羧乙基壳聚糖蒙脱石吸附养殖水体中Cu2+的应用

为了寻求性能良好、环保吸附剂,用于去除养殖水体中重金属Cu~(2+),作者利用蒙脱石负载羧乙基壳聚糖制备成复合吸附剂,并利用IR、SEM、XRD等手段分析其表面性能,将其用于处理Cu~(2+)溶液,考察了环境因子对其吸附性能的影响,并从吸附动力学和吸附热力学角度分析吸附剂对Cu~(2+)的吸附机理,最后考察其再生利用效果。结果表明:羧乙基壳聚糖成功进入到蒙脱石层间;在羧乙基壳聚糖与蒙脱石质量比为1︰25、40℃恒温水浴搅拌60min、pH=6.0、最佳投加量为4.0g/L、处理浓度不超过30 mg/L Cu~(2+)溶液时,复合吸附剂对Cu~(2+)去除率可以达到96.23%,将其用于淡水养殖鱼塘水体中, Cu~(2+)去除后可达到《渔业水质标准》规定;吸附剂对Cu~(2+)吸附热力学实验结果表明,符合Langmuir模型,反应过程为自发、吸热反应;吸附动力学结果表明该吸附符合准二级动力学方程,反应属于化学吸附;再生实验中NaOH的再生效果优于HCl。     

琼胶/SiO2复合纤维的制备及性能研究

利用湿法纺丝技术制备了琼胶/SiO₂复合纤维,对琼胶分子在溶液中的分散性、纺丝液流变性、纤维的形貌、化学结构分别用DLS、旋转黏度计、SEM、FTIR和XRD进行了表征,并对纤维的力学性能、热性能和吸湿性能进行了测定。研究结果表明：琼胶分子在溶液中呈纳米尺度分布,纺丝液具有良好的流动性;琼胶/纳米SiO₂复合纤维具有良好的形态。随着纳米SiO₂的添加量逐渐提高,复合纤维的力学拉伸强度先增强后降低,复合纤维的吸水性降低,复合纤维的热稳定性逐渐增强。结合复合纤维综合性能,纳米SiO₂的最佳添加质量分数为0.5%。     

基于核函数NPSSB模型的HY-2A卫星雷达高度计海况偏差研究

利用机器学习的方法,对14个周期HY-2A卫星高度计数据:风速、有效波高和海面高度差值进行训练,探究海况偏差和风速、有效波高之间的关系,创建海况偏差核函数非参数模型(NPSSB),并与参数模型中具有代表性的BM3、BM4模型进行对比。研究表明:(1)核函数NPSSB模型能够很好的反映SSB与U、SWH之间的关系,SSB与U呈二次函数关系,SSB与SWH呈反比例函数关系;(2)核函数NPSSB模型对SSB的模拟能力与训练数据集相关,数据量越多,模拟能力越好;(3)核函数NPSSB模型与BM3、BM4模型都存在0^-0.03 m的差值,随着风速和有效波高的增加,差值的绝对值越大。     

Cu2+对序批式反应器中活性污泥胞外聚合物产量及其组分的影响

研究了长期暴露条件下Cu2+对序批式反应器(SBR)性能及其活性污泥胞外聚合物(EPS)特性的影响。结果表明,进水中加入10 mg·L-1的Cu2+后,在SBR运行的第16~55天,COD和NH+4-N的去除率保持稳定;在第56~75天,COD和NH+4-N的平均去除率与进水Cu2+浓度为0 mg·L-1时相比分别下降了3.88%和6.41%。浓度为10 mg·L-1的Cu2+长期作用下,活性污泥中EPS、松散附着EPS(LB-EPS)和紧密附着EPS(TB-EPS)产量及LB-EPS和TB-EPS中蛋白质(PN)含量增加。傅里叶变换红外光谱分析表明10 mg·L-1 Cu2+的长期暴露导致TB-EPS中PN的C=O键、N-H键和C-O键相对含量降低。X射线光电子能谱(XPS)测试结果显示在10 mg·L-1 Cu2+长期暴露条件下,LB-EPS和TB-EPS中元素Cu和O百分含量增加。     

东昆仑祁漫塔格地区乌兰乌珠尔早古生代花岗岩锆石U-Pb年代学、地球化学及其地质意义

为确定东昆仑祁漫塔格乌兰乌珠尔地区片麻状黑云母花岗岩和二长花岗岩的形成时代、岩石成因、源区性质和构造背景,对该岩石样品进行了锆石U-Pb年代学、地球化学和锆石Hf同位素研究.结果显示:片麻状黑云母花岗岩加权平均年龄为457.5±2.3 Ma,铝饱和指数A/CNK介于0.98～1.02,属准铝质岩石,Na2O/K2O比值...     

