3-2xO4/MWCNT nanocomposites were prepared by co-precipitation method. The structure, morphology, and surface properties of the samples were characterized by X-ray diffraction (XRD), Transmission electron microscopy (TEM), Energy dispersive spectrometer (EDS), Fourier transform infrared spectrometer (FTIR), N2 physical adsorption instrument, and X-ray photoelectron spectrometer (XPS). The successful loading of metal oxides on MWCNTs increased the catalytic activity of nanocomposites. In addition, CuxMnxFe3-2xO4/MWCNTs were used as catalyst for the degradation of PVA wastewater by catalytic wet air oxidation. Under the degradation conditions, pH was 2.5, catalyst dosage was1.5 g/L, reaction temperature was 275 °C, oxygen pressure was 1.0MP, the PVA degradation rate was 99.94%, the viscosity average molecular weight was decreased by 99.36%, and the degradation products were small molecules such as aldehydes, phenols, and acids, which basically confirmed the degradation of PVA wastewater. The degradation principle and kinetics were analyzed. The catalyst was washed and recovered and can maintain good catalytic capacity after four times of repeated use.

In this study, a series of naringenin

Hydraulic conductivity curves (HCCs) are important parameters in land surface modeling. The general way for predicting HCC from soil water retention curve (SWRC) requires an additional input of the...

Due to the complex pathogenesis of AD, the multi-target-directed ligands (MTDLs) strategy presented the best pharmacological option for AD treatment. Herein, a series of novel 2-acetylphenol-O-alkylhydroxyethylamine derivatives was rationally designed and synthesized. Of these derivatives, 5c was a good multifunctional agent (eeAChE IC50 =7.9 μM, MAO-B IC50 = 9.9 μM, BACE1 IC50 = 8.3 μM) in vitro and displayed a mixed-type AChE inhibition, which could bind to the CAS and PAS of AChE. Compound 5c also exhibited good antioxidant activity (ORAC = 2.5 eq) and neuroprotective effects. Furthermore, compound 5c was a selective metal ions chelator. And it could cross blood-brain barrier in vitro and complied with drug-like properties rule of 5. Therefore, compound 5c was a promising multifunctional agent for the treatment of AD.

Alzheimer's disease (AD) is a chronic, progressive brain neurodegenerative disorder. Up to now, there is no effective drug to halt or reverse the progress of AD. Given the complex pathogenesis of AD, the multi-target-directed ligands (MTDLs) strategy is considered as the promising therapy. Herein, a series of novel donepezil-chalone-rivastigmine hybrids was rationally designed and synthesized by fusing donepezil, chalone and rivastigmine. The in vitro bioactivity results displayed that compound 10c was a reversible huAChE (IC

Terrestrial ecosystems provide multiple services interacting in complex ways. However, most ecosystem services (ESs) models (e.g., InVEST and ARIES) ignored the relationships among ESs. Process‐based models can overcome this limitation, and the integration of ecological models with remote sensing data could greatly facilitate the investigation of the complex ecological processes. Therefore, based on the Carbon and Exchange between Vegetation, Soil, and Atmosphere (CEVSA) models, we developed a process‐based ES model (CEVSA‐ES) integrating remotely sensed leaf area index to evaluate four important ESs (i.e., productivity provision, carbon sequestration, water retention, and soil retention) at annual timescale in China. Compared to the traditional terrestrial biosphere models, the main innovation of CEVSA‐ES model was the consideration of soil erosion processes and its impact on carbon cycling. The new version also improved the carbon‐water cycle algorithms. Then, the Sobol and DEMC methods that integrated the CEVSA‐ES model with nine flux sites comprising 39 site‐years were used to identify and optimize parameters. Finally, the model using the optimized parameters was validated at 26 field sites comprising 135 site‐years. Simulation results showed good fits with ecosystem processes, explaining 95%, 92%, 76%, and 65% interannual variabilities of gross primary productivity, ecosystem respiration, net ecosystem productivity, and evapotranspiration, respectively. The CEVSA‐ES model performed well for productivity provision and carbon sequestration, which explained 96% and 81% of the spatial‐temporal variations of the observed annual productivity provision and carbon sequestration, respectively. The model also captured the interannual trends of water retention and soil erosion for most sites or basins.

