杭州市大气PM2.5和PM10污染特征及来源解析

2006年在杭州市两个环境受体点位采集不同季节大气中PM_2.5和PM₁₀样品,同时采集了多种颗粒物源类样品,分析了其质量浓度和多种化学成分,包括21种无机元素、5种无机水溶性离子以及有机碳和元素碳等,并据此构建了杭州市PM_2.5和PM₁₀的源与受体化学成分谱;用化学质量平衡(CMB)受体模型解析其来源。结果表明,杭州市PM_2.5和PM₁₀污染较严重,其年均浓度分别为77.5μg/m³和111.0μg/m³;各主要源类对PM_2.5的贡献率依次为机动车尾气尘21.6%、硫酸盐18.8%、煤烟尘16.7%、燃油尘10.2%、硝酸盐9.9%、土壤尘8.2%、建筑水泥尘4.0%、海盐粒子1.5%。各主要源类对PM₁₀贡献率依次为土壤尘17.0%、机动车尾气尘16.9%、硫酸盐14.3%、煤烟尘13.9%、硝酸盐粒8.2%、建筑水泥尘8.0%、燃油尘5.5%、海盐粒子3.4%、冶金尘3.2%。     

顶空固相微萃取-色谱质谱联用测定饮用水中二甲基异冰片和土味素

研究了顶空固相微萃取-气相色谱质谱联用测定饮用水中二甲基异冰片和土味素的方法。结果表明,当选用聚二甲基硅氧烷(PDMS)萃取纤维萃取头,萃取温度为60℃,萃取时间为40min时,得到二甲基异冰片标准曲线方程为y=122.59+157.76x,相关系数(R)0.9998;土味素的标准曲线方程为y=14.847+180.99x,相关系数(R)0.9999;检出限为0.1ng/L,相对标准偏差在0.99%～4.05%之间,加标回收率86.4%～109.5%。     

电感耦合等离子体质谱法同时测定地下水中钴和钼

建立了一种用电感耦合等离子体质谱法同时测定水源地地下水中微量元素钴和钼的方法。与常规的元素测试方法相比,该方法可以同时快速有效地完成钴和钼测试,测试方法简单,结果准确可靠。     

高效液相色谱-电喷雾离子源-串联三重四极杆质谱法分析地表水中高氯酸盐

建立了高效液相色谱-电喷雾离子源-串联三重四极杆质谱(HPLC-ESI-MS/MS)测定地表水中高氯酸盐的方法。以Dionex IonPac AG20阴离子交换柱为分析柱,弱碱性的0.056%氨水/5 mmol/L乙酸氨为流动相,1.0 mL/min的流速,电喷雾负离子模式电离,MS/MS串联质谱为检测器,多反应监测(MRM)模式检测高氯酸盐。方法检出限达0.043μg/L,线性范围为0.2~50μg/L,线性相关系数为0.999 4,含量分别约为2、6、30μg/L的实际样品进样10次得到的相对标准偏差分别为2.47%、4.55%、0.49%,样品加标回收率在80%~109%,将该法与US EPA method314.0进行比对,结果基本吻合。     

“MMA”技术路线在太湖蓝藻水华监测中的应用

通过对3S技术整合,提出"MMA"技术路线应用于蓝藻水华监测,包括监测、测绘、分析等关键步骤。对太湖蓝藻水华研究结果表明,总体规律一致,但又有所差异。一方面,太湖蓝藻密度(CBD)、叶绿素a(Chl-a)及水华频率分布图结果均呈现"西高东低"的空间分布规律;另一方面,太湖湖心区CBD和Chl-a浓度亦较高,而遥感监测后的水华频率图显示为无水华或频率小于1%。故应参照"MMA"技术路线,综合应用3S技术,并核验比对,弥补单项技术存在的不足,全面真实反映藻类水华情况。"MMA"技术路线既适用于水华监测,亦可推广至其他环境监测工作。     

