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Long-term PM2.5 data are essential for the atmospheric environment, human health, and climate change. PM2.5 measurements are sparsely distributed and of short duration. In this study, daily PM2.5 concentrations are estimated using a machine learning method for the period from 1959 to 2022 in the Northern Hemisphere based on near-surface atmospheric visibility. They are extracted from the Integrated Surface Database (ISD). Daily continuous monitored PM2.5 concentration is set as the target, and near-surface atmospheric visibility and other related variables are used as the inputs. A total of 80 % of the samples of each site are the training set, and 20 % are the testing set. The training result shows that the slope of linear regression with a 95 % confidence interval (CI) between the estimated PM2.5 concentration and the monitored PM2.5 concentration is 0.955 [0.955, 0.955], the coefficient of determination (R2) is 0.95, the root mean square error (RMSE) is 7.2 µg m−3, and the mean absolute error (MAE) is 3.2 µg m−3. The test result shows that the slope within a 95 % CI between the predicted PM2.5 concentration and the monitored PM2.5 concentration is 0.864 [0.863, 0.865], the R2 is 0.79, the RMSE is 14.8 µg m−3, and the MAE is 7.6 µg m−3. Compared with a global PM2.5 concentration dataset derived from a satellite aerosol optical depth product with 1 km resolution, the slopes of linear regression on the daily (monthly) scale are 0.817 (0.854) from 2000 to 2021, 0.758 (0.821) from 2000 to 2010, and 0.867 (0.879) from 2011 to 2022, indicating the accuracy of the model and the consistency of the estimated PM2.5 concentration on the temporal scale. The interannual trends and spatial patterns of PM2.5 concentration on the regional scale from 1959 to 2022 are analyzed using a generalized additive mixed model (GAMM), suitable for situations with an uneven spatial distribution of monitoring sites. The trend is the slope of the Theil–Sen estimator. In Canada, the trend is −0.10 µg m−3 per decade, and the PM2.5 concentration exhibits an east–high to west–low pattern. In the United States, the trend is −0.40 µg m−3 per decade, and PM2.5 concentration decreases significantly after 1992, with a trend of −1.39 µg m−3 per decade. The areas of high PM2.5 concentration are in the east and west, and the areas of low PM2.5 concentration are in the central and northern regions. In Europe, the trend is −1.55 µg m−3 per decade. High-concentration areas are distributed in eastern Europe, and the low-concentration areas are in northern and western Europe. In China, the trend is 2.09 µg m−3 per decade. High- concentration areas are distributed in northern China, and the low-concentration areas are distributed in southern China. The trend is 2.65 µg m−3 per decade up to 2011 and −22.23 µg m−3 per decade since 2012. In India, the trend is 0.92 µg m−3 per decade. The concentration exhibits a north–high to south–low pattern, with high-concentration areas distributed in northern India, such as the Ganges Plain and Thar Desert, and the low-concentration area in the Deccan Plateau. The trend is 1.41 µg m−3 per decade up to 2013 and −23.36 µg m−3 per decade from 2014. The variation in regional PM2.5 concentrations is closely related to the implementation of air quality laws and regulations. The daily site-scale PM2.5 concentration dataset from 1959 to 2022 in the Northern Hemisphere is available at the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Atmos.tpdc.301127) (Hao et al., 2024).

The Madden–Julian Oscillation (MJO) is a crucial predictability source on a subseasonal-to-seasonal (S2S) timescale. Therefore, the models participating in the World Weather Research Programme and the World Climate Research Programme (WWRP/WCRP) S2S prediction project focus on accurately predicting and analyzing the MJO. This study provides a detailed description of the configuration within the Institute of Atmospheric Physics at the Chinese Academy of Sciences (IAP-CAS) S2S forecast system. We assess the accuracy of the IAP-CAS model's MJO forecast using traditional Real-time Multivariate MJO (RMM) analysis and cluster analysis. Then, we explain the reasons behind any bias observed in the MJO forecast. Comparing the 20-year hindcast with observations, we found that the IAP-CAS ensemble mean has a skill of 24 d. However, the ensemble spread still has potential for improvement. To examine the MJO structure in detail, we use cluster analysis to classify the MJO events during boreal winter into four types: fast-propagating, slow-propagating, standing, and jumping patterns of MJO. The model exhibits biases of overestimated amplitude and faster propagation speed in the propagating MJO events. Upon further analysis, it was found that the model forecasted a wetter background state. This leads to stronger forecasted convection and coupled waves, especially in the fast MJO events. The overestimation of the strength and length of MJO-coupled waves results in a faster MJO mode and quicker dissipation in the IAP-CAS model. These findings show that the IAP-CAS skillfully forecasts signals of MJO and its propagation, and they also provide valuable guidance for improving the current MJO forecast by developing the ensemble system and moisture forecast.

Long-term and high spatial resolution aerosol optical depth (AOD) data are essential for climate change detection and attribution. Global ground-based AOD observations are sparsely distributed, and satellite AOD retrievals have a low temporal frequency as well low accuracy before 2000 over land. In this study, AOD at 550 nm is derived from visibility observations collected at more than 5000 meteorological stations over global land regions from 1959 to 2021. The AOD retrievals (550 nm) of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua Earth observation satellite are used to train the machine learning model, and the ERA5 reanalysis boundary layer height is used to convert the surface visibility to AOD. Comparisons with an independent dataset (AERONET ground-based observations) show that the predicted AOD has a correlation coefficient of 0.55 at the daily scale. The correlation coefficients are higher at monthly and annual scales, which are 0.61 and 0.65, respectively. The evaluation shows consistent predictive ability prior to 2000, with correlation coefficients of 0.54, 0.66, and 0.66 at the daily, monthly, and annual scales, respectively. Due to the small number and sparse visibility stations prior to 1980, the global and regional analysis in this study is from 1980 to 2021. From 1980 to 2021, the mean visibility-derived AOD values over global land areas, the Northern Hemisphere, and the Southern Hemisphere are 0.177, 0.178, and 0.175, with a trend of −0.0029 per 10 years, −0.0030 per 10 years, and −0.0021 per 10 years from 1980 to 2021. The regional means (trends) of AOD are 0.181 (−0.0096 per 10 years), 0.163 (−0.0026 per 10 years), 0.146 (−0.0017 per 10 years), 0.165 (−0.0027 per 10 years), 0.198 (−0.0075 per 10 years), 0.281 (−0.0062 per 10 years), 0.182 (−0.0016 per 10 years), 0.133 (−0.0028 per 10 years), 0.222 (0.0007 per 10 years), 0.244 (−0.0009 per 10 years), 0.241 (0.0130 per 10 years), and 0.254 (0.0119 per 10 years) in Eastern Europe, Western Europe, Western North America, Eastern North America, Central South America, Western Africa, Southern Africa, Australia, Southeast Asia, Northeast Asia, Eastern China, and India, respectively. However, the trends decrease significantly in Eastern China (−0.0572 per 10 years) and Northeast Asia (−0.0213 per 10 years) after 2014, with the larger increasing trend found after 2005 in India (0.0446 per 10 years). The visibility-derived daily AOD dataset at 5032 stations over global land from 1959 to 2021 is available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Atmos.tpdc.300822) (Hao et al., 2023).

