共基质对10株细菌降解苯并芘的作用研究

从石油污染的污泥中分离驯化出10株细菌（SB01-SB10）,利用生物摇床实验对其降解苯并芘（BaP）的效能进行试验,研究了有（或无）共基质（葡萄糖Glu,或菲PHE）对细菌降解BaP的影响,并采用ANOVA和Tukey多重比较进行分析。结果表明,（1）当以BaP为惟一碳源和能源且BaP初始浓度为50mg·L^-1时（MS1）,SB01的降解率最高,5d可降解31．0％;以Glu为共代谢基质时（MS2）,SB09的降解率最高,可达36．9％;以PHE为共代谢基质时（MS3）,SB01对BaP的降解率为46．0％。（2）Glu对SB01、SB02、SB03、SB07、SB10降解BaP有抑制作用,对SB01抑制作用最明显,使SB01的降解率降低了13．1％,Glu对SB05,SB08降解率无明显促进或抑制作用。（3）PHE对细菌降解BaP均表现出促进作用,对SB01的促进作用最明显,使其降解率提高15．0％。（4）Glu对SB09的促进作用大于PHE的促进作用。而对SB06,PHE的促进作用大于Glu。     

均匀设计在固定化毛霉载体配方优化中的应用

将均匀设计方法应用于固定化毛霉(Mucorsp.)载体配方优化中。在单因素实验基础上,采用U(1557)均匀设计表对影响毛霉生长的主要营养因子进行优化,利用SPSS建立了固定化毛霉对土壤中芘、苯并(a)芘(BaP)和总多环芳烃(PAHs)降解率的回归方程。结果表明,全相关系数分别达到0.999,0.997和0.997。而后通过无约束规划求解获得了固定化载体最佳配方:玉米芯92.1%,豆饼4.8%,CaSO41.6%,白糖1.4%,MgSO40.2%,有效地提高了固定化毛霉对土壤中PAHs的降解率,为将固定化微生物技术应用于非流体介质中PAHs污染的原位修复提供了可行途径,而且该载体配方用料来源广泛,成本低廉,工艺简单,安全无毒。     

长期石油污水灌溉对东北旱田土壤微生物生物量及土壤酶活性的影响

以土壤微生物生物量和土壤酶活性等为土壤微生物变化指标,研究了含油污水长期灌溉对东北沈抚灌区农田土壤微生物的影响.结果表明:土壤微生物生物量碳和生物量氮随着污灌有机物污染程度的增加而增加,与土壤石油烃(TPH)含量极显著正相关,相关系数分别为0.955和0.962(P<0.01);与土壤多环芳烃(PAHs)含量也极显著正相关,相关系数为0.941和0.946(P<0.01).土壤酶活性分析表明,土壤脱氢酶和多酚氧化酶与土壤TPH含量极显著正相关,相关系数分别为0.977和0.958(P<0.01);与PAHs含量也极显著正相关,相关系数分别为0.997和0.977(P<0.01).土壤中的脲酶受污水灌溉中含N物质的影响与TPH含量显著相关,相关系数为0.713(P<0.05),与PAHs污染无明显相关性.而纤维素酶与土壤有机物污染无明显相关关系.土壤微生物生物量和土壤脱氢酶、多酚氧化酶可以作为污灌土壤TPH和PAHs污染敏感的生物学和生物化学指标.     

安徽省典型城市周边土壤-蔬菜中PAHs的污染特征

研究了安徽省合肥、芜湖和亳州市周边蔬菜地土壤和蔬菜中PAHs的含量及其污染特征。结果表明：安徽省典型蔬菜地土壤中15种PAHs（除萘外）的残留总量在58.2～437.8μg·kg-1之间,三环和四环PAHs占PAHs残留总量的70%以上。胡萝卜、菠菜和茄子体内15种PAHs的含量在23.4～209.1μg·kg-1之间,均值为120.7μg·kg-1,三环和四环PAHs占蔬菜中PAHs富集总量的92.8%～94.4%。不同蔬菜体内8种可疑性致癌PAHs的含量在11.5～17.4μg·kg-1之间,分别占蔬菜中PAHs残留总量的9.80%～13.8%,其中BaP含量在1.69～2.03μg·kg-1之间,低于国家对食品中污染物（BaP）的限量标准（5μg·kg-1）。不同类型PAHs在蔬菜体内的富集系数在0.10～9.20之间,极差达10倍以上,低分子量PAHs在蔬菜体内的富集系数要大于高分子量PAHs。不同PAHs在蔬菜体内的富集系数表现为胡萝卜〉菠菜〉茄子,其中芴在蔬菜体内的富集系数最高。     

