基于人体健康风险评估的冶炼行业污染场地风险管理与决策流程

简述了冶炼行业污染场地风险管理和风险评估流程。在借鉴国内外相关经验和教训的基础上,结合我国冶炼行业的特点,提出了基于层次性人体健康风险评估的冶炼行业污染场地风险管理与决策框架体系,利用该框架体系,通过层次性风险评估,可以筛选风险大的场地进行重点监管,并采取有针对性的措施防治污染扩散及消除对人体和生态环境的风险,从而经济有效地实现对冶炼行业污染场地的监管。     

三维可视化建模方法在污染场地中的应用

以某搬迁的电池厂原址场地为研究对象,利用场地地层勘探数据和土壤样品检测结果建立场地三维污染预测模型,对模型参数进行优化选择,在三维污染模型构建过程中采用交叉验证分析方法选择最优插值方法及参数,并对场地土壤中重金属铅的污染分布进行三维可视化预测分析。结果表明：三维地层模型构建过程中,样点最小间距设置为40 m×40 m,邻近点插值法最适合描述场地的地形地貌特征;克里格插值法更为适合进行场地污染特征插值分析。建立了三维可视化建模方法分析场地污染特征与场地地层及生产布局之间的相关性。     

污染场地地下水污染风险分级技术方法研究

借鉴国内外地下水污染风险分级方法,综合分析污染场地对地下水产生风险的关键环节,采用层次分析法,从场地本身存在的风险、场地区域地下水固有脆弱性和场地周边地下水的保护目标特征3个方面,建立了由17个指标构成的污染场地地下水污染风险分级指标体系。在此基础上,以典型污染场地实地调研结果和159种典型地下水污染物理化特性为数据基础,对各指标进行了风险水平的划分,基于聚类分析法,采用各指标风险指数相乘的风险表征方法计算总风险指数,构建了污染场地地下水污染风险分级技术方法。该方法可有效避免指标权重计算的主观性,并且能够直观地反映出导致风险的主要因素。结果表明:利用建立的风险分级技术方法可将我国典型污染场地地下水污染风险划分为3级,风险小于5为一级,风险在5~15为二级,风险大于15为三级。实际应用于某危险废物填埋场的结果表明,该危险废物填埋场地下水污染风险为三级,同时得出场地本身存在的风险,特别是场地特征污染物,是造成该危险废物填埋场地下水污染风险的主要因素。     

污染场地中挥发性有机污染工程修复技术及应用

工业企业环保搬迁后遗留的大量污染场地的修复面临着严峻挑战,其中尤以挥发性有机物遗留污染场地为甚。国外关于挥发性有机物的工程修复技术已较为成熟,且应用广泛,但国内场地工程修复案例较少,且依据于各地经济社会水平的修复技术筛选问题仍是制约我国污染场地修复的主要瓶颈。因此,为推动挥发性有机物工程修复技术在我国污染场地修复中的应用,介绍了挥发性有机物工程修复技术的主要类型及原理,并就其技术本身、修复周期、费用等方面进行比较;结合美国超级基金项目中近30年来的应用情况,探讨各种工程修复技术的工程应用及其发展趋势。     

基于DESYRE模型的污染场地修复决策研究

利用DESYRE模型对中国北方某污染场地的修复问题进行研究,在综合分析场地的污染物分布状况、污染物毒理性质和暴露途径的基础上,确定了污染物在不同土地使用方式下的风险等级分布;利用已有的修复技术数据库,筛选出较好的修复技术,并对修复效果进行模拟,提供修复技术选择和场地使用方案制定的依据。结果表明,该场地的最佳用地方式为居住用地或娱乐用地,清挖/处理技术与土壤固化/稳定技术（异位）配合应用修复效果较好。DESYRE模型应用结果较为理想,可以对该模型做进一步改进,使之更符合中国的实际情况。     

辐射环境监测优化布点的特征分析方法

介绍了特征分析方法的基本原理及其MATLAB语言实现过程,并将特征分析法、传统布点法,以及BP人工神经网络法对同一地区辐射环境监测优化布点的核素含量均值作了比较,结果表明,用特征分析法优选出的采样点位,其核素含量均值对传统布点法的相对偏差均为负值,且＜10%,即便与BP法相比,也不失其优越性,表明用特征分析法监测一个地区环境辐射平均水平的优化布点是十分理想的.     