Biogenic volatile organic compounds (BVOCs), as a crucial component that impacts atmospheric chemistry and ecological interactions with various organisms, play a significant role in the atmosphere–ecosystem relationship. However, traditional field observation methods are challenging for accurately estimating BVOC emissions in forest ecosystems with high biodiversity, leading to significant uncertainty in quantifying these compounds. To address this issue, this research proposes a workflow utilizing drone-mounted lidar and photogrammetry technologies for identifying plant species to obtain accurate BVOC emission data. By applying this workflow to a typical subtropical forest plot, the following findings were made: the drone-mounted lidar and photogrammetry modules effectively segmented trees and acquired single wood structures and images of each tree. Image recognition technology enabled relatively accurate identification of tree species, with the highest-frequency family being Euphorbiaceae. The largest cumulative isoprene emissions in the study plot were from the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family. To fully leverage the estimation results of BVOC emissions directly from individual tree levels, it may be necessary for communities to establish more comprehensive tree species emission databases and models.

The climate of the Tibetan Plateau (TP) has experienced substantial changes in recent decades as a result of the location's susceptibility to global climate change. The changes observed across the TP are closely associated with regional land–atmosphere interactions. Current models and satellites struggle to accurately depict the interactions; therefore, critical field observations on land–atmosphere interactions outlined here provide necessary independent validation data and fine-scale process insights for constraining reanalysis products, remote sensing retrievals, and land surface model parameterizations. Scientific data sharing is crucial for the TP since in situ observations are rarely available under these harsh conditions. However, field observations are currently dispersed among individuals or groups and have not yet been integrated for comprehensive analysis. This has prevented a better understanding of the interactions, the unprecedented changes they generate, and the substantial ecological and environmental consequences they bring about. In this study, we collaborated with different agencies and organizations to present a comprehensive dataset for hourly measurements of surface energy balance components, soil hydrothermal properties, and near-surface micrometeorological conditions spanning up to 17 years (2005–2021). This dataset, derived from 12 field stations covering a variety of typical TP landscapes, provides the most extensive in situ observation data available for studying land–atmosphere interactions on the TP to date in terms of both spatial coverage and duration. Three categories of observations are provided in this dataset: meteorological gradient data (met), soil hydrothermal data (soil), and turbulent flux data (flux). To assure data quality, a set of rigorous data-processing and quality control procedures are implemented for all observation elements (e.g., wind speed and direction at different height) in this dataset. The operational workflow and procedures are individually tailored to the varied types of elements at each station, including automated error screening, manual inspection, diagnostic checking, adjustments, and quality flagging. The hourly raw data series; the quality-assured data; and supplementary information, including data integrity and the percentage of correct data on a monthly scale, are provided via the National Tibetan Plateau Data Center (https://doi.org/10.11888/Atmos.tpdc.300977, Ma et al., 2023a). With the greatest number of stations covered, the fullest collection of meteorological elements, and the longest duration of observations and recordings to date, this dataset is the most extensive hourly land–atmosphere interaction observation dataset for the TP. It will serve as the benchmark for evaluating and refining land surface models, reanalysis products, and remote sensing retrievals, as well as for characterizing fine-scale land–atmosphere interaction processes of the TP and underlying influence mechanisms.

Photocatalytic reactions during the daytime, alongside aqueous-phase reactions occurring during both daytime and nighttime, are identified as the two primary processes facilitating the conversion of aerosol iron (Fe) from the insoluble state to the soluble state within the atmospheric environment. This study investigated the levels of total Fe (FeT) and soluble Fe (FeS) in PM2.5 samples collected during daytime and nighttime in Qingdao, a coastal city in eastern China, evaluating the distinctive roles of these two pathways in enhancing aerosol Fe solubility (%FeS, defined as the ratio of FeS to FeT). Under clean and humid conditions, characterized by prevailing sea breezes and a relative humidity (RH) typically above 80 %, an average daytime %FeS of 8.7 % was observed, which systematically exceeded the nighttime %FeS (6.3 %). Photochemical conversions involving oxalate contributed to the higher %FeS observed during daytime. Conversely, in scenarios where air masses originated from inland areas and exhibited slightly polluted, daytime %FeS (3.7 %) was noted to be lower than the nighttime %FeS (5.8 %). This discrepancy was attributable to the variations in RH, with nighttime RH averaging around 77 %, conducive to the more efficient generation of acidic compounds, thereby accelerating FeS production compared to the daytime, when RH was only about 62 %. Furthermore, the oxidation rates of sulfur (SOR) displayed a strong correlation with RH, particularly when RH fell below 75 %. A 10 % increase in RH corresponded to a 7.6 % rise in SOR, which served as the primary driver of the higher aerosol acidity and %FeS at night. These findings highlight the RH-dependent activation of aqueous-phase reactions and the augmentation of daytime photocatalysis in the formation of FeS in the coastal moist atmosphere.

Abstract Clonal hematopoiesis (CH) is defined as a single hematopoietic stem/progenitor cell (HSPC) gaining selective advantage over a broader range of HSPCs. When linked to somatic mutations in myeloid malignancy-associated genes, such as TET2-mediated clonal hematopoiesis of indeterminate potential or CHIP, it represents increased risk for hematological malignancies and cardiovascular disease. IL1β is elevated in patients with CHIP, however, its effect is not well understood. Here we show that IL1β promotes expansion of pro-inflammatory monocytes/macrophages, coinciding with a failure in the demethylation of lymphoid and erythroid lineage associated enhancers and transcription factor binding sites, in a mouse model of CHIP with hematopoietic-cell-specific deletion of Tet2. DNA-methylation is significantly lost in wild type HSPCs upon IL1β administration, which is resisted by Tet2-deficient HSPCs, and thus IL1β enhances the self-renewing ability of Tet2-deficient HSPCs by upregulating genes associated with self-renewal and by resisting demethylation of transcription factor binding sites related to terminal differentiation. Using aged mouse models and human progenitors, we demonstrate that targeting IL1 signaling could represent an early intervention strategy in preleukemic disorders. In summary, our results show that Tet2 is an important mediator of an IL1β-promoted epigenetic program to maintain the fine balance between self-renewal and lineage differentiation during hematopoiesis.

The application of a self-adjusted strategy has received increasing attention in current transmission design. This paper proposes a gear injury equilibrium oriented self-adjusted shifting strategy (EASS), which can make injury of different gears consistent. First, the injury value of different gears was judged in real time, and the working time of the gear with the largest injury value was reduced by adjusting the shift curve. Second, by considering key points as constraints, an optimal displacement trajectory for a synchronizer was proposed, and then a compound control method using adaptive nonsingular global fast-terminal sliding-mode control (AN-GFTSMC) was developed, which enables a high tracking performance and a better parameter perturbation rejection ability. Finally, both the simulation and real-vehicle experimental results showed that, compared with conventional control, the designed control strategy had good performance: response time was decreased, gear injury tended to be consistent, and transmission reliability was improved.

