Polycyclic Aromatic Compounds in the Greenland Marine Environment

Information on levels of polycyclic aromatic compounds (PACs) in the marine environment from pristine areas of the world are still sparse. In this study, PACs were analyzed in sediments and various organisms from the area of Qeqertarsuaq/Disko in the western part of Greenland. PAC levels were measured in sediments, blue mussels ( Mytilus edulis ), liver of shorthorn sculpins ( Myoxocephalus scorpius ), and blubber of ringed seals ( Phoca hispida ). The average levels of PAC in the four sample types were 359 w g/kg, 497 w g/kg, 2762 w g/kg, and 101 w g/kg dry weight respectively. Principal component analyses (PCA) revealed variations in PAC composition between the different samples that could be related to molecular weight of the PAC compounds and lifestyle characteristics of the biota.     

Multivariate Analysis of Polycyclic Aromatic Compounds in Suspended Particulate

Abstract

The monitoring of air quality today provides a number of parameter values measured as a function of time. In the urban atmosphere, and especially in the particulates, increasing importance is being given to the presence of polycyclic aromatic compounds (PAC), particularly since some are known to be carcinogenic. As the number of measured parameters increases, examining the data and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous statistical techniques have been introduced in chemistry, such as Multivariate Data Analysis (MVDA): Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR). The first technique has been applied in this work to the interpretation of the quality of Augusta (Siracusa, Italy) urban air by measuring the concentration of numerous PAC in the particulates in different sites and at different times. The MVDA has highlighted the similarity between various sampling sites whose data were initially thought to be different. Furthermore, it has allowed a choice of more significant parameters for future PAC monitoring and more suitable sampling site locations.     

聚类分析在古龙油田沉积成岩相研究中的应用

聚类分析是研究样本（或变量）分类的一种多元统计方法,通过分析各样本或变量间自寺相似性逐步归类。本文以古龙油田为例,运用了聚类分析中的Q型分层聚类法,研究了古龙油田葡萄花油层组沉积成岩相的类型,并对样品进行归类,得出沉积成岩相的空间展布规律。结果表明：该方法在储层评价中的应用是可行的,具有较强的合理性。