长株潭城市群人为热排放对城市热环境影响研究

采用"自上而下"的能源清单法,研究了长株潭城市群2017年人为热排放量及其时空分布特征;同时,利用中尺度天气预报模式(Weather Research and Forecasting,WRF)及其耦合的UCM对夏冬两季分别进行数值模拟试验,定量分析了不同类型建成区人为热排放增温效应的季节性差异.结果表明:(1)长株潭2017年人为热排放总量为3.49x1017J/a,平均人为热排放强度为14.22 W/m2,工业、建筑、交通和人体新城代谢对人为热的贡献率分别为48.15％、40％、11.3％和0.55％.(2)人为热的引入使得城市群主城区夏季和冬季的平均温度分别升高了约0.7℃和1.5℃;冬季增温效果是夏季的2倍.(3)不同密度分区人为热排放导致的增温效果不同,总的来说,工业/商业区＞高密度住宅区＞低密度住宅区.     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

UiO-66(Zr)@多孔陶瓷复合材料的制备及对络合态重金属EDTA-Cu(Ⅱ)的去除

本文采用多孔陶瓷作为基体制备了锆基金属有机骨架UiO-66@多孔陶瓷复合材料.通过扫描电子显微镜(SEM)、粉末X射线衍射(PXRD)、氮气吸附和傅里叶变换红外光谱(FTIR)等表征手段对比了氢氧化钠脱硅和乙二胺表面改性等基体活化方式对UiO-66(Zr)在多孔陶瓷表面负载情况的影响.结果表明,经过乙二胺表面改性的多孔陶瓷对UiO-66(Zr)的负载更均匀,负载效果更好.以EDTA-Cu(Ⅱ)为考察对象,研究了UiO-66(Zr)@乙二胺表面改性多孔陶瓷复合材料对络合态重金属的净化效能.结果表明,UiO-66(Zr)@多孔陶瓷复合材料在较宽的酸碱条件下(pH=3—9)对络合态重金属EDTA-Cu(Ⅱ)均表现出良好的吸附性能,饱和吸附量为1.17 mg·g~(-1),并可通过NaOH解吸再生,从而实现材料的重复利用.     

液液萃取-固相萃取-气质联用测定指甲中的多溴联苯醚与多氯联苯

利用液液萃取(LLE)与固相萃取法(SPE)提取和净化人体指甲中的多溴联苯醚(PBDEs)和多氯联苯(PCBs),经浓硫酸除脂后,利用气相色谱-质谱联用仪(GC-MS)测定PBDEs和PCBs.对提取溶剂比例、净化柱类型(复合硅胶柱与固相萃取柱)、固相萃取条件(洗脱溶剂及体积)以及脂肪的去除方法进行了优化,加标回收率较前人基础上均有明显提高.加标回收试验结果显示,PBDEs和PCBs平均基质加标回收率分别为90%—110%和71%—102%,空白加标回收率分别为70%—110%和60%—100%之间,仪器检出限(IDL)分别为0.034—0.120μg·L~(-1)和0.032—0.392μg·L~(-1).本方法快速、简单、高效,能够满足指甲中PBDEs和PCBs的分析.同时本研究利用该方法对电子垃圾拆解地区居民的指甲样品进行测定,PBDEs和PCBs平均浓度分别为623 ng·g~(-1)和148 ng·g~(-1),BDE(-154、-153、-183、-209)和PCB(-8、-28、-52、-66、-101、-77、-118、-153、-187)在所有样品中均检出,女性指甲中PBDEs与PCBs的浓度普遍高于男性.     

高效液相色谱-电感耦合等离子体质谱测定大米粉中的硒形态

建立了高效液相色谱-电感耦合等离子体质谱联用技术(HPLC-ICP-MS)测定大米粉中硒代胱氨酸(SeCys_2)、甲基-硒代半胱氨酸(MeSeCys)、亚硒酸根(Se(Ⅳ))、硒代蛋氨酸(SeMet)、硒酸根(Se(Ⅵ))等5种硒形态的分析方法.采用Hamilton PRP-X100分析柱,以pH 4和pH 6的20 mmol·L~(-1)的柠檬酸溶液辅以少量甲醇为流动相,在梯度洗脱条件下,9 min内可实现5种硒形态完全分离.SeCys_2、MeSeCys、Se(Ⅳ)、SeMet、Se(Ⅵ)的检出限分别为0.88、0.69、1.00、0.90、0.82μg·L~(-1).利用富硒小麦粉标准物质RM8436探讨了不同提取方式的提取效果.最终确定75 mmol·L~(-1) Tris-HCl(pH 7.5)添加XIV蛋白酶和Driselase酶作为提取剂,在37℃振荡提取3 h为大米样品前处理方法.利用该方法分析了富硒地区大米粉中的硒形态,结果表明,大米粉中的硒主要以有机硒形态为主,其中SeMet是最主要的硒形态,占总硒的90%左右.     