The Tibetan Plateau and its surroundings have recently experienced several catastrophic glacier-related disasters. It is of great scientific and practical significance to establish ground-based early warning systems (EWSs) to understand the processes and mechanisms of glacial disasters and warn against potential threats to downstream settlements and infrastructure. However, there are few sophisticated EWSs on the Tibetan Plateau. With the support of the Second Tibetan Plateau Scientific Expedition and Research Program (STPSER), an EWS was developed and implemented in the Sedongpu Valley, southeastern Tibetan Plateau, where repeated river blockages have occurred due to ice/rock collapse debris flow. The EWS collected datasets of optical/thermal videos/photos, geophone waveforms, water levels, and meteorological variables in this sparsely populated zone. It has successfully warned against three ice-rock collapse–debris flow–river blockage chain events, and seven small-scale ice-rock collapse–debris flow events. Meanwhile, it was found that the low-cost geophone can effectively indicate the occurrence and magnitude of ice/rock collapses by local thresholds, and water level observation is an efficient way to warn of river blockages. Our observations showed that there were no immediate meteorological triggers for the ice-rock collapses and associated debris flows. Several factors, such as the volume and location of the collapses and the percentage of ice content involved, influence the velocities of debris flows and the magnitude of river blockages. There are still two possible glaciers in the study area that are at risk of ice collapse. It is worth monitoring their dynamic changes using high-resolution satellite data and the ground-based EWS to safeguard the surrounding hydrological projects and infrastructure in this transboundary region.

This review paper describes the energy-upgraded Continuous Electron Beam Accelerator Facility (CEBAF) accelerator. This superconducting linac has achieved 12 GeV beam energy by adding 11 new high-performance cryomodules containing 88 superconducting cavities that have operated cw at an average accelerating gradient of 20 MV/m. After reviewing the attributes and performance of the previous 6 GeV CEBAF accelerator, we discuss the upgraded CEBAF accelerator system in detail with particular attention paid to the new beam acceleration systems. In addition to doubling the acceleration in each linac, the upgrade included improving the beam recirculation magnets, adding more helium cooling capacity to allow the newly installed modules to run cold, adding a new experimental hall, and improving numerous other accelerator components. We review several of the techniques deployed to operate and analyze the accelerator performance and document system operating experience and performance. In the final portion of the document, we present much of the current planning regarding projects to improve accelerator performance and enhance operating margins, and our plans for ensuring CEBAF operates reliably into the future. For the benefit of potential users of CEBAF, the performance and quality measures for the beam delivered to each of the experimental halls are summarized in the Appendix.

Exploring the snow depth on Mount Everest, one of the most inaccessible places on our planet, has long been a topic of interest. Previously reported snow depths have been inconsistent and have large uncertainties. Here, we report the ground-penetrating radar survey of snow depth along the north slope of Mount Everest in May 2022. Our radar measurements display a gradual increasing transition of snow depth along the north slope, and the mean depth estimates at the summit are 9.5±1.2 m. This updated snow depth on Mount Everest is much deeper than previously reported values (0.9–3.5 m).

Abstract Year‐round precipitation in coastal East Antarctica and Antarctic Peninsula was used to investigate the seasonal patterns in sources of atmospheric perchlorate (ClO4−). Although featuring distinct climates, the two locations exhibit similar annual mean and seasonal cycles of ClO4− concentration, with higher values in autumn and lower concentrations in winter and spring. Tropospheric formation dominates atmospheric ClO4− in spring and summer, which is influenced by both oxidants levels and environmental conditions (e.g., air humidity). Tropospheric ClO4− production may also be promoted by elevated levels of oxidants brought by air mass from the interior Antarctic ice sheet in spring and summer. The autumn concentration maximum may originate from ClO4− produced in the stratosphere through reactions between reactive chlorine and ozone during spring and summer. In winter, the stratospheric input may contribute to ClO4− via polar stratospheric clouds sedimentation.

The thermal state of permafrost in the present and future is fundamental to ecosystem evolution, hydrological processes, carbon release and infrastructure integrity in cold regions. In 2011, we initiated a permafrost monitoring network along the China–Russia crude oil pipeline (CRCOP) route at the eastern flank of the northern Da Xing'anling Mountains in Northeast China. We compiled an integrated dataset of the ground thermal state along the CRCOP route consisting of meteorological data near the southern limit of latitudinal permafrost, ground temperature (GT) data in 20 boreholes with depths of 10.0–60.6 m, soil volumetric liquid water contents (VWCs) and 2D electrical resistivity tomography (ERT) data at different sites. Results demonstrate a permafrost warming during 2011–2020 in the vicinity of the southern limit of latitudinal permafrost, as manifested by rising GTs at almost all depths in response to climate warming. Local thermal disturbances triggered by the construction and operation of CRCOPs have resulted in significant permafrost warming and subsequent thawing on the right-of-way (ROW) of the pipelines. This permafrost thaw will persist, but it can be alleviated by adopting mitigative measures, such as an insulation layer and thermosyphons. The in situ observational dataset is of great value for assessing the variability of permafrost under the linear disturbances of the CRCOPs and related environmental effects, for understanding hydro–thermal–mechanical interactions between the buried pipelines and permafrost foundation soils, and for evaluating the operational and structural integrity of the pipeline systems in the future. The dataset is available at the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.272357; Li, 2022).

Nonlinearity is one of the important factors affecting the positioning accuracy of the macro–micro composite actuator. To improve the positioning accuracy of the driving model of the macro–micro composite actuator, this paper combines the research phenomenon of the nonlinear characteristics of the voice coil motor to model the nonlinear factors that affect the macro-moving part of the macro–micro composite actuator. Firstly, based on analyzing its structure and working principle, the variation law of the magnetic field intensity at the working air gap of the macro-motion part is analyzed by the finite element method, and the driving force model of the macro-motion part is established. Secondly, through the magnetic field simulation analysis, there is a magnetization phenomenon in the mover part, and the static friction model is established. Then, the experimental data are acquired and processed by building the experimental test platform of the actuator, and the variation model of the electromechanical time constant with the macro-motion displacement is established. Then, combined with the Stribeck model and the static friction model, the kinetic model of the macro-motion part is established. Finally, using the least square method identify the parameter model, the results are compared with the experiment. The results show that the magnetic field distribution at the working air gap of the macro-motion part of the macro–micro composite actuator is relatively uniform, but it is related to the macro-motion displacement and the macro-motion coil current. When the macro-motion part of the macro-micro composite actuator starts, the friction model can approximately reflect the change of friction force, the kinetic model of the macro-motion part can reflect the dynamic characteristics of the macro-motion part, and the matching degree is 92.97 %. The research results lay a theoretical and technical foundation for the development of a high-speed and large-stroke positioning controller of the macro-motion micro composite actuator.