Using Mesoproterozoic sedimentary geochemistry to reconstruct basin tectonic geography and link organic carbon productivity to nutrient flux from a Northern Australian large igneous Province

The Beetaloo Sub-basin, northern Australia, is considered the main depocentre of the 1,000-km scale Mesoproterozoic Wilton package of the greater McArthur Basin – the host to one of the oldest hydrocarbon global resources. The ca. 1.40–1.31 Ga upper Roper Group and the latest Mesoproterozoic to early Neoproterozoic unnamed group of the Beetaloo Sub-basin, together, record ca. 500 million years of depositional history within the North Australia Craton. Whole-rock shale Sm–Nd and Pb isotope data from these sediments reveal sedimentary provenance and their evolution from ca. 1.35 to 0.85 Ga. Furthermore, these data, together with shale major/trace elements data from this study and pyrolysis data from previous publications, are used to develop a dynamic tectonic geography model that links the organic carbon production and burial to an enhanced weathering of nutrients from a large igneous province. The ca. 1.35–1.31 Ga Kyalla Formation of the upper Roper Group is composed of isotopically evolved sedimentary detritus that passes up, into more isotopically juvenile Pb values towards the top of the formation. The increase in juvenile compositions coincides with elevated total organic carbon (TOC) contents of these sediments. The coherently enriched juvenile compositions and TOC the upper portions of the Kyalla Formation are interpreted to reflect an increase in nutrient supply associated with the weathering of basaltic sources (e.g. phosphorous). Possible, relatively juvenile, basaltic sources include the Wankanki Supersuite in the western Musgraves and the Derim Derim–Galiwinku large igneous province (LIP). The transition into juvenile, basaltic sources directly before a supersequence-bounding unconformity is here interpreted to reflect uplift and erosion of the Derim Derim–Galiwinku LIP, rather than an influx of southern Musgrave sources. A new baddeleyite crystallisation age of 1,312.9 ± 0.7 Ma provides both a tight constraint on the age of this LIP, along with its associated magmatic uplift, as well as providing a minimum age constraint for Roper Group deposition. The unconformably overlying lower and upper Jamison sandstones are at least 300 million years younger than the Kyalla Formation and were sourced from the Musgrave Province. An up-section increase in isotopically juvenile compositions seen in these rocks is interpreted to document the progressive exhumation of the western Musgrave Province. The overlying Hayfield mudstone received detritus from both the Musgrave and Arunta regions, and its isotopic geochemistry reveals affinities with other early Neoproterozoic basins (e.g. Amadeus, Victoria and Officer basins), indicating the potential for inter-basin correlations.     

Targeting rare earth element bearing mine tailings on Bangka Island,Indonesia, with Sentinel-2 MSI

A laboratory study on rare earth element bearing mine tailings, collected from Bangka Island, Indonesia, reported a new spectral absorption feature at 674 nm associated with Erbium. The present study aims to evaluate the capability of the European Space Agency’s Sentinel-2 MSI sensors to detect this absorption feature from space. An arithmetic band operation is performed on selected visible and near-infrared spectral bands of a Sentinel-2 image. The results show that Sentinel-2 MSI is capable of detecting the 674 nm Erbium-related absorption feature within the particular environmental setting of the study area.     

Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots,UAV-LiDAR data and Sentinel-2 imagery

The mangrove forests of northeast Hainan Island are the most species diverse forests in China and consist of the Dongzhai National Nature Reserve and the Qinglan Provincial Nature Reserve. The former reserve is the first Chinese national nature reserve for mangroves and the latter has the most abundant mangrove species in China. However, to date the aboveground ground biomass (AGB) of this mangrove region has not been quantified due to the high species diversity and the difficulty of extensive field sampling in mangrove habitat. Although three-dimensional point clouds can capture the forest vertical structure, their application to large areas is hindered by the logistics, costs and data volumes involved. To fill the gap and address this issue, this study proposed a novel upscaling method for mangrove AGB estimation using field plots, UAV-LiDAR strip data and Sentinel-2 imagery (named G∼LiDAR∼S2 model) based on a point-line-polygon framework. In this model, the partial-coverage UAV-LiDAR data were used as a linear bridge to link ground measurements to the wall-to-wall coverage Sentinel-2 data. The results showed that northeast Hainan Island has a total mangrove AGB of 312,806.29 Mg with a mean AGB of 119.26 Mg ha⁻¹. The results also indicated that at the regional scale, the proposed UAV-LiDAR linear bridge method (i.e., G∼LiDAR∼S2 model) performed better than the traditional approach, which directly relates field plots to Sentinel-2 data (named the G∼S2 model) (R² = 0.62 > 0.52, RMSE = 50.36 Mg ha⁻¹<56.63 Mg ha⁻¹). Through a trend extrapolation method, this study inferred that the G∼LiDAR∼S2 model could decrease the number of field samples required by approximately 37% in comparison with those required by the G∼S2 model in the study area. Regarding the UAV-LiDAR sampling intensity, compared with the original number of LiDAR plots, 20% of original linear bridges could produce an acceptable accuracy (R² = 0.62, RMSE = 51.03 Mg ha⁻¹). Consequently, this study presents the first investigation of AGB for the mangrove forests on northeast Hainan Island in China and verifies the feasibility of using this mangrove AGB upscaling method for diverse mangrove forests.     

