沈阳市降雪中PFOS和PFOA污染现状调查

通过调查降雪中PFOS和PFOA的浓度,阐明了沈阳市大气中PFOS和PFOA的污染状况和污染规律.2006-02-06采集沈阳市区和郊区共计36个采样点的降雪样品,2006-02-25在其中5个采样点再次采集降雪样品.固相萃取融雪水中的PFOS和PFOA,利用LC-MS-SIM法测定样品中PFOS和PFOA浓度.全部样品中均检出PFOS和PFOA.2006-02-06降雪中PFOS和PFOA的浓度几何平均值分别为2.0 ng·L^-1（范围：0.4～46.2 ng·L^-1）和3.6 ng·L^-1（范围：1.6～22.4 ng·L^-1）,95%置信区间分别为1.5～2.8 ng·L^-1和3.1～4.2 ng·L^-1.PFOS和PFOA的最高浓度同时出现在郊区采样点朱尔屯,市中心区2种物质的浓度呈显著正相关.2006-02-25的5个采样点降雪中PFOS和PFOA的浓度几何平均值均为2.2 ng·L^-1.2次降雪中PFOS浓度差异不显著,2006-02-25降雪中PFOA浓度高于2006-02-06.结果表明,沈阳市区和郊区降雪中广泛存在PFOS和PFOA污染,局部区域可能存在共同的PFOS和PFOA污染来源;沈阳地区有较稳定的PFOS来源持续向大气中输送该类物质;PFOS和PFOA的环境行为可能不同.     

沙蚕暴露于石油烃、Cu2+和Cd2+毒性效应及乙酰胆碱酯酶活性的响应

采用浓度梯度污染暴露室内模拟方法,研究了沙蚕（Perinereis aibuhitensis Grube）暴露于不同浓度的石油烃和重金属Cu²⁺、Cd²⁺的毒性效应及乙酰胆碱酯酶活性的响应.结果表明,石油烃和Cd²⁺、Cu²⁺对沙蚕均具有较强的毒性效应.暴露4 d和10 d后,石油烃LC₅₀分别为440和110 μg·L^-1,Cu²⁺分别为1 150和570 μg·L^-1,Cd²⁺分别为5 090和2 500 μg·L^-1,相应的生态毒性大小为：石油烃＞Cu²⁺＞Cd²⁺.在Cd²⁺、Cu²⁺污染暴露条件下,沙蚕体内乙酰胆碱酯酶活性受到一定程度的抑制,但抑制率均低于50％.而在石油烃污染暴露条件下,沙蚕体内乙酰胆碱酯酶活性受到显著抑制,最高抑制率可达90％以上;而且,其乙酰胆碱酯酶活性的变化与石油烃的浓度显著相关.可见,乙酰胆碱酯酶活性的变化可以作为生物标志物,较灵敏地反映出石油烃对沙蚕的污染效应及其毒害作用.     

城市污染河道沉积物AVS与重金属生物毒性研究

采集珠江三角洲典型城市污染河道佛山水道表层沉积物和上覆水样品,测定了沉积物AVS,Eh,SEM_Pb,SEM_Cd,SEM_Cu,SEM_Zn,SEM_Ni,SEM_Cr,及上覆水Eh,DO.同步进行了底栖动物调查,结合调查结果分析了城市污染河道沉积物AVS与重金属生物毒性的关系.主要研究SEM-AVS判据在判断城市重污染河道重金属生物有效性方面的作用.所测AVS最大值为69.579 μmol/g,最小值为0.339 μmol/g,均值为20.283 μmol/g;各采样站位∑SEM₅（SEM_Pb,SEM_Cd,SEM_Cu,SEM_Zn,SEM_Ni之和）最大值为23.067 μmol/g,最小值为1.062 μmol/g;底栖动物种类和数量均较少,且基本为耐污种,优势种为水丝蚓.13个采样站位中,∑SEM₅-AVS<0的有9个,MDS分析结果显示：这9个站位中的7个底栖动物群落结构相似程度高.这表明重污染河道沉积物重金属的生物毒性与SEM-AVS的值关系密切,SEM-AVS判据在判断重污染区域重金属的生物毒性方面具有较大作用;同时说明重污染河流重金属生物毒性比较复杂,不能完全由SEM-AVS解释.     