On 22 March 2021, an approximately 50 Mm3 ice-rock avalanche occurred from 6500 m a.s.l. in the Sedongpu basin, southeastern Tibet. The avalanche transformed into a highly mobile mass flow which temporarily blocked the Yarlung Tsangpo river. The avalanche flow lasted ∼ 5 min and produced substantial geomorphological reworking. This event, and previous ones from the basin, occurred concurrently with, or shortly after, positive seasonal air temperature anomalies. The occurrence of future large mass flows from the basin cannot be ruled out, and their impacts must be carefully considered given implications for sustainable hydropower and associated socioeconomic development in the region.

The Tibetan Plateau and its surroundings, also known as the Third Pole, play an important role in the global and regional climate and hydrological cycle. Carbonaceous aerosols (CAs), including black carbon (BC) and organic carbon (OC), can directly or indirectly absorb and scatter solar radiation and change the energy balance on the Earth. CAs, along with the other atmospheric pollutants (e.g., mercury), can be frequently transported over long distances into the inland Tibetan Plateau. During the last decades, a coordinated monitoring network and research program named “Atmospheric Pollution and Cryospheric Changes” (APCC) has been gradually set up and continuously operated within the Third Pole regions to investigate the linkage between atmospheric pollutants and cryospheric changes. This paper presents a systematic dataset of BC, OC, water-soluble organic carbon (WSOC), and water-insoluble organic carbon (WIOC) from aerosols (20 stations), glaciers (17 glaciers, including samples from surface snow and ice, snow pits, and 2 ice cores), snow cover (2 stations continuously observed and 138 locations surveyed once), precipitation (6 stations), and lake sediment cores (7 lakes) collected across the Third Pole, based on the APCC program. These data were created based on online (in situ) and laboratory measurements. High-resolution (daily scale) atmospheric-equivalent BC concentrations were obtained by using an Aethalometer (AE-33) in the Mt. Everest (Qomolangma) region, which can provide new insight into the mechanism of BC transportation over the Himalayas. Spatial distributions of BC, OC, WSOC, and WIOC from aerosols, glaciers, snow cover, and precipitation indicated different features among the different regions of the Third Pole, which were mostly influenced by emission sources, transport pathways, and deposition processes. Historical records of BC from ice cores and lake sediment cores revealed the strength of the impacts of human activity since the Industrial Revolution. BC isotopes from glaciers and aerosols identified the relative contributions of biomass and fossil fuel combustion to BC deposition on the Third Pole. Mass absorption cross sections of BC and WSOC from aerosol, glaciers, snow cover, and precipitation samples were also provided. This updated dataset is released to the scientific communities focusing on atmospheric science, cryospheric science, hydrology, climatology, and environmental science. The related datasets are presented in the form of excel files. BC and OC datasets over the Third Pole are available to download from the National Cryosphere Desert Data Center (https://doi.org/10.12072/ncdc.NIEER.db0114.2021; Kang and Zhang, 2021).

Rapid urbanisation and economic development in China have led to a dramatic increase in nitrogen oxide (NO2) emissions, causing serious atmospheric nitrogen pollution and relatively high levels of nitrogen deposition. However, despite the importance of nitrogen deposition, dry deposition processes in forested areas are still insufficiently represented in current global and regional atmospheric chemistry models, which constrains our understanding and prediction of spatial and temporal patterns of nitrogen transport in forest ecosystems in southern China. The offline 1-D community Noah land surface model with multi-parameterisation options (Noah-MP) is coupled with the WRF-Chem dry deposition module (WDDM) and is applied to further understand and identify the key processes that affect forest canopy dry deposition. The canopy stomatal resistance mechanism and the nitrogen-limiting scheme for photosynthesis in Noah-MP-WDDM are modified to improve the simulation of reactive nitrogen oxide dry deposition velocity. This study finds that the combined improved stomatal resistance mechanism and nitrogen-limiting scheme for photosynthesis (BN-23) agree better with the observed NO2 dry deposition velocity, with the mean bias being reduced by 50.1 %. At the same time, by comparing the different mechanisms of the two processes of canopy stomatal resistance and leaf nitrogen-limiting factors, this study also finds that the diurnal changes in dry deposition velocity simulated by each regional model present four sets of distributions. This is mainly due to the different ways that each integrated mechanism handles the opening and closing of stomata at noon and the way the nitrogen-limiting factor acts.

The effects of horizontal resolution on the simulation of tropical cyclones were studied using the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System Finite-Volume version 3 (FGOALS-f3) climate system model from the High-Resolution Model Intercomparison Project (HighResMIP) for the Coupled Model Intercomparison Project phase 6 (CMIP6). Both the low-resolution (about 100 km resolution) FGOALS-f3 model (FGOALS-f3-L) and the high-resolution (about 25 km resolution) FGOALS-f3 (FGOALS-f3-H) models were used to achieve the standard Tier 1 experiment required by HighResMIP. FGOALS-f3-L and FGOALS-f3-H have the same model parameterizations with the exactly the same parameters. The only differences between the two models are the horizontal resolution and the time step. The performance of FGOALS-f3-H and FGOALS-f3-L in simulating tropical cyclones was evaluated using observations. FGOALS-f3-H (25 km resolution) simulated more realistic distributions of the formation, movement and intensity of the climatology of tropical cyclones than FGOALS-f3-L at 100 km resolution. Although the number of tropical cyclones increased by about 50 % at the higher resolution and better matched the observed values in the peak month, both FGOALS-f3-L and FGOALS-f3-H appear to replicate the timing of the seasonal cycle of tropical cyclones. The simulated average and interannual variabilities of the number of tropical cyclones and the accumulated cyclone energy were both significantly improved from FGOALS-f3-L to FGOALS-f3-H over most of the ocean basins. The characteristics of tropical cyclones (e.g., the average lifetime, the wind–pressure relationship and the horizontal structure) were more realistic in the simulation using the high-resolution model. The possible physical linkage between the performance of the tropical cyclone simulation and the horizontal resolution were revealed by further analyses. The improvement in the response between the El Niño–Southern Oscillation and the number of tropical cyclones and the accumulated cyclone energy in FGOALS-f3 contributed to the realistic simulation of tropical cyclones. The genesis potential index and the vorticity, relative humidity, maximum potential intensity and the wind shear terms were used to diagnose the effects of resolution. We discuss the current insufficiencies and future directions of improvement for the simulation of tropical cyclones and the potential applications of the FGOALS-f3-H model in the subseasonal to seasonal prediction of tropical cyclones.

