磷对褐土中锌镉次级吸附和解吸影响

通过吸附和解吸试验,研究了不同磷吸附量石灰性褐土对锌镉次级吸附和解吸的影响。结果表明,次级吸附锌和镉对不同吸附量磷土壤的磷解吸量随磷吸附量的增加而增加,而磷解吸量随次级吸附后锌、镉浓度的增加而降低,即随锌镉添加量的增加,磷的有效性有所降低。土壤对锌的次级吸附量和吸附率随磷吸附量的增加先降低后升高,并随添加镉浓度的增加而降低,解吸量和解吸率随磷吸附量的增加而增加,说明在正常施磷范围内,增加磷的施用量能提高土壤中锌的有效性,同时,土壤对高浓度锌的次级吸附率小于低浓度锌的次级吸附率,而土壤对高浓度锌的解吸量和解吸率要远大于对浓度锌的解吸量和解吸率;土壤对镉的次级吸附量、吸附率和解吸量、解吸率都随着磷吸附量的增加而增加,且吸附量随添加镉的量增加而增加,但镉次级吸附量和吸附率随添加锌浓度的增加而减小,解吸量和解吸率却增大,说明在磷吸附量相同的条件下,添加锌促进了镉的有效性。     

可溶性有机质对芘在泥炭和高岭土上吸附和解吸的影响

为掌握可溶性有机质(DOM)对憎水性有机污染物吸附和解吸行为的影响,本研究选取四环多环芳烃——芘作为目标污染物,通过批平衡实验研究了不同分子量组分DOM对芘在泥炭和高岭土上吸附和解吸的影响.结果表明,吸附和解吸数据均可以用Freundlich模型很好地拟合(R²>0.93).DOM的添加抑制了泥炭对芘的吸附,并且分子量越大的DOM产生的抑制效应越明显,主要是由于DOM与芘分子的竞争、增溶作用及泥炭表面微孔的堵塞引起的.与之相反,DOM促进了芘在高岭土上的吸附,DOM分子量越大,促进效应越强,这是由于DOM与芘分子之间通过累积吸附或共吸附增加高岭土对芘的吸附.DOM促进了芘在泥炭和高岭土上的解吸,并且促进效应随分子量的增加而增强.此外,芘在泥炭和高岭土上的解吸均存在迟滞现象,均在低浓度时表现出更明显的效应.DOM_bulk和DOM_(>14000 Da)增加了芘在泥炭上的解吸迟滞现象,但降低了其在高岭土上的解吸迟滞现象.     

PreVent GC系统提高多环芳烃致突变物检出量的研究

利用ＰｒｅＶｅｎｔ预排／切割气相色谱进样技术,对多种多环芳烃致突变物质进行大体积进样分析,并与常规毛细管色谱进样方式进行比较,最大进样量为１２５μｌ,检测灵敏度可提高０．５－２个数量级以上,检测精度一般〈５％。     

U1WH2O2／TiO2催化氧化法对油田采出水中多环芳烃的处理效果

针对油田采出水中含有多环芳烃种类多且较难去除的特点,选取了菲和芴两种代表性多环芳烃作为研究对象,采用UV／H2O2／TiO2技术对油田采出水中多环芳烃的处理效果进行了研究;考察了在254nm波长紫外光照射下,TiO2投加量、H2O2投加量、pH值和光照时间对水样中的菲和芴处理效果的影响．实验结果显示,处理初始浓度为1000μg·L-1的菲、芴时,TiO2用量为2．2g·L-1、H2O2用量为0．12mmol·L-1、pH值为7、光照时间1．5h时,去除效果较好．     

气相色谱法估算多环芳烃的辛醇/水分配系数

通过对2－6环多环芳烃（PAHs)气相色谱保留时间（RGC）与HPLC保留值及与辛醇／水分配系数（KOW）对应关系的研究，发现RGC与HPLC保留值主KOW间存在明显的线性相关关系，建立了RGC与KOW间的一元回归方程，并对包括EPA16种优先控制的PAHs在内的33种多环芳烃化合物的KOW值进行估算，估算值的相对误差为0．10％－12．10％，平均值为4．51％。     