我国典型土壤对病毒等温静态吸附的数值模拟

通过室内等温静态批量平衡吸附实验,采用3种常见的等温线（Freundlich方程、Langmuir方程和Temkin方程）对2种病毒（MS2和X174）在2种处理（非灭菌和灭菌）条件下的6种土壤（红壤土、红粘土、乌栅土、黄泥土、沙质潮土和壤质潮土）中的吸附行为进行了回归拟合.实验结果和模拟结果均表明,土壤性质、病毒性质、土壤中的土著微生物对病毒在土壤中吸附行为均具有重要的影响.红粘土对MS2和X174的平均吸附比例几乎能达到100％,而2种潮土（沙质潮土和壤质潮土）相对较弱;总体来看土壤对X174的吸附能力高于MS2,但灭菌后的土壤对MS2的吸附能力却高于X174.在数值模拟中,Freundlich方程和Langmuir方程均具有理想的相关性.Freundlich方程能够表现出病毒浓度对其在土壤中吸附行为的影响;尽管Langmuir方程能够应用于土壤对病毒吸附能力的比较,但本研究中不能应用Langmuir方程来计算土壤对病毒的最大吸附量.     

Determination of alkali-labile phosphoprotein phosphorus from fish plasma using the Tb^3＋-tiron complex as a fluorescence probe

A sensitive method based on the fluorescence quenching effect of the Tb^3＋-Tiron complex is proposed for the determination of alkali-labile phosphoprotein phosphorus （ALP） released from fish plasma. The detection limit was 5.4 ng/ml （S/N=2）, and the relative standard deviation of the quenching effect （6 replicates） was 4.6%. The results obtained by the proposed method were in good agreement with those obtained by the colorimetric assay. The advantages of the present method are its relatively simple detection procedure, the lack of toxic organic solvents, and high sensitivity.     

Inorganic nitrogen removal of toilet wastewater with an airlift external circulation membrane bioreactor

Removal of inorganic nitrogen (inorganic-N) from toilet wastewater, using a pilot-scale airlift external circulation membrane bioreactor (AEC-MBR) was studied. The results showed that the use of AEC-MBR with limited addition of alkaline reagents and volumetric loading rates of inorganic-N of 0.19-0.40 kg inorganic-N/(m3·d) helped achieve the desired nitrification and denitrification. Furthermore, the effects of pH and dissolved oxygen (DO) on inorganic-N removal were examined. Under the condition of MLSS at 1.56-2.35 g/L, BOD5/ammonia nitrogen (NH/-N) at 1.0, pH at 7.0-7.5, and DO at 1.0-2.0 mg/L, the removal efficiencies of NH4 -N and inorganic-N were 91.5% and 70.0%, respectively, in the AEC-MBR. The cost of addition of alkaline reagent was approximately 0.5-1.5 RMB yuan/m3, and the energy consumption was approximately 0.72 kWh/m3 at the flux of 8 L/(m2·h).     

Artificial neural network model for identifying taxi gross emitter from remote sensing data of vehicle emission

Vehicle emission has been the major source of air pollution in urban areas in the past two decades. This article proposes an artificial neural network model for identifying the taxi gross emitters based on the remote sensing data. After carrying out the field test in Guangzhou and analyzing various factors from the emission data, the artificial neural network modeling was proved to be an advisable method of identifying the gross emitters. On the basis of the principal component analysis and the selection of algorithm and architecture, the Back-Propagation neural network model with 8-17-1 architecture was established as the optimal approach for this purpose. It gave a percentage of hits of 93%. Our previous research result and the result from aggression analysis were compared, and they provided respectively the percentage of hits of 81.63% and 75%. This comparison demonstrates the potentiality and validity of the proposed method in the identification of taxi gross emitters.     

