固相萃取技术在环境水质监测方法开发中的应用

固相萃取技术非常适用于环境水质中痕量有机污染物的监测分析。文章从选择固相萃取柱到萃取液进入色谱分析这样一个完整的过程,并以使用该技术萃取环境水样中的硝基苯类化合物为例,具体阐述了如何使用固相萃取技术建立一个方便实用的环境水质监测分析方法。     

强力霉素生产废水资源化技术研究

根据强力霉素生产废水的特殊性,选用三烷基胺为络合剂、正辛醇和磺化煤油为稀释剂、氢氧化钠为反萃取剂,进行萃取-反萃取实验研究.确定了最佳的工艺条件.结果表明,通过三级萃取后,磺基水杨酸(SSA)、对甲基苯磺酸(PTSA)、COD和BOD5去除率分别达到99.8%、95.4%、92.8%和77.4%,一次反萃取率接近100%,并且萃取剂可以循环使用.采用该工艺不但有明显的环境效益,而且还可以回收磺酸类原料资源.具有良好的经济效益.     

氟苯生产废水处理及资源化技术

采用酸化、萃取、反萃、除氟、电催化氧化技术处理氟苯生产废水（简称废水）。工艺条件为：以硫酸为酸化剂,pH小于等于1;萃取温度10～25℃,搅拌时间大于4min,油水比（萃取剂与废水的体积比）1：4．0;反萃碱油比（NaOH溶液体积与油相体积比）1：3,NaOH质量分数10％;除氟时先加入2倍理论计算量的氯化钙、后加入氧化钙调pH至7～8;电催化氧化时粒子群电催化反应器槽电流2．0～2．5A,停留时间40～60min。处理后废水的COD、苯酚、F^-、石油类去除率分别高于99．3％,99．9％,99．8％,99．9％,苯酚回收率高于93．5％;出水COD、苯酚、F^-、石油类的浓度低于GB8978—1996《污水综合排放标准》中的一级排放标准。     

膜萃取和CaO-MgO乳状液反萃取法由醋酸废水生产醋酸钙镁盐

采用磺化聚醚砜中空纤维膜萃取醋酸废水,再用CaO—MgO乳状液反萃取制备醋酸钙镁盐。考察了膜萃取和反萃取的最佳实验条件。单级膜萃取醋酸废水（醋酸质量分数2％）的最佳条件为：水相走管程有机相走壳程（水外油内）逆流、有机相流量与水相流量比1．3、水相流量0．23mL/min,在此条件下萃取率可达74％;采用二级萃取,总萃取率可达95％。反萃取的最佳条件为：采用质量浓度100g／L的CaO—MgO乳状液作反萃取剂,CaO—MgO与醋酸摩尔比1．0：2．0,投料钙与镁摩尔比2．9：7．0,反萃取时间30min,室温,在此条件下反萃取率高于97％。     

硝基苯并噻唑重氮氨基偶氮苯固相萃取光度法测定镉的研究

研究了用硝基苯并噻唑重氮氨基偶氮苯(NBTDAA)固相萃取光度法测定镉,在pH＝10的硼砂-氢氧化钠缓冲介质中,TritonX-100存在下,NBTDAA与镉反应生成2∶1稳定络合物,该络合物可被MCI-GEL 反相固相萃取小柱萃取富集,富集的络合物用丙酮洗脱后用光度法测定,在丙酮介质中体系最大吸收波长为525nm,摩尔吸光系数ε=1.32×105 L·mol-1·cm-1,镉含量在0.01～1.5 mg/L内符合比耳定律,方法用于痕量镉的测定,结果令人满意.     

浊点萃取-高效液相色谱测定土壤及底泥中痕量多环芳烃

采用阴离子表面活性剂十二烷基硫酸钠(SDS)超声波辅助浊点萃取(CPE),高效液相色谱法(HPLC)测定土壤及底泥中痕量多环芳烃(PAHs),在SDS浓度为2.75%,HCl用量为4.2mol·l-1,平衡温度为70℃.恒温时间为50min的最佳条件下,萘、芴、苊烯、菲和芘的方法检测限分别:31.40,18.84,12.56,94.20和31.40μg·l-1,线性范嗣为0-10.0 mg·l-1.     

长江(南京段)环境雌激素的污染特征

利用固相萃取技术和重组基因酵母检测了长江(南京段)四个典型断面环境雌激素污染状况.结果表明,除秦淮新河断面外,江心洲断面、三汊河断面和大桥断面均有环境雌激素的检出,雌二醇当量分别为0.38、0.24和0.45 ng·L~(-1).与国内外地表水环境雌激素检测结果相比,长江(南京段)典型断面雌激素活性水平为较低至中等.对江心洲断面和大桥断面,甲醇洗脱组分的雌激素活性最大,其次为丙酮洗脱组分,二氯甲烷洗脱组分的雌激素活性最小;对三汊河断面,丙酮洗脱组分的雌激素活性最大,其次为二氯甲烷洗脱组分,甲醇洗脱组分的雌激素活性最小.这可能是污水来源不同所致,生活污水导致大量极性雌激素污染物的输入,而工业污水则主要引入了中等至弱极性雌激素污染物.三个雌激素活性阳性检出断面主要活性洗脱组分的雌激素活性均大于混合样的雌激素活性,这可能是由于样品混合后各种结构上不同的污染物之间的交互作用掩盖了实际的雌激素活性.     

γ酸废水的综合利用

用PCW－2萃取剂对γ酸（2－氨基－8－萘酚－6－磺酸）废水进行了一级萃取,废话水的COD去除率大于97％,萃取液用碱液反萃加收γ酸产品,每立方米废水回收4kgγ酸,加收产品中γ酸的质量分数大于96％,符合工业品质量要求,回收过程运行费用低,具有良好的经济效益和环境效益。     

留兰香栽培管理与香油提取技术

作者介绍了留兰香的生长习性,从水土保持开发性治理的角度探讨了留兰香在红壤侵蚀区的栽培管理技术,并对留兰香油提取技术进行了对比研究。     

Quantification of carbamazepine and atrazine and screening of suspect organic contaminants in surface and drinking waters

A new approach for the identification of suspect trace organic contaminants in drinking and surface waters is presented. Samples were initially analyzed using a target determination method for two contamination tracers, carbamazepine (CBZ) and atrazine (ATZ). This method used offline solid-phase extraction and online solid-phase extraction techniques coupled to liquid chromatography-triple quadrupole mass spectrometry to accelerate the sample preparation process and improve method performance. CBZ and ATZ were found respectively in 31% and 56% of the samples, and concentrations were usually <20 ng L⁻¹. These samples were re-analyzed with a similar method on a quadrupole time-of-flight mass spectrometer to identify suspect contaminants by means of exact mass measurements and isotope patterns. A database of 264 common organic contaminants was built and used in conjunction with a Molecular Feature algorithm to identify the presence of these substances in drinking and surface water collected from different sources at various locations across Canada. Several organic contaminants were identified in the samples, but only the presence of caffeine, desethylatrazine, simazine and venlafaxine could be verified by comparison to pure standards. The presence of desethylatrazine was also confirmed by MS/MS experiments. These results suggest that target analysis for tracers of organic contamination may be a helpful tool to prioritize samples which should be further screened for suspect contaminants. This study also shows that the combination of separation techniques (offline and online SPE, LC) contribute to advance the applicability of high-resolution mass spectrometry for the identification of trace organic contaminants by accelerating the preparation step, reducing complexity and increasing analyte concentrations for optimal detection.