庐山南北坡苔藓中PAHs污染特征研究

[目的]对庐山南北坡21个采样点大灰藓（Hypnum plumaeforme）样品中16种PAHs进行定量分析,[方法]研究了庐山地区苔藓中多环芳烃的含量水平,南北坡空间分布差异和海拔梯度分布特征。[结果]庐山地区大灰藓中∑PAHs与已有报道中背景区含量水平接近,浓度范围为371.5～842.8ng/g,其中菲含量最高,不同环数PAHs呈现出3环〉4环〉2环〉5环〉6环依次递减的趋势。庐山北坡高分子量PAHs（HMWPAHs）含量显著高于南坡,这是导致南北坡PAHs空间分布差异的主要原因,而来自于远距离输送的低分子量PAHs（LMWPAHs）在不同坡向含量水平相当。[结论]苔藓中PAHs含量受当地旅游经济发展和地形地势综合影响,海拔梯度分布特征不明显。     

净化液处理对豇豆采后多环芳烃(PAHs)的净化效果研究

为降低蔬菜采后体内多环芳烃(PAHs)对人体的危害风险,以豇豆为材料,利用不同浓度洗洁精、食盐、米酒、米醋、植物油及清水分别对豇豆豆荚进行浸洗,通过高效液相色谱-质谱联用法检测豇豆采后体内PAHs的含量,并筛选出豇豆体内PAHs的最佳净化方法。结果表明,米酒和米醋处理对豇豆体内PAHs的去除效果基本一致,其中米酒处理组的∑PAHs（美国环保局公布的优先监测的16种多环芳烃的含量总和）降低68.92%,米醋处理组的∑PAHs降低73.88%,且对萘、二苯并(a,h)蒽和茚并(1,2,3-c,d)芘等均有明显的去除效果;清水浸洗可有效降低豇豆体内的茚并(1,2,3-c,d)芘含量,但会使菲的含量增加;食盐处理使∑PAHs增加了77.15%,主要表现在增加了2、3环PAHs在豇豆体内的积累;植物油处理可降低个别PAHs单体含量,但会引入其他PAHs单体,同时增加∑PAHs含量。毒性当量计算结果表明,米酒能有效降低豇豆体内的PAHs毒性,同时食盐处理也使豇豆体内的PAHs毒性当量降低。米酒和米醋能有效降低豇豆体内∑PAHs和二苯并(a,h)蒽的含量及其毒性当量。     

黄河兰州段多环芳烃生态风险的初步评价

以黄河兰州段11个不同采样点3种多环芳烃的临测浓度及其对6～38种水生生物的LC50为基础资料,分别应用商值法、概率密度函数重叠面积和联合概率曲线3种风险浮价方法对黄河兰州段苯并(a)芘、荧蒽、芘的生态风险进行了评价.结果表明:黄河兰州段3种PAHs残留具有一定的生态风险.其中低暴露风险条件下(受威胁生物不超过1%),...     

淮河中下游干流贝类体中多环芳烃的分布及风险评价（摘要）

[目的]探讨淮河流域贝类体中PAHs污染情况,为淮河居民安全食用贝类提供科学依据。[方法]在淮河中下游干流吴小街和浮山集两处采集悬浮物、沉积物物和贝类样品。将1 L水样抽真空过0.45μm玻璃纤维滤膜得悬浮物样品,沉积物阴凉处自然风干;贝类经鉴定均为短褶矛蚌,去壳,阴凉处风干。称取已过100目尼龙筛的沉积物干样10g,加入10g无水硫酸钠,1 g纯铜粉（除硫）,混均,用120 ml二氯甲烷在水浴65℃下索氏提取48j。将提取液浓缩至约0.5 ml,经无水硫酸钠脱水,过硅胶/氧化铝柱分离净化,用正己烷/二氯甲烷（1：1,V/V）混合液淋洗得PAHs组分。将淋洗液浓缩至0.1 ml,正己烷定容至1.0 ml,冷冻保存,作GC-MS检测。悬浮物干样的处理类似于沉积物。利用外标法定量计算环境样品中PAHs含量。在样品分析过程中,增加方法空白和加标空白。[结果]淮河中下游两采样点中,1号点吴小街处悬浮物、沉积物中PAHs总量均远大于2号点浮山集中含量,但两处矛蚌体中PAHs总含量则相差不大。1号点位于2号点上游,毗邻蚌埠市,而2号点流域基本上是农村和乡镇,沿岸污染较少,加之水体自净作用,故1号点悬浮物和沉积物中PAHs偏高。矛蚌自身用于代谢的混合氧化系统存在缺陷,体内化合物的释放较慢,富集于矛蚌体中的PAHs代谢较慢,因此两采样点处矛蚌体中PAHs含量存在空间差距,时间差距较小,其含量相差不大。两点环境介质中PAHs含量均呈现出悬浮物〉矛蚌〉沉积物的分布特征。2号采样点处设有采砂场,水体搅动相对频繁,沉积物再悬浮作用显著,因此悬浮物中PAHs含量远高于沉积物中含量。矛蚌因本身的生物特性,易富集PAHs,其含量亦高于沉积物中含量。就多环芳烃单组分特征而言,淮河中下游两采样点悬浮物中均以低环PAHs为主,矛蚌体中均以高环PAHs为主。高环PAHs的沉积物/水分配系数（KOC）值较大,主要吸附于沉积相,难迁移转化,相对而言,低环PAHs易载于悬浮物颗粒上,随水流迁移,因此两点悬浮物中低环PAHs含量较高。PAHs随环数增加,稳定性增加,降解速率降低,因此矛蚌体中5、6环的PAHs含量较高。沉积物中则1号点吴小街以低环PAHs为主,2号点浮山集以高环为主。[结论]通过对环境介质中PAHs进行生态风险评价看出,沉积物中PAHs的潜在生态风险很小,沉积物和矛蚌尚未受到污染（PAHs污染指数均小于0.5）,但其周围环境中PAHs含量较高,应对PAHs的潜在危害予以重视。     

