Characterization of AOX by Fractionation Analysis and Size‐exclusion Chromatography

A characterization method for AOX in surface water samples was developed and tested. The method involves fractionation using a hydrophobic C18 resin and a weak anionic exchange resin and allows the fractionation of the AOX pool of surface water samples into four fractions: (1) hydrophilic acidic, (2) hydrophilic non‐acidic, (3) hydrophobic acidic, and (4) hydrophobic non‐acidic. The adsorption analysis was verified with AOX‐relevant model compounds and was applied to characterize the AOX pool of a stream sample from the Moskva river (Russia). In addition to the fractionation analysis, size‐exclusion chromatography was used to characterize the AOX pool of the sample studied. Hydrophilic acids made up the major fraction of the AOX pool (55 %). Among this fraction chlorinated high‐molecular acids (humic substances) made up the main fraction (35 %).     

基于CNGI的政府地理信息系统建设与应用技术研究

介绍了我国首个基于CNGI的地理信息系统移植和建设情况,针对CNGI与IPv6的技术特点开展了新的地理信息应用技术研究,并以政府地理信息系统“地学之窗”为基础开发了GIS应用示范系统,为下一代网络环境下地理信息系统技术开发和应用建设奠定了一系列技术基础。     

Modelling the Kinetics of Calcium Hydroxide Dissolution in Water

In water treatment calcium hydroxide is used in softening and decarbonization techniques as well as in stabilization processes. Due to its slight solubility calcium hydroxide is applied as suspension. The dissolution kinetics plays a major role in these processes. For the characterization of calcium hydroxide dissolution empirical methods exist. These methods allow relative comparison of different calcium hydroxide products. Thus in this study a dissolution rate model is presented that is based on the chemical reactions determining the dissolution. This model allows to predict the dissolution with respect to particle diameter and temperature. However, the most important factor is the particle diameter i.e. the total surface of particles in solution. Furthermore an effect of the dosed amount of calcium hydroxide particles on the solubility was found.     

Polluted River Systems: Monitoring and Assessment of Ecotoxicological Risks

In the past chemical, ecological, and toxicological research was carried out in a separate way. Nowadays, more and more studies are undertaken considering these three approaches in an integrated way (triad studies). A sophisticated combination of chemical and biological monitoring and bioassays can improve water quality management of polluted rivers. Application of quantitative structure-activity relationships (QSARs), algorithms for mixture toxicity of known substances, chemical group parameters, and response-oriented sum parameters, may reduce uncertainties in ecotoxicological risk management.     

BCC-ESM1 Model Datasets for the CMIP6 Aerosol Chemistry Model Intercomparison Project(AerChemMIP)

BCC-ESM1 is the first version of the Beijing Climate Center’s Earth System Model,and is participating in phase 6 of the Coupled Model Intercomparison Project(CMIP6).The Aerosol Chemistry Model Intercomparison Project(AerChemMIP)is the only CMIP6-endorsed MIP in which BCC-ESM1 is involved.All AerChemMIP experiments in priority 1 and seven experiments in priorities 2 and 3 have been conducted.The DECK(Diagnostic,Evaluation and Characterization of Klima)and CMIP historical simulations have also been run as the entry card of CMIP6.The AerChemMIP outputs from BCC-ESM1 have been widely used in recent atmospheric chemistry studies.To facilitate the use of the BCC-ESM1 datasets,this study describes the experiment settings and summarizes the model outputs in detail.Preliminary evaluations of BCC-ESM1 are also presented,revealing that:the climate sensitivities of BCC-ESM1 are well within the likely ranges suggested by IPCC AR5;the spatial structures of annual mean surface air temperature and precipitation can be reasonably captured,despite some common precipitation biases as in CMIP5 and CMIP6 models;a spurious cooling bias from the 1960s to 1990s is evident in BCC-ESM1,as in most other ESMs;and the mean states of surface sulfate concentrations can also be reasonably reproduced,as well as their temporal evolution at regional scales.These datasets have been archived on the Earth System Grid Federation(ESGF)node for atmospheric chemistry studies.     

浅层地下水SF6年龄测试技术及其应用

地下水年龄是水文地质研究的重要参数,特别是年轻地下水的年龄.论述了安装设计的用于地下水中SF6的测试技术,该技术装置由SF6提取系统和分析测试系统两部分组成,前者由剥离器、硅胶管、冷冻富集陷阱、六通阀、十通阀、高纯氮气钢瓶和载气过滤系统组成,后者由带电子捕获检测器(ECD)的气相色谱仪组成.通过条件实验,该系统测定SF6的标准误差为1.77%,对SF6的最低检测极限为1.0×10-12,测定空气中的SF6只需10 mL气体,测定地下水样时只需1.0 L.研究了地下水SF6年龄的计算程序,计算了石家庄市浅层地下水的年龄.     

