Comprehensive Environmental Investigation at Former Industrial/Petroleum Underground Storage Tank Sites in Long Beach,CA: A Forensic Perspective

Two industrial sites were investigated based on years of available hydrogeologic information and monitoring data for soil and groundwater. Collected data were forensically evaluated using age-dating and fingerprinting methods. The previous business uses of the project sites were as a gas station, laundry/dry-cleaning service, and car wash with petroleum underground storage tanks (USTs). As a result, these sites were exposed to a number of toxic contaminants at relatively high concentrations. Source control was necessary for successful remediation and the ultimate removal of the remaining compounds from these industrial sites. Although contaminated soil around the source was excavated during the remedial action and the high concentrations of contaminants were reduced, typical groundwater contaminants such as petroleum hydrocarbons as gasoline (TPH-G), benzene, toluene, ethylbenzene, xylenes (BTEX), and oxygenates including methyl tert-butyl ether (MTBE), diisopropyl ether (DIPE), ethyl tert-butyl ether (ETBE), tert-amyl methyl ether (TAME), and tert-butyl alcohol (TBA) were persistently found at the studied sites around the source points. The plume and concentration of contaminants had changed their shapes and strength for all monitoring periods. Thus, additional source control seems to be a requirement for the complete removal of source contamination, which must be ascertained with groundwater and soil monitoring on a regular time base. For the study sites, monitored natural attenuation was relatively feasible for the long-term plan; however, it did not offer a perfect remediation solution for an ultimate goal because of residual toxic compounds that might have affected the surrounding residential areas at higher concentrations than their health limits. Therefore, as a remediation strategy, the combination of clean-up technology and natural attenuation with monitoring activities are more highly recommended than either clean-up or natural attenuation used separately.     

欧美等发达国家水环境监测方法体系

分别简述了美国、欧盟和日本等发达国家或组织水环境监测方法体系发展历程,分析了其各自水环境监测方法体系特点。对中国水环境监测方法体系的制定与实施提出了建议。     

油井远程监控与综合评价系统开发

为解决油田管理中面临的用工总量多、生产建设成本高和管理难度大的问题,胜利油田进行了大规模数字化建设。通过电参数、示功图、产液量自动采集传输,对油井进行综合评价分析,提出节电意见,确保油井安全正常运转,有效地减少了油田生产用工需求,进一步促进了油田管理的现代化。     

大气细粒子(PM2.5)监测技术进展

大气细粒子(PM2.5)的污染对人和生态环境等影响巨大,迫切需要进行PM2.5质量浓度的监测;本文介绍了PM2.5国内外监测研究进展、监测网络应用情况以及监测技术;重点介绍了几种先进的技术:β射线法、振荡天平法和光散射法,并详细描述了各种监测设备的原理及结构,提出最好采用PM2.5在线监测仪进行日常监测。     

PM2.5在线监测技术概述

针对PM2.5颗粒物监测技术和PM2.5的监测网络的建设,重点介绍了美国多年来对PM2.5的监测状况,以及采用的Beta射线法、Beta射线光浊度法、微量振荡天平法等监测技术的方法和原理;指出综合国内外多年的监测经验,PM2.5的在线监测需要经过大量手工经典方法数据作为比对和校验,才能给出有效而高质量的PM2.5监测数据。     

基于RS和GIS的山东省17城市生态环境质量动态变化研究

运用遥感动态监测与地理信息系统技术相结合的方法,以2005年和2009年遥感解译数据、土地侵蚀数据及环境统计数据为数据源,依据《生态环境状况评价技术规范(试行)》(HJ/T192-2006),对山东省17个城市生态环境质量现状及动态变化趋势进行了评价。结果表明:2009年17个城市生态环境状况指数在59.81～78.08之间,生态环境质量状况总体良好;2005-2009年17城市生态环境状况指数变化值在0.06～3.5之间,生态环境质量状况基本稳定。     

秦皇岛海岸侵蚀动态研究

利用不同时期的地形图、遥感图片对比,并选取典型海岸岸滩监测剖面实测数据,对海岸侵蚀现状进行了分析和定量计算。分析结果显示,秦皇岛海岸全线处于侵蚀状态,平均蚀退率1.5～4 m/a,根据蚀退率可将秦皇岛海岸划分为严重侵蚀、强侵蚀、侵蚀、微侵蚀、稳定5种岸线侵蚀类型。     

Pb-Al relationships in waterfowl feces discriminate between sources of Pb exposure

Hunted mallards (n = 56) were collected in the Ebro Delta (Spain) in 2007-08 to evaluate the use of feces as a non-invasive monitoring method to study lead shot ingestion. The prevalence of Pb shot ingestion in these birds was 28.6%, and similar to that reported before a ban on Pb shot use in 2003. Lead concentrations in terminal intestinal contents were higher in mallards with Pb shot in their gizzard. Feces Pb concentrations >34 μg/g d.w were indicative of Pb shot ingestion, and background Pb levels were <12.5 μg/g d.w. To discriminate between birds ingesting soil Pb, and those ingesting Pb shot, we correlated Al and Pb levels and showed that mallards with ingested Pb shot in the gizzard stood out as outliers within the regression. Feces Pb-Al relationships can be used as a simple non-invasive tool in monitoring programs regarding Pb shot ingestion in birds.     

Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of ^131mXe, ¹³³Xe, ^133mXe, and ¹³⁵Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naïve Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment.