区域红壤资源信息系统的建立

将GIS技术与数学模型相结合,探讨区域红壤资源信息系统的建立与应用.在明确红壤资源信息系统研制的目的、任务与基本原则的基础上,进行系统的总体设计.划分系统的模块和确定系统的各个组成部分,并确定系统的软硬件配置、设计系统界面.建立空间数据库及多种分析与应用模型.     

污染土壤添加有机物质对黑麦草吸收铜的影响

研究了泥炭和堆肥对铜污染土壤盆栽黑麦草吸收铜状况的影响。结果表明 ,黑麦草地上、地下部含铜量皆随土壤污染水平提高而增加 ,地下部的增幅远大于地上部 ;添加有机物质明显降低了黑麦草地上、地下部的含铜量 ,平均降幅近 3 0 %。泥炭降低黑麦草地上、地下部含铜量的作用随土壤污染水平的提高而逐渐变小 ,而堆肥的作用至重度污染水平仍较明显 ;在近 4 0 0mg/kg铜污染水平上 ,有机物质表现出最佳降低植株铜吸收量的效果。有机物质的控制作用与土壤pH有关 ,并在 3茬黑麦草的试验期间内得以维持     

单甲脒饱和蒸气压的测定和估算

用气体的法测单甲脒在１５,２５,３５和４５℃时的饱和蒸气分别为０．２０２,０．５５４６,１．９５,６．２９Ｐａ;亨利常数计算值分别为６．３０×１０＾－４,１．６７×１０＾－３,５．６８×１０＾０－３和１．７８×１０＆－２,根据Ｃｌａｕｓｉｕｓ Ｃｌａｐｅｙｒｏｎ方程求出单甲脒在常温下气化热为８９．２ｋＪ．ｍｏｌ＾－１。     

渤海排污口邻近海域异养细菌的组成与分布

对渤海4个重点监测排污口（北塘、大蒲河、弥河和虞河）邻近海域异养细菌的组成和分布进行了调查研究。结果表明,分离到的各排污口邻近海域的细菌隶属于变形菌门（Proteobacteria）、厚壁菌门（Firmicutes）、放线菌门（Acti-nobacteria）和拟杆菌门（Bacteroidetes）4个细菌类群,其中变形菌门的细菌最丰富。各排污口的优势菌有所不同,北塘、弥河2个采样点的优势菌分别为Bacillus sp．、Pseudoalteromonas sp．,大蒲河采样点的优势菌为Vibrio sp．和Oceanospirillum sp．,虞河采样点的优势菌为 Shewanella sp．和 Bacillus sp．。多维尺度分析表明,北塘和虞河采样点的细菌种群特征较相近,细菌种群分布特征可能与排污口的海洋环境有一定的相关性。     

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.     

云南曲靖某煤化工基地及周边土壤中多环芳烃的检测研究

采用快速溶剂提取处理土壤样品,利用气相色谱质谱内标法测定土壤中多环芳烃,其检出限范围为2.01~3.68μg/kg,相对标准偏差为2.6%~14.7%,加标回收率为67.1%~119%。结果表明,此方法具有良好的灵敏度、准确度和精密度。本研究对11个不同采样点土壤进行了检测分析,并考察了土壤中多环芳烃的污染水平。     

基于PSO-SVM算法的环境监测数据异常检测和缺失补全

针对环境监测数据异常和数据缺失问题,提出了基于支持向量机的粒子群优化数据异常检测和缺失补全算法。利用粒子群优化算法选取较优的支持向量机训练参数组合,以此建立非线性的支持向量机模型,并利用结果模型对测得的真实数据拟合预测。以宁夏回族自治区某污水处理厂的污染物测量数据作为实验数据,结果表明,利用该算法预测数据的准确率可达97.977%,检测异常数据准确度高,缺失数据补全正确。     

固相萃取-GC/MS法测定水中持久性有机污染物

采用Envi-18固相萃取小柱富集水样,用正己烷/丙酮混合溶剂洗脱水样中42种POPs化合物,再用气质联用法测定。通过优化仪器监测条件,使目标物在0.250 mg/L~5.00 mg/L范围内线性良好。方法检出限为50.9 ng/L~11 640 ng/L,实际水样加标回收率为57.1%~129%,测定结果的RSD为0.1%~13.8%。将该方法用于测定浙江省东苕溪流域的45份水样,结果滴滴涕、六六六等有机氯农药的检出率较高,其他POPs的检出率较低。