大气颗粒物中多环芳烃的研究

系统地讨论了大气颗粒物中PAHs的研究状况,并对其来源和分布、采样技术、样品预处理、分离分析方法进行了阐述。     

Organic geochemical parameters for estimation of petrogenic inputs in the coastal area of Kavala City,Greece

Background, aims, and scope  Sediments and soils in coastal areas are frequently polluted by anthropogenic contaminants as the result of both riverine or terrestrial discharge and autochthonic marine emissions. In order to determine petrogenic contamination in the coastal industrial area of Kavala City in northern Greece, a combination of polycyclic aromatic hydrocarbon (PAH) and organic geochemical petroleum biomarker analyses has been performed on marine and freshwater sediments as well as soils. Materials and methods  Soils, freshwater, and marine sediments have been treated by standard extraction methods. The dried and desulphurized sample extracts have been fractionated by column chromatography, followed by addition of surrogate standards. Qualitative and quantitative data were obtained by gas chromatograph connected with a flame ionization and electron capture detector (GC-FID/ECD) and by GC linked to a mass spectrometer (GC/MS), whereas identification of compounds was based on EI⁺-mass spectra and gas chromatographic retention times. Quantitative data were obtained by integration of specific ion chromatograms. Results  The total PAH concentrations measured in the area varied highly, showing different levels from 18 up to 318,000 ng g⁻¹ dry weight (dw). Several PAH ratios, as well as the ratio of pristane (Pr) to phytane (Phyt), have been considered. Out of 39 samples, 22 revealed a specific distribution of hopane fingerprints indicating petrogenic input. Finally, in numerous samples, the ratio of 17α(H)-22,29,30-trisnorhopane (Tm) and 18α(H)-22,29,30-trisnorhopane (Ts) was calculated, as well as the ratio of 22S-17α(H),21β(H)-30 homohopane (αβC₃₁-hopane 22S) and 22R-17α(H),21β(H)-30 homohopane (αβC₃₁-hopane 22R). Discussion  Based on the specific PAH ratios, a group of samples was clearly characterized to be contaminated dominantly by combustion-derived emissions, whereas a second group of samples exhibited mixed influence from petrogenic and pyrogenic PAHs. On the other hand, the exhibition of specific hopane fingerprints in many samples indicates a direct petrogenic input. Finally, the values of the ratio of Tm/(Ts + Tm) and of αβC₃₁-hopanes 22S/(22S+22R)-isomer demonstrated an input of highly mature organic matter that has to be clearly attributed to petroleum-derived contamination, while the ratio of Pr/Phyt showed that most samples exhibited an input of organic matter. Conclusions  The coastal area of Kavala is strongly affected by anthropogenic contaminants. Petrogenic emissions were pointed out firstly by PAH analyses that separated dominantly pyrogenic contaminated sites from areas affected by both pyrogenic and petrogenic emissions. However, analyses of organic geochemical biomarkers revealed a much higher sensitivity in identifying petroleum-derived contaminations and were successfully used to differentiate several petrogenic contaminations in the marine and terrestrial samples. Recommendations and perspectives  Based on this study, it was recommended to use a complementary approach of source-specific substances to successfully characterize petrogenic emissions. Generally, a PAH-based source identification of petrogenic versus pyrogenic contaminations should be combined with petroleum biomarker analysis. PAH and biomarker ratios as well as individual biomarker fingerprints revealed a more comprehensive view on the quality and quantity of petrogenic emissions in sediments and soils.