Modeling of air quality with a modified two-dimensional Eulerian model： A case study in the Pearl River Delta （PRD） region of China

A modified two-dimensional Eulerian air quality model was used to simulate both the gaseous and particulate pollutant concentrations during October 21-24, 2004 in the Pearl River Delta （PRD） region, China. The most significant improvement to the model is the added capability to predict the secondary organic aerosols （SOA） concentrations because of the inclusion of the SOA formation chemistry. The meteorological input data were prepared using the CALMET meteorological model. The concentrations of aerosol-bound species such as NO3^-, NH4^＋, SO4^2-, and SOA were calculated in the fine particle size range （〈2.5 μm）. The results of the two-dimensional model were compared to the measurements at the ground level during the PRD Intensive Monitoring Campaign （IMC）. Overall, there were good agreements between the measured and modeled concentrations of inorganic aerosol components and O3. Both the measured and the modeled results indicated that the maximum hourly O3 concentrations exceeded the China National Air Quality Standard. The predicted 24-h average SOA concentrations were in reasonable agreement with those predicted by the method of minimum OC/EC ratio.     

Residual dynamics of thiacloprid in medical herbs marjoram, thyme, and camomile and in soil

Thiacloprid is a new insecticide of the chloronicotinyl family. To assess its risk after application, residual characteristics of thiacloprid in marjoram, thyme, and camomile and in soil were studied under field conditions. The active ingredient was extracted from the plant material using a mixture of acetone-water. After filtration, the extract was concentrated to the aqueous phase, diluted with water, and portioned against ethyl acetate on a matrix solid phase dispersion column. Thiacloprid was extracted from soil using a mixture of methanol-water, filtered, and re.extracted （clean up） with dichloromethane. The residues were quantified using HPLC-MS-MS. The methods were validated by recovery experiments. Thiacloprid residues in marjoram, thyme, and camomile and in soil persisted beyond 10, 14, 14, and 21 d but no residues were detected after 14, 21, 21, and 28 d, respectively. The data obtained in this study indicated that the biexponential model is more suitable than the first-order function to describe the decline of thiacloprid in fresh marjoram, fresh thyme, and dried camomile flowers with half-life （t1/2） of 1.1, 0.7, and 1.2 d, respectively. However, both the first-order function and biexponential model were found to be applicable for dissipation of thiacloprid in soil with almost the same t1/2 values of 3.5 and 3.6 d. The results indicated that thiacloprid dissipates rapidly and does not accumulate in the tested herbs and in soil.     

Vertical and temporal distribution of nitrogen and phosphorus and relationship with their influencing factors in aquatic-terrestrial ecotone： a case study in Taihu Lake, China

Vertical and temporal distributions of N and P in soil solution in aquatic-terrestrial ecotone （ATE） of Taihu Lake were investigated, and the relations among N, P, ORP （oxidation reduction potential）, TOC, root system biomass and microorganism were studied. As a whole, significant declines in TN, NO3^--N, DON （dissolved organic nitrogen） and TP concentration in soil solution have occurred with increase of the depth, and reached their minima at 60 cm depth, except for NH4^＋-N, which increased with depth. The concentration of TP increased gradually from spring to winter in the topsoil, the maximum 0.08 mg/L presented in the winter while the minimum 0.03 mg/L in spring. In the deeper layer, the concentration value of TP fluctuated little. As for the NO3^--N, its seasonal variation was significant at 20 cm depth, its concentration increased gradually from spring to autumn, and decreased markedly in winter. Vertical and temporal distribution of DON is contrary to that of NO3^--N. The results also show that the variation of N and P in the percolate between adjacent layers is obviously different. The vertical variation ofTN, TP, NO3^--N, NH4^＋-N and DON is significant, of which the variation coefficient of NO3^--N along the depth reaches 100.23%, the highest; while the variation coefficient of DON is 41.14%, the smallest. The results of correlation analysis show that the concentration of nitrogen and phosphorus correlate significantly with TOC, ORP, root biomass and counts of nitrifying bacteria. Most nutrients altered much from 20 to 40 cm along the depth. However, DON changed more between 60 and 80 cm. Results show that soil of 0-60 cm depth is active rhizoplane, with strong capability to remove the nitrogen and phosphorus in ATE. It may suggest that there exists the optimum ecological efficiency in the depth of above 60 cm in reed wetland. This will be very significant for ecological restoration and reestablishment.