CX-6(02)微纳卫星超分辨率成像

面向微纳卫星高分辨率对地遥感,将超分辨率成像应用于中国整星60公斤级的CX-6(02)微纳卫星设计中,解决因体积和重量限制导致传统长焦距、大口径成像载荷无法应用于微纳卫星的问题。图像获取上,采用高帧频面阵CMOS探测器对同一地物目标多次曝光的方式,利用卫星姿态控制偏差和地速补偿来获得多帧具有亚像元位移的图像;超分辨率重建算法上,在变分贝叶斯框架下提出加权双向差分模型,提高先验概率模型的方向约束性,削弱观测方程求解的病态性。CX-6(02)星成像数据实验结果表明,本文的图像采样方法可获得较为充分的亚像元信息;相比传统的L1范数先验和全变分先验的变分贝叶斯超分辨算法重建结果,本文重建结果对反卷积运算导致的噪声放大具有更好的抑制作用,可获得两倍分辨率提升,有效提高数据质量和应用价值。     

Vegetation species mapping in a coastal-dune ecosystem using high resolution satellite imagery

Vegetation mapping is a priority when managing natural protected areas. In this context, very high resolution satellite remote sensing data can be fundamental in providing accurate vegetation cartography at species level. In this work, a complete processing methodology has been developed and validated in a complex vulnerable coastal-dune ecosystem. Specifically, the analysis has been carried out using WorldView-2 imagery, which offers spatial and spectral resolutions. A thorough assessment of 5 atmospheric correction models has been performed using real reflectance measures from a field radiometry campaign. To select the classification methodology, different strategies have been evaluated, including additional spectral (23 vegetation indices) and spatial (4 texture parameters) information to the multispectral bands. Likewise, the application of linear unmixing techniques has been tested and abundance maps of each plant species have been generated using the library of spectral signatures recorded during the campaign. After the analysis conducted, a new methodology has been proposed based on the use of the 6S atmospheric model and the Support Vector Machine classification algorithm applied to a combination of different spectral and spatial input data. Specifically, an overall accuracy of 88,03% was achieved combining the corrected multispectral bands plus a vegetation index (MSAVI2) and texture information (variance of the first principal component). Furthermore, the methodology has been validated by photointerpretation and 3 plant species achieve significant accuracy: Tamarix canariensis (94,9%), Juncus acutus (85,7%) and Launaea arborescens (62,4%). Finally, the classified procedure comparing maps for different seasons has also shown robustness to changes in the phenological state of the vegetation.     

基于CMIP6多模式集合的未来中国风功率预估

实现我国2060年“碳中和”目标,需要大力发展包括风能在内的清洁能源,然而气候变化给未来风资源利用带来较大的不确定性。本文利用人工神经网络(Artificial Neural Network,ANN)算法对16个CMIP6气候模式风速数据进行逐一订正,在此基础上预估21世纪30、60年代以及21世纪末这3个不同年代在低(SSP1-2.6)和高(SSP5-8.5)排放情景下中国风功率较当代的变化。结果表明,ANN算法使CMIP6气候模式均方根误差平均降低(39.93％±9.57％),并使多模式集合平均与观测的相关系数从0.56增加到0.83,更好地再现了中国当代风速的空间分布和季节变化。在此基础上,预估的21世纪60年代(2050—2064年)风功率密度在两种情景下分别减少了(1.01±0.94) W·m^-2(2.62％±2.27％)和(1.11±1.45) W·m^-2(1.90％±2.51％)。时间上,春季作为风能密度最大的季节,两种排放情景下风功率分别减少了(1.16±1.14) W·m^-2和(1.43±1.58) W·m^-2。空间上,中国东南部风功率密度在SSP1-2.6情景下降(0.56±0.53) W·m^-2,而SSP5-8.5情景下上升(0.40±0.29) W·m^-2。近期(2025—2039年)全国平均风功率密度在两种情景下分别减少了(0.52±0.83) W·m^-2和(0.54±1.02) W·m^-2,而长期(2085—2099年)风功率密度分别减小了(0.98±1.17) W·m^-2和(1.83±1.17) W·m^-2。利用极度梯度提升(XGB)算法订正CMIP6数据的预估变化量级偏小但趋势一致,表明随着全球变暖幅度的增加,我国风功率降低的趋势将更加显著。