As an important production base for livestock and a unique ecological zone in China, the northeast Tibetan Plateau has experienced dramatic land use/land cover (LULC) changes with increasing human activities and continuous climate change. However, extensive cloud cover limits the ability of optical remote sensing satellites to monitor accurately LULC changes in this area. To overcome this problem in LULC mapping in the Ganan Prefecture, 2000–2018, we used the dense time stacking of multi-temporal Landsat images and random forest algorithm based on the Google Earth Engine (GEE) platform. The dynamic trends of LULC changes were analyzed, and geographical detectors quantitatively evaluated the key driving factors of these changes. The results showed that (1) the overall classification accuracy varied between 89.14% and 91.41%, and the kappa values were greater than 86.55%, indicating that the classification results were reliably accurate. (2) The major LULC types in the study area were grassland and forest, and their area accounted for 50% and 25%, respectively. During the study period, the grassland area decreased, while the area of forest land and construction land increased to varying degrees. The land-use intensity presents multi-level intensity, and it was higher in the northeast than that in the southwest. (3) Elevation and population density were the major driving factors of LULC changes, and economic development has also significantly affected LULC. These findings revealed the main factors driving LULC changes in Gannan Prefecture and provided a reference for assisting in the development of sustainable land management and ecological protection policy decisions.

Traditional compartmental models such as SIR (susceptible, infected, recovered) assume that the epidemic transmits in a homogeneous population, but the real contact patterns in epidemics are heterogeneous. Employing a more realistic model that considers heterogeneous contact is consequently necessary. Here, we use a contact network to reconstruct unprotected, protected contact, and airborne spread to simulate the two-stages outbreak of COVID-19 (coronavirus disease 2019) on the “Diamond Princess” cruise ship. We employ Bayesian inference and Metropolis-Hastings sampling to estimate the model parameters and quantify the uncertainties by the ensemble simulation technique. During the early epidemic with intensive social contacts, the results reveal that the average transmissibility t was 0.026 and the basic reproductive number R 0 was 6.94, triple that in the WHO report, indicating that all people would be infected in one month. The t and R 0 decreased to 0.0007 and 0.2 when quarantine was implemented. The reconstruction suggests that diluting the airborne virus concentration in closed settings is useful in addition to isolation, and high-risk susceptible should follow rigorous prevention measures in case exposed. This study can provide useful implications for control and prevention measures for the other cruise ships and closed settings.

COVID-19 (Corona Virus Disease 2019) is globally spreading and the international cooperation is urgently required in joint prevention and control of the epidemic. Using the Maximum-Hasting (MH) parameter estimation method and the modified Susceptible Exposed Infectious Recovered (SEIR) model, the spread of the epidemic under three intervention scenarios (suppression, mitigation, mildness) is simulated and predicted in South Africa, Egypt, and Algeria, where the epidemic situations are severe. The studies are also conducted in Nigeria, Senegal and Kenya, where the epidemic situations are growing rapidly and the socio-economic are relatively under-developed, resulting in more difficulties in preventing the epidemic. Results indicated that the epidemic can be basically controlled in late April with strict control of scenario one, manifested by the circumstance in the South Africa and Senegal. Under moderate control of scenario two, the number of infected people will increase by 1.43-1.55 times of that in scenario one, the date of the epidemic being controlled will be delayed by about 10 days, and Algeria, Nigeria, and Kenya are in accordance with this situation. In the third scenario of weak control, the epidemic will be controlled by late May, the total number of infected cases will double that in scenario two, and Egypt is in line with this prediction. In the end, a series of epidemic controlling methods are proposed, including patient quarantine, close contact tracing, population movement control, government intervention, city and county epidemic risk level classification, and medical cooperation and the Chinese assistance.