Determination of 27 pharmaceuticals and personal care products (PPCPs) in water: The benefit of isotope dilution

• Isotope dilution method was developed for the determination of 27 PPCPs in water. • The established method was successfully applied to different types of water samples. • The correction effect of corresponding 27 ILSs over 70 d was investigated. • Benefit of isotopic dilution method was illustrated for three examples. Pharmaceuticals and personal care products (PPCPs) are a unique group of emerging and non-persistent contaminants. In this study, 27 PPCPs in various water samples were extracted by solid phase extraction (SPE), and determined by isotope dilution method using liquid chromatography coupled to tandem triple quadruple mass spectrometer (LC-MS/MS). A total of 27 isotopically labeled standards (ILSs) were applied to correct the concentration of PPCPs in spiked ultrapure water, drinking water, river, effluent and influent sewage. The corrected recoveries were 73%–122% with the relative standard deviation (RSD)<16%, except for acetaminophen. The matrix effect for all kinds of water samples was<22% and the method quantitation limits (MQLs) were 0.45–8.6 ng/L. The developed method was successfully applied on environmental water samples. The SPE extracts of spiked ultrapure water, drinking water, river and wastewater effluent were stored for 70 days, and the ILSs-corrected recoveries of 27 PPCPs were obtained to evaluate the correction ability of ILSs in the presence of variety interferences. The recoveries of 27 PPCPs over 70 days were within the scope of 72%–140% with the recovery variation<37% in all cases. The isotope dilution method seems to be of benefit when the extract has to be stored for long time before the instrument analysis.     

饱和粉末活性炭电化学再生研究

采用电化学再生法对吸附处理染料废水产生的饱和粉末活性炭(PAC)进行再生,以NaCl为电解质,考察了电源类型、pH、再生时间、电压和NaCl浓度对活性炭再生率的影响,并对活性炭表面酸性含氧官能团进行测定。结果表明:(1)在pH=1、直流电压为6V、NaCl为6g/L、再生90min的最佳条件下,采用单室反应器,饱和PAC再生率达到59.09%。(2)电极循环伏安曲线结果表明,饱和PAC电极表面发生氧化反应,与主电极直接和间接氧化共同作用,使活性炭表面吸附的污染物降解。活性炭表面酸性含氧官能团滴定和红外光谱测试结果进一步表明,电化学再生法使活性炭表面基团得到恢复。     

铜陵某富硫尾矿库周边土壤重金属污染特征及风险评价

铜陵某尾矿库堆积大量富硫尾矿,为研究其氧化状况及对周边土壤的污染情况,在尾矿库和周边采集尾矿及土壤样品,测试分析尾矿及土壤样品典型重金属(Hg、As、Cr、Cd、Pb、Zn)含量和赋存形态,并基于单因子污染指数法和内梅罗综合污染指数法对土壤污染状况进行了评价。结果表明:(1)尾矿中Fe_2O_3平均占比达到38.08%(质量分数,下同),S平均占比达到5.34%;(2)尾矿库周边土壤中Cd、As、Zn、Hg严重超标,分别为《土壤环境质量农用地土壤污染风险管控标准(试行)》(GB 15618—2018)风险筛选值的6.3、3.7、1.8、1.5倍;(3)土壤中重金属主要以残渣态形式存在,但Cd、Hg、Zn的非残渣态平均占比均达到25%以上,生物有效性较高,对周边环境存在潜在危害;(4)两种污染指数法评价结果表明,尾矿库周边土壤以Cd、As、Zn污染为主,该富硫尾矿库已对周边环境造成重度污染。     

射阳湖浮游动物群落结构特征及其与环境因子相关性研究

2016—2017年对射阳湖开展浮游动物群落结构和水质指标逐月监测。结果表明,射阳湖共鉴定出浮游动物61种,其中原生动物、轮虫、枝角类和桡足类分别为25种、24种、7种和5种。浮游动物种类数呈现春夏季多于秋冬季的变化趋势。浮游动物优势种数量较多、分布广,群落结构相对复杂且稳定。运用Shannon-Wiener指数、均匀度指数和B/T指数对射阳湖水质作评价,结果表明,该湖处于轻度—中度污染状态,生物学指标评价法与常规水质评价结果一致。浮游动物群落结构与水质指标相关性分析表明,水温、透明度、Chl-a和DO是影响射阳湖浮游动物群落结构的主要水质指标。