渤海湾入海溶解无机氮总量控制研究

基于渤海湾近岸海域的实际调查结果,采取生态物理耦合模型,对渤海湾的主要污染物-溶解无机氮(DIN)的基准环境容量和极小剩余海洋环境容量进行了计算。结果表明,渤海湾DIN的极小剩余海洋环境容量在Ⅰ类和Ⅱ类水质标准下均为负值,渤海湾的DIN已经超标。结合实际的海水功能区水质管理目标,应重点控制非点源的排放,加强上游携带入境污染物的处理,从总量上控制DIN入海污染通量,改善渤海湾水质。     

Migratory crustaceans as biomonitors of metal pollution in their nursery areas. The Lesina lagoon (SE Italy) as a case study

Lichens collected in an unpolluted forest (background) in November 2004, transplanted at 41 sampling sites along the Madina-Tetteh Quarshie road, retrieved in February 2005 and analysed were found to contain higher concentrations of Manganese (Mn), Vanadium (V), lead, Cadmium (Cd), Chromium (Cr) and Nickel (Ni) than in the background area. Observations showed that of all the heavy metals studied, Manganese concentrations were highest at all sampling points with maximum values around a traffic light, an intersection and car fitting/mechanic workshops. Significant correlations were found between Ni and Mn, Mn and Cr and Mn and V. Statistical analysis also revealed a relatively even dispersion of the studied elements on the eastern side of the road than on the western side.     

Fecal source tracking by antibiotic resistance analysis on a watershed exhibiting low resistance

The ongoing development of microbial source tracking has made it possible to identify contamination sources with varying accuracy, depending on the method used. The purpose of this study was to test the efficiency of the antibiotic resistance analysis (ARA) method under low resistance by tracking the fecal sources at Turkey Creek, Oklahoma exhibiting this condition. The resistance patterns of 772 water-isolates, tested with nine antibiotics, were analyzed by discriminant analysis (DA) utilizing a five-source library containing 2250 isolates. The library passed various representativeness tests; however, two of the pulled-sample tests suggested insufficient sampling. The resubstitution test of the library individual sources showed significant isolate misclassification with an average rate of correct classification (ARCC) of 58%. These misclassifications were explained by low antibiotic resistance (Wilcoxon test P < 0.0001). Seasonal DA of stream E. coli isolates for the pooled sources human/livestock/deer indicated that in fall, the human source dominated (P < 0.0001) at a rate of 56%, and that human and livestock respective contributions in winter (35 and 39%), spring (43 and 40%), and summer (37 and 35%) were similar. Deer scored lower (17–28%) than human and livestock at every season. The DA was revised using results from a misclassification analysis to provide a perspective of the effect caused by low antibiotic resistance and a more realistic determination of the fecal source rates at Turkey Creek. The revision increased livestock rates by 13–14% (0.04 ≤ P ≤ 0.06), and decreased human and deer by 6–7%. Negative misclassification into livestock was significant (0.04 ≤ P ≤ 0.06). Low antibiotic resistance showed the greatest effect in this category.     

Nutrient dynamics between sediment and overlying water in the inner part of Izmir Bay, Eastern Aegean

In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0–20, 20–63, 63–2,000 μ) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.     

北京市昌平区大气环境PM10中多环芳烃的含量及变化趋势

通过采集了2004～2006年北京市昌平区四个季节中大气PM10样品,采用超声抽提方法,使用GC/MS分析了该区PAHs含量和组成.结果显示,三年中四个季度的18种PAHs总量范围分别为21.64～656.39ng/m3、31.94～164.33ng/m3和7.294～209.3ng/m3,其中致癌性极强的苯并[a]芘含量范围为2.69～36.95 ng/m3、1.44～6.6ng/m3和0.256～8.625ng/m1,其变化趋势与PAHs总量有较好的相关性.PAHs的浓度是冬季＞秋季＞夏季＞春季,这与夏季时雨水冲刷和阳光照射强度大导致PAHs光解,冬季时燃煤排放大等影响因素有关.文章还使用多种方法判断昌平区大气PM10中的PAHs主要来源于燃煤和汽车尾气,其它污染源贡献较小.