Wetland methane (CH4) emissions are the largest natural source in the global CH4 budget, contributing to roughly one third of total natural and anthropogenic emissions. As the second most important anthropogenic greenhouse gas in the atmosphere after CO2, CH4 is strongly associated with climate feedbacks. However, due to the paucity of data, wetland CH4 feedbacks were not fully assessed in the Intergovernmental Panel on Climate Change Fifth Assessment Report. The degree to which future expansion of wetlands and CH4 emissions will evolve and consequently drive climate feedbacks is thus a question of major concern. Here we present an ensemble estimate of wetland CH4 emissions driven by 38 general circulation models for the 21st century. We find that climate change-induced increases in boreal wetland extent and temperature-driven increases in tropical CH4 emissions will dominate anthropogenic CH4 emissions by 38 to 56% toward the end of the 21st century under the Representative Concentration Pathway (RCP2.6). Depending on scenarios, wetland CH4 feedbacks translate to an increase in additional global mean radiative forcing of 0.04 W·m-2 to 0.19 W·m-2 by the end of the 21st century. Under the "worst-case" RCP8.5 scenario, with no climate mitigation, boreal CH4 emissions are enhanced by 18.05 Tg to 41.69 Tg, due to thawing of inundated areas during the cold season (December to May) and rising temperature, while tropical CH4 emissions accelerate with a total increment of 48.36 Tg to 87.37 Tg by 2099. Our results suggest that climate mitigation policies must consider mitigation of wetland CH4 feedbacks to maintain average global warming below 2 °C.

Difficulty in measuring hydraulic conductivity, particularly under dry conditions, calls for methods of predicting the conductivity from easily obtained soil properties. As a complement to the recently published EMFX model, a method based on two specific suction conditions is proposed to estimate saturated film conductivity from the soil water retention curve. This method reduces one fitting parameter in the previous EMFX model, making it possible to predict the hydraulic conductivity from the soil water retention curve over the complete moisture range. Model performance is evaluated with published data of soils in a broad texture range from sand to clay. The testing results indicate that 1) the modified EMFX model (namely the EMFX-K model), incorporating both capillary and adsorption forces, provides good agreement with the conductivity data over the entire moisture range; 2) a value of 0.5 for the tortuosity factor in the EMFX-K model as that in the Mualem’s model gives comparable estimation of the relative conductivity associated with the capillary force; and 3) a value of −1.0 × 10 −20 J for the Hamaker constant, rather than the commonly used value of −6.0 × 10 −20 J, appears to be more appropriate to represent solely the effect of the van der Waals forces and to predict the film conductivity. In comparison with the commonly used van Genuchten-Mualem model, the EMFX-K model significantly improves the prediction of hydraulic conductivity under dry conditions. The sensitivity analysis result suggests that the uncertainty in the film thickness estimation is important in explaining the model underestimation of hydraulic conductivity for the soils with fine texture, in addition to the uncertainties from the measurements and the model structure. High quality data that cover the complete moisture range for a variety of soil textures are required to further test the method.

Eddy covariance (EC) measurements are often used to validate net ecosystem productivity (NEP) estimated from satellite remote sensing data and biogeochemical models. However, EC measurements represent an integrated flux over their footprint area, which usually differs from respective model grids or remote sensing pixels. Quantifying the uncertainties of scale mismatch associated with gridded flux estimates by upscaling single EC tower NEP measurements to the grid scale is an important but not yet fully investigated issue due to limited data availability as well as knowledge of flux variability at the grid scale. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE) built a flux observation matrix that includes 17 EC towers within a 5 km × 5 km area in a heterogeneous agricultural landscape in northwestern China, providing an unprecedented opportunity to evaluate the uncertainty of upscaling due to spatial representative differences at the grid scale. Based on the HiWATER-MUSOEXE data, this study evaluated the spatial representativeness and uncertainty of EC CO2 flux measurements for upscaling to the grid scale using a scheme that combines a footprint model and a model-data fusion method. The results revealed the large spatial variability of gross primary productivity (GPP), ecosystem respiration (Re), and NEP within the study site during the growing season from 10 June to 14 September 2012. The variability of fluxes led to high variability in the representativeness of single EC towers for grid-scale NEP. The systematic underestimations of a single EC tower may reach 92(±11)%, 30(±11)%, and 165(±150)% and the overestimations may reach 25(±14)%, 20(±13)%, and 40(±33)% for GPP, Re, and NEP, respectively. This finding suggests that remotely sensed NEP at the global scale (e.g., MODIS products) should not be validated against single EC tower data in the case of heterogeneous surfaces. Any systematic bias should be addressed before upscaling EC data to grid scale. Otherwise, most of the systematic bias may be propagated to grid scale due to the scale dependence of model parameters. A systematic bias greater than 20% of the EC measurements can be corrected effectively using four indicators proposed in this study. These results will contribute to the understanding of spatial representativeness of EC towers within a heterogeneous landscape, to upscaling carbon fluxes from the footprint to the grid scale, to the selection of the location of EC towers, and to the reduction in the bias of NEP products by using an improved parameterization scheme of remote-sensing driven models, such as VPRM.