Gross primary productivity (GPP) quantifies the amount of carbon dioxide (CO2) fixed by plants through photosynthesis. Although as a key quantity of terrestrial ecosystems, there is a lack of high-spatial-and-temporal-resolution, real-time and observation-based GPP products. To address this critical gap, here we leverage a state-of-the-art vegetation index, near-infrared reflectance of vegetation (NIRV), along with accurate photosynthetically active radiation (PAR), to produce a SatelLite Only Photosynthesis Estimation (SLOPE) GPP product for the contiguous United States (CONUS). Compared to existing GPP products, the proposed SLOPE product is advanced in its spatial resolution (250 m versus >500 m), temporal resolution (daily versus 8 d), instantaneity (latency of 1 d versus >2 weeks) and quantitative uncertainty (on a per-pixel and daily basis versus no uncertainty information available). These characteristics are achieved because of several technical innovations employed in this study: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR. (2) SLOPE couples highly efficient and pragmatic gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRV (SANIRV) dataset. (3) SLOPE couples a temporal pattern recognition approach with a long-term Cropland Data Layer (CDL) product to predict dynamic C4 crop fraction. Through developing a parsimonious model with only two slope parameters, the proposed SLOPE product explains 85 % of the spatial and temporal variations in GPP acquired from 49 AmeriFlux eddy-covariance sites (324 site years), with a root-mean-square error (RMSE) of 1.63 gC m−2 d−1. The median R2 over C3 and C4 crop sites reaches 0.87 and 0.94, respectively, indicating great potentials for monitoring crops, in particular bioenergy crops, at the field level. With such a satisfactory performance and its distinct characteristics in spatiotemporal resolution and instantaneity, the proposed SLOPE GPP product is promising for biological and environmental research, carbon cycle research, and a broad range of real-time applications at the regional scale. The archived dataset is available at https://doi.org/10.3334/ORNLDAAC/1786 (download page: https://daac.ornl.gov/daacdata/cms/SLOPE_GPP_CONUS/data/, last access: 20 January 2021) (Jiang and Guan, 2020), and the real-time dataset is available upon request.

The lower parts of two glaciers in the Aru range on the western Tibetan Plateau (TP) collapsed on 17 July and 21 September 2016, respectively, causing fatal damage to local people and their livestock. The giant ice avalanches, with a total volume of 150 × 106 m3, had almost melted by September 2019 (about 30 % of the second ice avalanche remained). The impact of these extreme disasters on downstream lakes has not been investigated yet. Based on in situ observation, bathymetry survey and satellite data, we explore the impact of the ice avalanches on the two downstream lakes (i.e., Aru Co and Memar Co) in terms of lake morphology, water level and water temperature in the subsequent 4 years (2016–2019). After the first glacier collapse, the ice avalanche slid into Aru Co along with a large amount of debris, which generated great impact waves in Aru Co and significantly modified the lake's shoreline and underwater topography. An ice volume of at least 7.1 × 106 m3 was discharged into Aru Co, spread over the lake surface and considerably lowered its surface temperature by 2–4 ∘C in the first 2 weeks after the first glacier collapse. Due to the large amount of meltwater input, Memar Co exhibited more rapid expansion after the glacier collapses (2016–2019) than before (2003–2014), in particular during the warm season. The melting of ice avalanches was found to contribute to about 23 % of the increase in lake storage between 2016 and 2019. Our results indicate that the Aru glacier collapses had both short-term and long-term impacts on the downstream lakes and provide a baseline in understanding the future lake response to glacier melting on the TP under a warming climate.

Purpose: Bats are the natural reservoir hosts for many viral zoonotic pathogens including lyssaviruses that can cause the fatal disease rabies. Lagos bat lyssavirus (LBV), a member of phylogroup II lyssaviruses, has been classified into four lineages (A, B, C and D). There is minimal information of LBV lineages circulating in fruit bat populations in Nigeria, despite that the bat lyssavirus (LBV-B) was first isolated in Nigeria in 1956. This study was undertaken to assess the levels of neutralising antibodies against four lineages of LBVs in straw-coloured fruit bats (Eidolon helvum) in Makurdi, Nigeria. Methods & Materials: Serum samples (n=180) were collected during two consecutive seasons between (November 2017 – March 2018 and November 2018 – March 2019) from terminally bled bats captured for human consumption and tested using a modified fluorescent antibody virus neutralisation (mFAVN) assay. Results: The data showed that a high number of bat sera (73%) neutralised at least one lineage of LBV with the reciprocal titre values ranging from 9 – > 420.89. Many sera (n=107) neutralised more than one lineages of LBV while 24 serum samples neutralised only one lineage, i.e. LBV-A (n=17), LBV-D (n=6), LBV-C (n=1) and LBV-B (n=0). Conclusion: The high seroprevalence of neutralising antibodies suggested that the exposures to LBVs were common and LBV- A (and possibly C and D) were circulating amongst those bats whereas LBV-B was unlikely to be present. The infected bats could pose a danger to their handlers and consumers.

Assimilating observations of shallow soil moisture content into land models is an important step in estimating soil moisture content. In this study, several modifications of an ensemble Kalman filter (EnKF) are proposed for improving this assimilation. It was found that a forecast error inflation-based approach improves the soil moisture content in shallow layers, but it can increase the analysis error in deep layers. To mitigate the problem in deep layers while maintaining the improvement in shallow layers, a vertical localization-based approach was introduced in this study. During the data assimilation process, although updating the forecast state using observations can reduce the analysis error, the water balance based on the physics in the model could be destroyed. To alleviate the imbalance in the water budget, a weak water balance constrain filter is adopted. The proposed weakly constrained EnKF that includes forecast error inflation and vertical localization was applied to a synthetic experiment. An additional bias-aware assimilation for reducing the analysis bias is also investigated. The results of the assimilation process suggest that the inflation approach effectively reduces the analysis error from 6.70 % to 2.00 % in shallow layers but increases from 6.38 % to 12.49 % in deep layers. The vertical localization approach leads to 6.59 % of the analysis error in deep layers, and the bias-aware assimilation scheme further reduces this to 6.05 %. The spatial average of the water balance residual is 0.0487 mm of weakly constrained EnKF scheme, and 0.0737 mm of a weakly constrained EnKF scheme with inflation and localization, which are much smaller than the 0.1389 mm of the EnKF scheme.

Early life stages of marine fish populations may be strongly affected by environmental factors. Changes in the physical environment or the availability of food resources could lead to stress-related physiological responses affecting larval fitness, growth and survival. In the present study, we determined, for the first time, amino acid composition (AAC), lipid, and carbohydrate content, as well as alkaline phosphatase and peroxidase activities in larvae from the European anchovy Engraulis encrasicolus. Fishes were caught in two different spawning areas of the Strait of Sicily, characterized by different environmental conditions, including a coastal upwelling with a lower temperature (Adventure Bank; 20.22 ± 0.38°C) and a thermohaline front with a higher temperature (Maltese Bank 23.10 ± 0.25°C). The results showed that the two groups of larvae, in their early life, had similar nutritional status. However, compared with the samples from the Maltese Bank, the specimens collected in the Adventure Bank area exhibited higher alkaline phosphatase activity, lower concentrations of aspartate plus asparagine, threonine, and arginine but a higher concentration of leucine, highlighting different patterns of amino acid metabolism. Collectively, these results indicated that AAC analysis could represent an additional valid tool to evaluate the link between physiological responses and environmental conditions at early life stages.

