微波萃取技术在分析土壤中有机污染物的应用

介绍了微波萃取技术及其使用的试剂、设备和条件,对微波萃取在分析土壤中有机污染物的应用予以综述,阐述了微波萃取技术是分析土壤中有机污染物的好方法。     

生物过滤技术在大气污染控制中的应用

生物过滤是控制大气污染的经济有效技术,具有较好的发展前景。本文介绍了生物过滤技术处理废气的研究,应用历史,现状,和生物过滤理论,分析了工艺的使用范围,设计及运行控制要点,列举了应用的范例。     

固相微萃取-气相色谱/质谱联用法测定饮用水中苯类化合物

用固相微苹取(ＳＰＭＥ)－气相色谱/质谱联用法测定饮用水中苯类化合物,以１００μｍ ＰＤＭＳ(聚二甲基硅氧烷)萃取针提取、浓缩、分离与测定九种目标化合物．萃取时间经优化选定为８ｍｉｎ,而热解析时间设定为２ｍｉｎ． 本方法的相对标准偏差小于５%,线性范围宽(２０ｎｇ·ｍｌ－１－１００００ｎｇ·ｍｌ－１),多数化合物的检测限低于５μｇ·ｌ－１．饮用水样品检测显示,样品加标回收率范围在８４%至１１０%内．     

铝铁锡共聚物的合成及其特性研究

合成制备了铝铁锡共聚物,测定分析了其水解共聚合和熟化过程中的pH变化,并通过扫描电镜和混凝实验对共聚物的晶形貌像和絮凝作用进行了研究。结果表明：Sn^4 具有比Fe^3 ,Al^3 更强的水解活性,它有使共聚物的分子趋于均一的作用;铝铁锡共聚物的最佳配比为：NAl∶NFe∶NSn=5∶5∶3,最佳水解度B^*＝2．0,此共聚物具有比CPAFC更优良的絮凝性能。     

二氧化氯对有机染料脱色效果的研究

本文对二氧化氯二两种直接染料和两种活性染料脱色效果的影响因素－ClO2的投加量、染料的初始浓度、pH值、温度以及反应时间等进行了研究。结果表明,在适当的条件下,二氧化氯对这几种有机染料均具有很好的脱色效果。     

强化混凝去除微污染原水胶体颗粒的研究

对珠江水系统进行了强化混凝处理,燕利用准弹性激光散射技术（PCS）对常规混凝和强化混凝前后水中胶体颗粒（小于0.45um)的大小与分布进行了测定,探讨了搅拌条件对混凝效果的影响。     

杀虫单降解菌的筛选分离与降解特性研究

从农药厂废水排放沟污泥中分离到一株对杀虫单有较强降解能力的菌株LY－4,经鉴定为巨大芽孢杆菌（Bacillus megaterium)。其生长的最适pH为7,最适温度为30℃。该菌对杀虫单有很强的耐受性,在杀虫单浓度ρ＝5000mg/L时,仍能较好地生长并发挥降解作用。当杀虫单初始浓度高于一定值时,一定量的菌剂对杀虫单的降解率随底物浓度的提高而降低,而绝对去除量则随底物浓度的提高而提高。与不加菌的对照相比,加入LY－4后,可使杀虫单浓度在很短的时间内降到很低的水平。图5表1参6     

贵州省煤中挥发性和半挥发性微量元素分布规律的初步研究

研究了贵州省四大煤田不同层位、不同煤种中Hg,As,Se,Pb,Cd,Tl,Zn,Sb等挥发性和半挥发性微量元素的分布规律。贵州省原煤中Hg,As,Se,Pb,Cd,Sb等元素的含量高于地壳克拉克值;Tl,Zn等的含量低于地壳克拉克值;另外,除了Pb,Zn外,贵州省原煤中Hg,As,Se,Cd的含量远远高于东北和内蒙古东部地区。微量元素聚类分析结果表明,Hg,As,Sb可能主要分布于煤的黄铁矿中;Zn和Se可能主要赋存于闪锌矿中;Cd可能部分存在于硫化物中,部分存在于硅酸盐矿物相中;Pb可能主要存在于硅酸盐矿物相中;而Tl在煤中的赋存形式较复杂。     

Behaviour of selected endocrine-disrupting chemicals in three sewage treatment plants of Beijing, China

Occurrence and fate of eight kinds of selected endocrine-disrupting compounds (EDCs) in three sewage treatment plants (STPs) of Beijing, China was investigated. These EDCs, composed of 4-octylphenol (4-OP), 4-n-nonylphenol (4-n-NP), bisphenol A (BPA), estrone (E1), 17α-estradiol (17α-E2), 17β-estradiol (E2), estriol (E3) and 17α-ethinylestradiol (EE2), in every step of STPs, were simultaneously analysed by gas chromatography/mass spectrometry after derivatisation. All the EDCs were detected in the influents of three STPs, and BPA was the most abundant compound. The concentrations of EDCs ranged from 36.6 ng/l of 17α-E2 (STP C) to 1342.3 ng/l of BPA (STP B) in the influent sewages and from below limits of detection of E2 and E3 (STP C) to 142.5 ng/l of E1 (STP B) in the effluent sewages. The STPs could not remove alkylphenols effectively from the aqueous phase with less than 40% reduction. BPA decreased over 90%, and steroid estrogens achieved considerable reductions from 64.8% of E2 to 94.9% of E3. Generally, biological treatment was more effective in removing alkylphenols, BPA and natural estrogens from the aqueous phase than primary treatment. However, the synthetic estrogen, EE2, was mostly removed by the primary treatment with about 63.5% reduction. It is the first time that the concentration of 17α-E2 in the sewage of China was reported in this paper. The compound might have a bearing with the waste effluents of dairy farms around urban area of Beijing.     

Multi-scale spatial structure of heavy metals in agricultural soils in Beijing

To effectively investigate the spatial variability of heavy metals in soil, produce a higher quality spatial distribution map, and identify the potential pollution sources of heavy metals, geostatistics was employed to evaluate the effect of scale on spatial variability of heavy metals in Beijing agricultural soils. The results revealed that spatial variability of Cr, Ni, Zn, and Hg was dependent on scale. Validation of the optimality of theoretical semivariance and comparative analysis of the estimation accuracy demonstrated that the multi-scale nested model can reveal the spatial structure of heavy metals effectively and improve the estimation accuracy better than the single-scale method, thereby enabling production a higher quality spatial interpolation map. Thus, the multi-scale kriging nested model is a useful tool for revealing spatial variability of heavy metals in soils, while the spatial distribution maps allow the identification of hot spots with high concentrations of heavy metals.