土壤对恩诺沙星的吸附和解吸特性研究

恩诺沙星是第一个动物专用的氟喹诺酮类药物,在畜禽养殖业中应用非常广泛。恩诺沙星进入畜禽体后,其原形及活性代谢物会随畜禽的排泄物进入环境,对环境生物产生影响。文章研究了恩诺沙星在土壤中的吸附和解吸规律,为恩诺沙星的生态风险评价提供依据。试验分3组,各组土壤分别采自菜园、水稻田和果园。在离心管中称取1 g土壤样品,加入恩诺沙星系列标准溶液,在25±0.5℃条件下机械振摇,用高效液相色谱(HPLC)法测定水相中恩诺沙星的含量,分别求出土壤对恩诺沙星的吸附和解吸平衡时间及其对恩诺沙星的吸附和解吸量。结果表明,土壤对恩诺沙星的吸附和解吸平衡时间分别为34 h和44 h;土壤对恩诺沙星的吸附性很强,对恩诺沙星的吸附量占水相中恩诺沙星总量99%以上,其吸附机理符合Freundlich平衡吸附方程wS=kfρe1/n;土壤对恩诺沙星的解吸具有浓度依赖性,其解吸量仅为吸附量的1‰左右,表明恩诺沙星在土壤中的迁移能力弱,不易污染地下水。     

pH和添加有机物料对3种酸性土壤中磷吸附-解吸的影响

研究了pH和添加有机物料对红壤、砖红壤和水稻土中磷吸附-解吸的影响。结果表明,砖红壤和水稻土中磷的吸附量和解吸量均随pH的升高而降低,pH对红壤中磷吸附和解吸的影响很小。土壤阳离子交换量(CEC),铁、铝氧化物含量和有机质含量是影响磷吸附的主要因素。红壤的CEC和有机质含量很低,铁、铝氧化物含量高,因而对磷的吸附量最高。砖红壤和水稻土CEC较高,土壤表面对磷的排斥作用较大,而且较高含量的有机质覆盖了土壤表面的磷吸附位,因此这2种土壤对磷的吸附量低于红壤。添加稻草并进行恒温培养可使红壤和水稻土对磷的吸附量显著减少,但对砖红壤中磷吸附的影响较小。添加稻草使土壤磷的解吸量和解吸率增加,从而增加了土壤中吸附性磷的活性。     

三峡水库消落区土壤汞吸附解吸动力学特征

对三峡水库消落区5种土壤进行了汞的吸附-解吸试验,用不同的等温吸附方程和化学反应动力学方程进行了模拟比较,结果显示,不同土壤对汞的吸附解吸动力学规律相类似,吸附速率和解吸速率均与土壤pH值呈显著(r=0.933,p＜0.05)和极显著相关性(r=0.962,p＜0.01),但吸附量和解吸量各不相同,其中,紫色潮土对汞的吸附量最大,酸性紫色土最小;灰棕潮土对汞的解吸量最大,黄壤最小,其它类型土壤介于它们之间.     

土壤与沉积物对多环芳烃类有机物的吸附作用

吸附作用是疏水性有机物在土壤和沉积物环境中的重要迁移转化行为之一。多环芳烃是环境中一种重要的疏水性有机污染物。文章着重阐述了多环芳烃类有机物在土壤和沉积物中有机质和粘土矿物吸附机理，指出土壤、沉积物有机质的结构异质性是导致非线形吸附的重要原因；分析了影响多环芳烃吸附过程的诸多因素，并提出该研究领域存在的问题以及今后发展的方向。     

干酪根对多环芳烃吸附机理的初步研究

采用间歇平衡法研究多环芳烃在干酪根上的吸附机理,结果表明,干酪根对多环芳烃的吸附具有明显的非线性,推测干酪根对多环芳烃的吸附作用可能遵循的是双元吸附模式,总体吸附是由烷烃活动相中的分配过程和刚性大分子骨架内外表面的表面吸附共同作用的结果.     