Phenology plays a fundamental role in regulating photosynthesis, evapotranspiration, and surface energy fluxes and is sensitive to climate change. The global mean surface air temperature data indicate a global warming hiatus between 1998 and 2012, while its impacts on global phenology remains unclear. Here we use long-term satellite and FLUXNET records to examine phenology trends in the northern hemisphere before and during the warming hiatus. Our results based on the satellite record show that the phenology change rate slowed down during the warming hiatus. The analysis of the long-term FLUXNET measurements, mainly within the warming hiatus, shows that there were no widespread advancing (or delaying) trends in spring (or autumn) phenology. The lack of widespread phenology trends partly led to the lack of widespread trends in spring and autumn carbon fluxes. Our findings have significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks., A global warming hiatus occurred during 1998 and 2012 but its effects on phenology are unclear. Here the authors examine the trends in spring and autumn phenology in the northern hemisphere and the effects of the warming hiatus and show that phenology change rate in the northern hemisphere slowed down during the warming hiatus.

In this study, MnCoO3@Al2O3 (MCA) was synthesized using a simple sol-gel method a4nd investigated as a catalyst for Polyvinyl alcohol (PVA) textiles degradation via hydrogen peroxide (H2O2) activation. The structures and properties of MCA were characterized using XRD, SEM, XPS, BJH and EDS. The optimum conditions of PVA degradation, such as MCA load, catalyst dosage, initial pH value and H2O2 concentration were explored. It was found that the removal rate of PVA under the conditions of 1000 mg/L MCA, initial pH = 3 and 2.934 ∗ 103 mM H2O2 reached 98.6%. The reusability of MCA catalyst was tested for 5 consecutive cycles. The intermediate degradation products of PVA were tested by GCMS, and the possible way of PVA degradation was suggested. Moreover, the existence of OH∙ was confirmed to be the main radicals through quenching experiment. Finally, the degradation pathways of PVA in the MCA/H2O2 system was proposed. In conclusion, this study put forward MCA as a heterogeneous catalyst to activate H2O2 for the degradation of PVA, which could be an excellent application in wastewater treatment.

As an important part of the wetland ecosystem, alpine wetland is not only one of the most important ecological water conservation areas in the Qinghai&ndash, Tibet Plateau region, but is also an effective regulator of the local climate. In this study, using three machine learning algorithms to extract wetland, we employ the landscape ecological index to quantitatively analyze the evolution of landscape patterns and grey correlation to analyze the driving factors of Zoige wetland landscape pattern change from 1995 to 2020. The following results were obtained. (1) The random forest algorithm (RF) performs best when dealing with high-dimensional data, and the accuracy of the decision tree algorithm (DT) is better. The performance of the RF and DT is better than that of the support vector machine algorithm. (2) The alpine wetland in the study area was degraded from 1995 to 2015, whereas wetland area began to increase after 2015. (3) The results of landscape analysis show the decrease in wetland area from 1995 to 2005 was mainly due to the fragmentation of larger patches into many small patches and loss of the original small patches, while the 2005 to 2015 decrease was caused by the loss of many middle patches and the decrease in large patches from the edge to the middle. The 2015 to 2020 increase is due to an increase in the number of smaller patches and recovery of original wetland area. (4) The grey correlation degree further shows that precipitation and evaporation are the main factors leading to the change in the landscape pattern of Zoige alpine wetland. The results are of great significance to the long-term monitoring of the Zoige wetland ecosystem.