Whether for cancer diagnosis or single-cell analysis, it remains a major challenge to isolate the target sample cells from a large background cell for high-efficiency downstream detection and analysis in an integrated chip. Therefore, in this paper, we propose a 3D-stacked multistage inertial microfluidic sorting chip for high-throughput enrichment of circulating tumor cells (CTCs) and convenient downstream analysis. In this chip, the first stage is a spiral channel with a trapezoidal cross-section, which has better separation performance than a spiral channel with a rectangular cross-section. The second and third stages adopt symmetrical square serpentine channels with different rectangular cross-section widths for further separation and enrichment of sample cells reducing the outlet flow rate for easier downstream detection and analysis. The multistage channel can separate 5 μm and 15 μm particles with a separation efficiency of 92.37% and purity of 98.10% at a high inlet flow rate of 1.3 mL/min. Meanwhile, it can separate tumor cells (SW480, A549, and Caki-1) from massive red blood cells (RBCs) with a separation efficiency of >80%, separation purity of >90%, and a concentration fold of ~20. The proposed work is aimed at providing a high-throughput sample processing system that can be easily integrated with flowing sample detection methods for rapid CTC analysis.

Abstract Ginkgo biloba is a traditional Chinese herbal medicine containing multiple components that contribute to its notable bioactivities. Variations of seasonal, meteorological and planting soil on the phytochemicals contents in G. biloba leaves due to the effects of growth meteorological and soil parameters were investigated in this study. The leaves of G. biloba were collected from different months and place in Zhejiang province, the contents of flavones (quercetin, kaempferol and isorhamnetin) and terpene lactones (bilobalide, ginkgolides A, B and C) were quantified by high performance liquid chromatography (HPLC) and the evaporative light scattering detector (ELSD) method. The established methods were validated with good linearity, precision, repeatability, stability, and recovery. Comprehensive analysis suggested the proper harvest time for G. biloba was in October of Zhejiang province. The result of correlation analysis with meteorological factors shows that the temperature and precipitation have non-significant effect on the main components of G. biloba. In addition, the type and content (Mn and Zn) of the soil showed significantly effect on the content of flavonoids and terpene lactones. This study enriched the knowledge on the development and utilization value of the G. biloba leaves and was useful for determining the optimal harvest time and growing condition.

Mineral dust particles play an important role in the Earth system, imposing a variety of effects on air quality, climate, human health, and economy. Accurate forecasts of dust events are highly desirable to provide an early warning and inform the decision-making process. East Asia is one of the largest dust sources in the world. This study applies and evaluates four widely used regional air quality models to simulate dust storms in northeastern China. Three dust schemes in the Weather Research and Forecasting model with Chemistry (WRF-Chem) (version 3.9.1), two schemes in both CHIMERE (version 2017r4) and CMAQ (version 5.2.1), and one scheme in CAMx (version 6.50) were applied to a dust event during 4–6 May 2015 in northeastern China. Most of these models were able to capture this dust event with the exception of CAMx, which has no dust source map covering the study area; hence, another dust source mask map was introduced to replace the default one for the subsequent simulation. Although these models reproduced the spatial pattern of the dust plume, there were large discrepancies between predicted and observed PM10 concentrations in each model. In general, CHIMERE had relatively better performance among all simulations with default configurations. After parameter tuning, WRF-Chem with the Air Force Weather Agency (AFWA) scheme using a seasonal dust source map from Ginoux et al. (2012) showed the best performance, followed by WRF-Chem with the UOC_Shao2004 scheme, CHIMERE, and CMAQ. The performance of CAMx had significantly improved by substituting the default dust map and removing the friction velocity limitation. This study suggested that the dust source maps should be carefully selected on a regional scale or replaced with a new one constructed with local data. Moreover, further study and measurement of sandblasting efficiency of different soil types and locations should be conducted to improve the accuracy of estimated vertical dust fluxes in air quality models.

Currently, the bearings of Poyanghu Bridge, a 636-meter long cable-stayed bridge, have been damaged. According to numerical analyses, the mechanical state of the damaged bridge unfavorably deviates from the ideal design state, and the bridge should be repaired in time to restore its safety and serviceability. However, compared with the bearing repair of beam bridges, much less scientific and engineering endeavors have been made in the history to direct the bearing repair of cable-stayed bridges. This article proposes two innovative bearing repair schemes for cable-stayed bridges and reports the numerical validations, the on-location applications, and the monitoring of the proposed repair schemes under the engineering backgxround of Poyanghu Bridge. Through these works, it is found that the proposed repair schemes are effective in practical use.

Cryoconite is a mixture of impurities and ice visually represented by dark colors present in the ablation zone of glaciers. As an important constituent of light-absorbing impurities on the glacier surface, iron oxides influence the radiative properties of mineral dust and thus its impact on ice melting processes. In particular, the distinct optical properties between hematite and goethite (the major iron oxide species) highlight the necessity to obtain accurate knowledge about their abundance and geochemical behavior. Cryoconite samples from five glaciers in different regions of the Tibetan Plateau (TP) and surroundings were studied. The iron abundance in the cryoconite from TP glaciers ranged from 3.40 % to 4.90 % by mass, in accordance with typical natural background levels. Because the light absorption capacity of mineral dust essentially depends on the presence of iron oxides (i.e., free iron), iron oxides were extracted and determined using diffuse reflectance spectroscopy. The ratios of free to total iron for the five glaciers ranged from 0.31 to 0.70, emphasizing that iron in the form of oxides should be considered rather than total iron in the albedo and radiative modeling. Furthermore, the goethite content in iron oxides (in mass fraction) ranged from 81 % to 98 %, showing that goethite was the predominant form among the glaciers. Using the abundance and speciation of iron oxides as well as their optical properties, the total light absorption was quantitatively attributed to goethite, hematite, black carbon (BC) and organic matters at 450 and 600 nm wavelengths. We found that the goethite played a stronger role than BC at shorter wavelengths for most glaciers. Such findings were essential to understand the relative significance of anthropogenic and natural effects, and then taking the proper mitigation measures.

Disaster preparedness is critical for reducing potential impact. This paper contributes to current knowledge of disaster preparedness using representative national sample data from China, which faces high earthquake risks in many areas of the country. The adoption of earthquake preparedness activities by the general public, including five indicators of material preparedness and five indicators of awareness preparedness, were surveyed and 3245 respondents from all 31 provinces of Mainland China participated in the survey. Linear regression models and logit regression models were used to analyze the effects of potential influencing factors. Overall, the preparedness levels are not satisfied, with a material preparation score of 3.02 (1–5), and awareness preparation score of 2.79 (1–5), nationally. Meanwhile, residents from western China, which has higher earthquake risk, have higher degrees of preparedness. The concern for disaster risk reduction (DRR) and the concern for building safety and participation in public affairs are consistent positive predictors of both material and awareness preparedness. The demographic and socioeconomic variables' effects, such as gender, age, education, income, urban/rural division, and building size, vary according to different preparedness activities. Finally, the paper concludes with a discussion of the theoretical contribution and potential implementation.