The application of solid-phase micro-extraction (SPME) to the analysis of polycyclic aromatic hydrocarbons (PAHs)

There are many established extraction techniques regularly used in the isolation and analysis of PAHs and similar organic compounds from various phases. These include Soxhlet or ultrasonic extractions from solids, and liquid-liquid or solid-phase extraction from aqueous samples. However, these methods have some inherent disadvantages; most require large volumes of organic solvents, they can be time consuming and many involve multi-step processes that always present the risk of the loss of some analytes (Zhang et al., 1994). Solid-phase micro-extraction (SPME) is a relatively new technique that has been used with much success in the analysis of a variety of compounds including PAHs. Experiments are being carried out to determine the optimum range of conditions for the extraction of a range of PAHs. Parameters under investigation include temperature, equilibration time, salinity and compound concentration. Presented here are some preliminary experiments into the applicability of SPME for PAH analysis. Further work will investigate the reproducibility of the technique, limits of detection and matrix effects. When an optimised method has been developed the technique will be used in investigations into PAH profiles in sediment cores.     

水中痕量亚当氏剂和二苯胺的固相微萃取方法研究

研究了固相微萃取(SPME)-高效液相色谱(HPLC)测定水样中痕量亚当氏剂和二苯胺的分析方法.对SPME的条件如萃取纤维、萃取时间、萃取温度、离子强度、解吸方式、解吸溶剂、解吸时间进行了优化,并用于地下水等实际水样的分析.SPME优化的条件为:选用60μmPDMS/DVB萃取纤维在室温25℃下直接萃取60min,磁力搅拌速度为1100r.min-1,然后萃取纤维在解吸室内静态解吸9min后进行HPLC分析.液相色谱分离条件为ZORBAXSBC18柱(4.6mmi.d.×250mm,5.0μm),流动相为甲醇-水(70:30,V/V),流速为1.0ml.min-1,二极管阵列检测器波长为280nm.方法线性范围为0.005mg.l-1—0.5mg.l-1(R>0.99),两种物质的检出限(S/N=3)分别为0.003mg.l-1和0.002mg.l-1.加标回收率分别在89.6%—100.4%和97.5%—100.1%(n=5)之间,相对平均标准偏差(RSD)分别在4.5%—6.2%和3.8%—6.7%之间.该方法快速、简便,无需使用有机溶剂,适于水样中痕量物质的分析.     

中国饮用水中多环芳烃的分布和健康风险评价

饮用水中存在的多环芳烃对人类的身体健康会产生危害。应用固相萃取富集法和气相色谱?质谱联用(GC/MS)分析方法对全国主要城市的80座自来水厂出水中多环芳烃的浓度进行了分析。结果表明:各自来水厂的出水中多环芳烃总量在174.02-658.44ng.L-1之间,其中致癌性多环芳烃的总量为55.08-173.36ng.L-1,致癌性多环芳烃占多环芳烃总量比例最高可达到49.68%。就其组成而言,出水中多环芳烃以3环芳烃(31%-37%)为主,但各环均有检出;通过评价水体健康风险,得到水厂出水中多环芳烃对人体的健康风险值是10-6a-1。     

煤飞灰环境标准参考物中PAHs的表征

本文采用不同提取方法以及不同溶剂对煤飞灰环境标准参考物质样品中PAHs的提取效率进行了考察.采用HPLC,毛细管GC以及GC-MS对飞灰样品中的PAHs进行了分析表征,并对前两种分析方法的精密度、准确性和所得结果的一致性进行了研究.     

利用HS-SPME-GC技术分析环境水样中超痕量的六氯苯,DDT及其代谢产物

利用顶空固相微萃取(HS-SPME)和气相色谱检测技术,通过对三种不同的SPME萃取头(PDMS,PMPVS,PA)实验条件的优化,并参照液液萃取的方法,对水相中六氯苯,DDT及其代谢产物的萃取效果进行了比较．结果表明,SPME方法比液液萃取方法在检测限和回收率上有很大的提高,其中PDMS对检测六氯苯,DDT及其代谢产物的效果较其它两种萃取头好．     

Polycyclic aromatic hydrocarbons (PAHs) in multimedia environment of Heshan coal district,Guangxi: distribution,source diagnosis and health risk assessment