The distribution of stable isotopes and ions in precipitation in the Shule River Basin, northwestern China, were investigated to understand the regional water cycle and precipitation input to groundwater recharge. The study found that the mean annual concentrations of Ca2+, Na+, SO42–, Cl–, Mg2+, NO3–, and K+ in the basin were lower than those in other arid areas of northwestern China. The average concentrations of ions in the lower reaches of the Shule River were higher than those in the upper reaches. The results showed that the main ionic concentrations decreased with the increase of precipitation amount, indicating that heavy precipitation cannot only wash crustal aerosols out of the atmosphere, but also create a dilution effect. Cl– and Na+ in precipitation had a strong and positive correlation, suggesting a common origin for the two ions. However, the excess of Na+, combined with non-marine SO42– and NO3–, indicated that some ions were contributed by terrestrial origins. In the extremely arid regions of northwestern China, the evaporation process obviously changes the original relationship between δ2H and δ18O in precipitation, and leads to dexcess values

An ecosystem model serves as an important tool to understand the carbon cycle in the forest ecosystem. However, the sensitivities of parameters and uncertainties of the model outputs are not clearly understood. Parameter sensitivity analysis (SA) and uncertainty analysis (UA) play a crucial role in the improvement of forest gross primary productivity GPP simulation. This study presents a global SA based on an extended Fourier amplitude sensitivity test (EFAST) method to quantify the sensitivities of 16 parameters in the Flux-based ecosystem model (FBEM). To systematically evaluate the parameters&rsquo, sensitivities, various parameter ranges, different model outputs, temporal variations of parameters sensitivity index (SI) were comprehensively explored via three experiments. Based on the numerical experiments of SA, the UA experiments were designed and performed for parameter estimation based on a Markov chain Monte Carlo (MCMC) method. The ratio of internal CO2 to air CO2 ( , canopy quantum efficiency of photon conversion , maximum carboxylation rate at 25 ( were the most sensitive parameters for the GPP. It was also indicated that were influenced by temperature throughout the entire growth stage. The result of parameter estimation of only using four sensitive parameters (RMSE =1.657) is very close to that using all the parameters (RMSE = 1.496). The results of SA suggest that sensitive parameters, such as strongly influence on the forest GPP simulation, and the temporal characteristics of the parameters` SI on GPP and NEE were changed in different growth. The sensitive parameters were a major source of uncertainty and parameter estimation based on the parameter SA could lead to desirable results without introducing too great uncertainties.

Based on direct measurements of half-hourly canopy evapotranspiration (ET; W m−2) using the eddy covariance (EC) system and daily soil evaporation (E; mm day−1) using microlysimeters over a crop ecosystem in arid northwestern China from 27 May to 14 September in 2013, a Bayesian method was used to simultaneously parameterize the soil surface and canopy resistances in the Shuttleworth–Wallace (S–W) model. Four of the six parameters showed relatively larger uncertainty reductions (> 50%), and their posterior distributions became approximately symmetric with distinctive modes. There was a moderately good agreement between measured and simulated values of half-hourly ET and daily E with a linear regression being y = 0.84 x + 0.18 (R2 = 0.83) and y = 1.01 x + 0.01 (R2 = 0.82), respectively. The causes of underestimations of ET by the S–W model was possibly attributed to the microscale advection, which can contribute an added energy in the form of downward sensible heat fluxes to the ET process. Therefore, the advection process should be taken into account in simulating ET in heterogeneous land surfaces. Also, underestimations were observed on or shortly after rainy days, which may be due to direct evaporation of liquid water intercepted in the canopy. Thus, the canopy interception model should be coupled to the S–W model in the long-term ET simulation.

Photosynthesis is a very important sub-process in the carbon cycle and is a crucial sub-modular function in carbon cycle models. In this study, two typical photosynthesis parameterization schemes were compared based on meteorological and eddy covariance (EC) observations at an alpine meadow site. The photosynthesis model parameters were estimated using the Markov Chain Monte Carlo (MCMC) method. The results indicated that the Farquhar-conductance coupled model better predicted the gross primary production (GPP) for the alpine meadow ecosystem at an hourly time scale than the light use efficiency (LUE) model even though the Farquhar-conductance coupled model has a lower computational efficiency than the LUE model. Compared to the Ball–Woodrow–Berry (BWB) stomatal conductance model, coupling the Farquhar model with the Leuning stomatal conductance model more accurately simulated GPP.