Abstract We present possible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals, and study the capability of the network to determine the sky location of the source. We report our findings for gravitational-wave transients, with particular focus on gravitational-wave signals from the inspiral of binary neutron star systems, which are the most promising targets for multi-messenger astronomy. The ability to localize the sources of the detected signals depends on the geographical distribution of the detectors and their relative sensitivity, and $$90\%$$ 90% credible regions can be as large as thousands of square degrees when only two sensitive detectors are operational. Determining the sky position of a significant fraction of detected signals to areas of 5–$$20~\mathrm {deg}^2$$ 20deg2 requires at least three detectors of sensitivity within a factor of $$\sim 2$$ ∼2 of each other and with a broad frequency bandwidth. When all detectors, including KAGRA and the third LIGO detector in India, reach design sensitivity, a significant fraction of gravitational-wave signals will be localized to a few square degrees by gravitational-wave observations alone.

The ensemble Kalman filter (EnKF) is a widely used ensemble-based assimilation method, which estimates the forecast error covariance matrix using a Monte Carlo approach that involves an ensemble of short-term forecasts. While the accuracy of the forecast error covariance matrix is crucial for achieving accurate forecasts, the estimate given by the EnKF needs to be improved using inflation techniques. Otherwise, the sampling covariance matrix of perturbed forecast states will underestimate the true forecast error covariance matrix because of the limited ensemble size and large model errors, which may eventually result in the divergence of the filter. In this study, the forecast error covariance inflation factor is estimated using a generalized cross-validation technique. The improved EnKF assimilation scheme is tested on the atmosphere-like Lorenz-96 model with spatially correlated observations, and is shown to reduce the analysis error and increase its sensitivity to the observations.

To better understand the characteristics of biomass burning in the northern Indo-Gangetic Plain (IGP), total suspended particles were collected in a rural site, Lumbini, Nepal, during April 2013 to March 2014 and analyzed for the biomass burning tracers (i.e., levoglucosan, mannosan, vanillic acid). The annual average concentration of levoglucosan was 734 ± 1043 ng m−3 with the maximum seasonal mean concentration during post-monsoon season (2206 ± 1753 ng m−3), followed by winter (1161 ± 1347 ng m−3), pre-monsoon (771 ± 524 ng m−3) and minimum concentration during monsoon season (212 ± 279 ng m−3). The other biomass burning tracers (mannosan, galactosan, p-hydroxybenzoic acid, vanillic acid, syringic acid and dehydroabietic acid) also showed the similar seasonal variations. There were good correlations among levoglucosan, organic carbon (OC) and elemental carbon (EC), indicating significant impact of biomass burning activities on carbonaceous aerosol loading throughout the year in Lumbini area. According to the characteristic ratios, levoglucosan ∕ mannosan (lev ∕ man) and syringic acid ∕ vanillic acid (syr ∕ van), we deduced that the high abundances of biomass burning products during non-monsoon seasons were mainly caused by the burning of crop residues and hardwood while the softwood had less contribution. Based on the diagnostic tracer ratio (i.e., lev ∕ OC), the OC derived from biomass burning constituted large fraction of total OC, especially during post-monsoon season. By analyzing the MODIS fire spot product and 5-day air-mass back trajectories, we further demonstrated that organic aerosol composition was not only related to the local agricultural activities and residential biomass usage but also impacted by the regional emissions. During the post-monsoon season, the emissions from rice residue burning in western India and eastern Pakistan could impact particulate air pollution in Lumbini and surrounding regions in southern Nepal. Therefore, our finding is meaningful and has a great importance for adopting the appropriate mitigation measures, not only at the local level but also by involving different regions and nations, to reduce the biomass burning emissions in the broader IGP region nations.

The establishment of grasslands on abandoned cropland has been proposed as an effective method to mitigate climate change. In this study, five cultivated grasslands (three leguminous species and two gramineous species), one abandoned cropland, and one natural grassland were studied to examine how soil organic carbon (SOC) sequestration rate and sequestration efficiency change in a semi-arid area in China. Our results showed that leguminous grasslands had greater total biomass (above- and belowground biomass), SOC storage, SOC sequestration rate, and efficiency than gramineous grasslands, abandoned cropland, and natural grassland during the experimental period. The largest soil carbon (C) accumulation in leguminous grassland was mainly attributed to the capacity to incorporate C and the higher biomass production. Leguminous grasslands accumulated more SOC than gramineous grasslands by 0.64 Mg C ha−1 yr−1. The average SOC sequestration efficiency in leguminous grassland (1.00) was about 2 times greater than gramineous grassland (0.34). The results indicate that cultivated leguminous grassland sequestered more SOC with higher SOC sequestration efficiency than cultivated gramineous grassland in arid and semi-arid areas. Our results provide a reference for ecological management in arid and semi-arid areas.

Hotpot meat is a popular way of meat consumption in some Asian countries. This study was carried out to investigate the effect of visible fat content on consumer acceptability of hotpot meat. Hotpot beef with six visible fat levels (11%–35%) was produced and digitally photographed, and the images were ranked by panels of New Zealand Chinese (110), Japanese (145), and Korean (118) consumers. For all the nationalities, a preference for visible fat was influenced by both gender and age. The Chinese preferred the visibly fattiest hotpot beef, whereas the Koreans preferred the leanest with the Japanese preferring the two fat extremes equally. For individuals in the age range of 19–30 years, both Chinese males and females preferred the higher fat meat (35%), while their Japanese and Korean counterparts preferred the second visibly leanest (14%). For those over 50 years, Chinese females preferred the lower fat meat compared to their male counterparts, whereas there was no gender difference at this age for the Japanese and Koreans preference for the visibly lean hotpot beef. This study indicates that there are subtle differences between nationalities in terms of their preference for the fat content of hotpot beef that may have implications in meat merchandising, product development, and health policies.

The simulation of rainfall-runoff process is essential for disaster emergency and sustainable development. One common disadvantage of the existing conceptual hydrological models is that they are highly dependent upon specific spatial-temporal contexts. Meanwhile, due to the inter-dependence of adjacent flow paths, it is still difficult for the RS or GIS supported distributed hydrological models to achieve high-performance application in real world applications. As an attempt to improve the performance efficiencies of those models, this study presents a high-performance rainfall-runoff simulating framework based on the flow path network and a separate particle system. The vector-based flow path lines are topologically linked to constrain the movements of independent rain drop particles. A separate particle system, representing surface runoff, is involved to model the precipitation process and simulate surface flow dynamics. The trajectory of each particle is constrained by the flow path network and can be tracked by concurrent processors in a parallel cluster system. The result of speedup experiment shows that the proposed framework can significantly improve the simulating performance just by adding independent processors. By separating the catchment elements and the accumulated water, this study provides an extensible solution for improving the existing distributed hydrological models. Further, a parallel modeling and simulating platform needs to be developed and validate to be applied in monitoring real world hydrologic processes.