Mapping wetland characteristics using temporally dense Sentinel-1 and Sentinel-2 data: A case study in the St. Lucia wetlands,South Africa

Wetlands have been determined as one of the most valuable ecosystems on Earth and are currently being lost at alarming rates. Large-scale monitoring of wetlands is of high importance, but also challenging. The Sentinel-1 and -2 satellite missions for the first time provide radar and optical data at high spatial and temporal detail, and with this a unique opportunity for more accurate wetland mapping from space arises. Recent studies already used Sentinel-1 and -2 data to map specific wetland types or characteristics, but for comprehensive wetland characterisations the potential of the data has not been researched yet. The aim of our research was to study the use of the high-resolution and temporally dense Sentinel-1 and -2 data for wetland mapping in multiple levels of characterisation. The use of the data was assessed by applying Random Forests for multiple classification levels including general wetland delineation, wetland vegetation types and surface water dynamics. The results for the St. Lucia wetlands in South Africa showed that combining Sentinel-1 and -2 led to significantly higher classification accuracies than for using the systems separately. Accuracies were relatively poor for classifications in high-vegetated wetlands, as subcanopy flooding could not be detected with Sentinel-1’s C-band sensors operating in VV/VH mode. When excluding high-vegetated areas, overall accuracies were reached of 88.5% for general wetland delineation, 90.7% for mapping wetland vegetation types and 87.1% for mapping surface water dynamics. Sentinel-2 was particularly of value for general wetland delineation, while Sentinel-1 showed more value for mapping wetland vegetation types. Overlaid maps of all classification levels obtained overall accuracies of 69.1% and 76.4% for classifying ten and seven wetland classes respectively.     

Winter cover crops in Dutch maize fields: Variability in quality and its drivers assessed from multi-temporal Sentinel-2 imagery

Planting a cover crop between the main cropping seasons is an agricultural management measure with multiple potential benefits for sustainable food production. In the maize production system of the Netherlands, an effective establishment of a winter cover crop is important for reducing nitrogen leaching to groundwater. Cover crop establishment after maize cultivation is obliged by law for sandy soils and consequently implemented on nearly all maize fields, but the winter-time vegetative ground cover varies significantly between fields. The objectives of this study are to assess the variability in winter vegetative cover and evaluate to what extent this variability can be explained by the timing of cover crop establishment and weather conditions in two growing seasons (2017–2018). We used Sentinel-2 satellite imagery to construct NDVI time series for fields known to be cultivated with maize within the province of Overijssel. We fitted piecewise logistic functions to the time series in order to estimate cover crop sowing date and retrieve the fitted NDVI value for 1 December (NDVI_Dec). We used NDVI_Dec to represent the quality of cover crop establishment at the start of the winter season. The Sentinel-2 estimated sowing dates compared reasonably with ground reference data for eight fields (RMSE = 6.6 days). The two analysed years differed considerably, with 2018 being much drier and warmer during summer. This drought resulted in an earlier estimated cover crop sowing date (on average 19 days) and an NDVI_Dec value that was 0.2 higher than in 2017. Combining both years and all fields, we found that Sentinel-2 retrieved sowing dates could explain 55% of the NDVI_Dec variability. This corresponded to a positive relationship (R² = 0.50) between NDVI_Dec and the cumulative growing degree days (GDD) between sowing date and 1 December until reaching 400 GDD. Based on cumulative GDD derived from two weather stations within Overijssel, we found that on average for the past three decades a sowing date of 19 September (± 7 days) allowed to attain these 400 GDD; this provides support for the current legislation that states that from 2019 onwards a cover crop should be sown before 1 October. To meet this deadline, while simultaneously ascertaining a harvest-ready main crop, in practice implies that undersowing of the cover crop during spring will gain importance. Our results show that Sentinel-2 NDVI time series can assess the effectiveness and timing of cover crop growth for small agricultural fields, and as such has potential to inform regulatory frameworks as well as farmers with actionable information that may help to reduce nitrogen leaching.