Mining activities are among the major culprits of the wide occurrences of soil and water pollution by PAHs in coal district, which have resulted in ecological fragilities and health risk for local residents. Sixteen PAHs in multimedia environment from the Heshan coal district of Guangxi, South China, were measured, aiming to investigate the contamination level, distribution and possible sources and to estimate the potential health risks of PAHs. The average concentrations of 16 PAHs in the coal, coal gangue, soil, surface water and groundwater were 5114.56, 4551.10, 1280.12 ng g^?1, 426.98 and 381.20 ng L^?1, respectively. Additionally, higher soil and water PAH concentrations were detected in the vicinities of coal or coal gangue dump. Composition analysis, isomeric ratio, Pearson correlation analysis and principal component analysis were performed to diagnose the potential sources of PAHs in different environmental matrices, suggesting the dominant inputs of PAHs from coal/coal combustion and coal gangue in the soil and water. Soil and water guidelines and the incremental lifetime risk (ICLR) were used to assess the health risk, showing that soil and water were heavily contaminated by PAHs, and mean ICLR_{coal/coal-gangue} and mean ICLR_soil were both significantly higher than the acceptable levels (1 × 10^?4), posing high potential carcinogenic risk to residents, especially coal workers. This study highlights the environmental pollution problems and public health concerns of coal mining, particularly the potential occupational health hazards of coal miners exposed in Heshan.     

Polycyclic aromatic hydrocarbons in medicinal plants from Syria

The levels of 16 US Environmental Protection Agency polycyclic aromatic hydrocarbons (EPA PAHs) in 10 medicinal plants in different used parts of plant (leaves and flowers) have been determined. The analytical method consists of sample preparation by ultrasonic extraction with dichloromethane followed by silica gel clean-up. Subsequently, the analysis was carried out by reversed-phase high-performance liquid chromatography (HPLC) coupled to both ultraviolet and fluorescence detections in series to insure the detection of all 16 EPA PAHs. It was observed that the sum of the 16 PAHs (ΣPAHs) in the investigated medicinal plants ranged from 47 to 890 μg kg^–1 where the highest ΣPAHs was found in Sage plant sample. Light PAHs were dominants in all studied medicinal plants. The sum of eight genotoxic PAHs (ΣPAH8) have shown a better indicator of the degree of contamination with carcinogenic PAHs compared to benzo[a]pyrene in these products.     

Spatial distribution and temporal trends of polycyclic aromatic hydrocarbons (PAHs) in water and sediment from Songhua River, China

The spatial and temporal distributions of polycyclic aromatic hydrocarbons (PAHs) in the Songhua River, Harbin, China, were investigated. Seventy-seven samples, 42 water and 35 sediment samples, were collected in April and October of 2007 and January of 2008. The concentrations of total PAHs in water ranged from 163.54 to 2,746.25 ng/L with the average value of 934.62 ng/L, which were predominated by 2- and 3-ring PAHs. The concentrations of total 16 PAHs in sediment ranged from 68.25 to 654.15 ng/g dw with the average value of 234.15 ng/g dw, which were predominated by 4-, 5- and 6-ring PAHs. Statistical analysis of the PAH concentrations shown that the highest concentrations of the total PAHs were found during rainy season (October of 2007) and the lowest during snowy season (January of 2008). Ratios of specific PAH compounds, including fluoranthene/(fluoranthene + pyrene) (Flu/(Flu + Pyr)) and phenanthrene/(phenanthrene + anthracene) (An/(Ant + PhA)), were calculated to evaluate the possible sources of PAH contaminations. These ratios reflected pyrolytic inputs of PAHs in Songhua River water and a mixed pattern of pyrolytic and petrogenic inputs of PAHs in the Songhua River sediments. Ecotoxicological risk levels calculated for PAHs suggested that there were individual PAHs, which can less frequently cause biological impairment in some samples, but no samples had constituents that may frequently cause biological impairment. Total toxic benzo[a]pyrene equivalent of ΣcPAHs varied from 10.03 to 29.7 ng/g dw and from 0.36 to 1.92 ng/g dw for total toxic tetrachlorodibenzo-p-dioxin equivalent. The level of PAHs indicated a low toxicological risk to this area.     

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．