Lake droughts are the consequence of climatic, hydrologic and anthropogenic influences. Quantification of droughts and estimation of the contributions from the individual factors are essential for understanding drought features and their causation structure. This is also important for policymakers to make effective adaption decisions, especially under changing climate. This study examines Poyang Lake, China's largest freshwater lake, which has been undergoing drastic hydrological alternation in the past decade. Standardized lake stage is used to identify and quantify the lake droughts, and hydroclimatic contributions are determined with a water budget analysis, in which absolute deficiency is defined in reference to normal hydrologic conditions. Our analyses demonstrate that in the past decade the lake droughts worsened in terms of duration, frequency, intensity and severity. Hydroclimatic contributions to each individual drought varied between droughts, and the overall contribution to the lake droughts in the past decade came from decreased inflow, increased outflow, and reduced precipitation and increased evapotranspiration in the lake region. The decreased inflow resulted mainly from reduced precipitation and less from increased evapotranspiration over the Poyang Lake basin. The increased outflow was attributable to the weakened blocking effects of the Yangtze River, which the Three Gorges Dam (TGD) established upstream. The TGD impoundments were not responsible for the increased number of drought events, but they may have intensified the droughts and changed the frequency of classified droughts. However, the TGD contribution is limited in comparison with hydroclimatic influences. Hence, the recently increased droughts were due to hydroclimatic effects, with a less important contribution from anthropogenic influences.

Polyhydroxyalkanoates are a family of natural polyesters being produced as intracellular carbon and energy reserves by a wide variety of microorganisms. They have developed rapidly in both research and development efforts globally in the last 15 years. Till now, over 100 different types of PHAs have been successfully biosynthesized using both genetic engineering and fermentation techniques. Their unique biodegradable, biocompatible and thermoplastic characteristics make PHAs promising candidates for the commodity and biomedical applications. This review focused on the chemical synthesis of the derivatives of the biosynthesized PHAs.

Hyporheic exchange is of great significance for evaluating and developing water resources, as well as protecting ecosystem health. Temperature monitoring is one of the powerful tools for recognizing the hyporheic flux with high precision, low cost and great convenience. The streambed temperature at different depths (0 to 1.00 m), and the air and stream water temperatures at Dawen River, Jining City, were monitored using distributed temperature sensors (DTS). The temperature series were used to estimate the hyporheic flux through the analytical solution of the governing one-dimensional heat transport equation. The temporal patterns of flux along the vertical profile were analysed. The results indicated that surface water and air temperatures fluctuated approximately sinusoidally, and the groundwater temperature was relatively stable over time. The hyporheic flux at different depths showed different temporal patterns. Moreover, the dynamic curves of hyporheic flux were depth-dependent and probably controlled by the stream water level and groundwater field.

A Global Carbon Assimilation System based on the ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments, including inclusion of atmospheric CO2 concentration in state vectors, using the ensemble Kalman filter (EnKF) with 1-week assimilation windows, using analysis states to iteratively estimate ensemble forecast errors, and a maximum likelihood estimation of the inflation factors of the forecast and observation errors. The proposed assimilation approach is used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO2 distributions from 2002 to 2008. The results show that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.

High temporal resolution measurements of black carbon (BC) and organic carbon (OC) covering the time period of 1956–2006 in an ice core over the southeastern Tibetan Plateau show a distinct seasonal dependence of BC and OC with higher respective concentrations but a lower OC / BC ratio in the non-monsoon season than during the summer monsoon. We use a global aerosol-climate model, in which BC emitted from different source regions can be explicitly tracked, to quantify BC source–receptor relationships between four Asian source regions and the southeastern Tibetan Plateau as a receptor. The model results show that South Asia has the largest contribution to the present-day (1996–2005) mean BC deposition at the ice-core drilling site during the non-monsoon season (October to May) (81%) and all year round (74%), followed by East Asia (14% to the non-monsoon mean and 21% to the annual mean). The ice-core record also indicates stable and relatively low BC and OC deposition fluxes from the late 1950s to 1980, followed by an overall increase to recent years. This trend is consistent with the BC and OC emission inventories and the fuel consumption of South Asia (as the primary contributor to annual mean BC deposition). Moreover, the increasing trend of the OC / BC ratio since the early 1990s indicates a growing contribution of coal combustion and/or biomass burning to the emissions. The estimated radiative forcing induced by BC and OC impurities in snow has increased since 1980, suggesting an increasing potential influence of carbonaceous aerosols on the Tibetan glacier melting and the availability of water resources in the surrounding regions. Our study indicates that more attention to OC is merited because of its non-negligible light absorption and the recent rapid increases evident in the ice-core record.

Biocompatible and biodegradable carboxymethyl cellulose (CMC) has been modified with 4-hydroxybenzylamine (CMC-Ph) in order to prepare CMC-based microgels through the horseradish peroxidise/hydrogen peroxide enzymatic reaction. CMC-Ph was identified as a blend, and the amount of the grafted 4-hydroxybenzylamine per 100 units of CMC was between 17 and 23 according to the molecular weight of CMC. Through a special designed co-flowing microfluidic device, CMC-Ph microgels were prepared with the radius from 100 to 500 μm via adjusting the flow rates of the disperse phase and the continuous phase, respectively. The chondrocytic cell line ATDC5 was encapsulated in the CMC-Ph microgels. The cell-laden microgels were cultured for up to 40 days, illustrating the biocompatibility of CMC-Ph and the microfluidic approach through the enzymatic crosslinking reaction primarily. CMC-Ph showed a great promise to encapsulate the cells for further fabrication of the injectable scaffolds.

Transgenic CrylAc and CpTI insect-resistant cotton SGK321 is widely adopted for many years in several regions of China, however the understanding of its potential effects on soil enzyme activities is not studied. The impacts of transgenic cotton SGK321 on dehydrogenase, urease and phosphatase activities in rhizosphere soil were investigated in a two-year field study in Northern China. Rhizosphere soil enzyme activities between transgenic cotton SGK321 and its non-transgenic parental cotton Shiyuan 321 were found to differ at senescence. However compared to the plant growth stages and cotton cultivar, the impacts of the transgenic trait were minor or transient. The principal component analysis also showed no significant or minor difference in the activities of dehydrogenase, urease and phosphatase in the rhizosphere soil of transgenic cotton SGK321 and its counterpart. Our results indicated that the transgenic cotton SGK321 has no apparent impact on dehydrogenase, urease and phosphatase activities in rhizosphere soil.