固化/稳定化修复后场地土壤中铬的环境行为与归趋

土壤重金属铬(Cr)污染形势严峻,对人群健康和生态环境构成了严重威胁。通过固化/稳定化技术降低土壤中金属的毒性或迁移性,是Cr污染场地常用的修复技术之一。由于Cr的环境行为变化多端、机制复杂,故导致固化/稳定化修复后场地存在Cr污染反弹的环境风险。综述了Cr在土壤中的氧化还原、吸附与解吸、沉淀与溶解,以及植物、微生物吸收与转化等多种环境行为;并梳理了已修复的Cr污染场地案例及场地长期跟踪监测数据,探讨了固化/稳定化修复后Cr的环境归趋及其影响因素,以期为修复后场地的风险管理提供参考。     

Costs of Arsenic Treatment for Potable Water in California and Comparison to U.S. Environmental Protection Agency Affordability Metrics1

Hilkert Colby, Elizabeth J., Thomas M. Young, Peter G. Green, and Jeannie L. Darby, 2010. Costs of Arsenic Treatment for Potable Water in California and Comparison to U.S. Environmental Protection Agency Affordability Metrics. Journal of the American Water Resources Association (JAWRA) 46(6):1238–1254. DOI: 10.1111/j.1752-1688.2010.00488.x Abstract: The United States (U.S.) federal standard for arsenic in potable water systems is only the second water quality standard in which the U.S. Environmental Protection Agency (USEPA) administrator used “discretionary authority to establish a less stringent standard” based on the results of cost-benefit analyses. Based on the findings that a “standard of 3 μg/l would be feasible but not justified,” the revised maximum contaminant level (MCL) lowered the allowable arsenic concentration from 50 to 10 μg/l in 2002. In 2009, approximately 145 systems in California were out of compliance. The objectives were to gather performance and cost data from arsenic treatment systems in California to compare with data from the USEPA demonstration sites as well as with the USEPA affordability metrics for drinking water. The median cost of compliance with the revised arsenic MCL for the 36 surveyed systems was $1.95/1,000 gallons (2008 dollars), which is 69% of the average cost of delivered tap water in the U.S. in 2008 ($2.81/1,000 gallons). Additionally, 22% of the surveyed systems in California paid more than the maximum predicted cost of compliance with the revised arsenic MCL ($5.05/1,000 gallons). The largest variation in cost was seen in the systems that treated <500 gpm. For the systems utilizing adsorption, systems obtained between 20 and 80% of the expected bed volumes prior to breakthrough, indicating the need for better prediction of performance.     

北京市大气污染物浓度空间分布与优化布点研究

基于地统计学方法对北京市2012年11—12月的大气污染物SO2、NO2、PM10和PM2.5浓度数据进行了空间分析。结果表明,4种污染物浓度数据均符合正态分布,满足地统计学分析的使用条件且均呈现中等强度的变异性。4种污染物半变异函数的块金效应值分别是29%、24%、7%、4%,表现出很强的空间相关性。4种污染物长轴变程分别是63、58、62、90 km,短轴变程分别是31、37、48、50 km,空间分布呈现出各向异性,变程范围与中尺度天气系统相当。研究大气污染物的空间分布特性对于整体把握区域环境空气质量和监测点位优化十分重要,以北京市区域空气质量中PM2.5监测站点设置为例,其监测站点在长轴方向上的间隔设置应取20~25 km,短轴方向上布点间隔应为8~12 km。     

PM2.5 characterization of primary and secondary organic aerosols in two urban-industrial areas in the East Mediterranean

Primary and secondary organic aerosols in PM_2.5 were investigated over a one-year campaign at Zouk Mikael and Fiaa, Lebanon. The n-alkanes concentrations were quite similar at both sites (26-29 ng/m³) and mainly explained by anthropogenic emissions rather than natural ones. The concentrations of total Polycyclic Aromatic Hydrocarbons (PAHs) were nearly three times higher at Zouk Mikael (2.56 ng/m³) compared to Fiaa (0.95 ng/m³), especially for indeno[1,2,3-c,d]pyrene linked to the presence of the power plant. A characteristic indeno[1,2,3-c,d]pyrene/(indeno[1,2,3-c,d]pyrene + benzo[g,h,i]perylene) ratio in the range 0.8-1.0 was determined for heavy fuel oil combustion from the power plant. Fatty acids and hopanes were also investigated and were assigned to cooking activities and vehicular emissions respectively. Phthalates were identified for the first time in Lebanon with high concentrations at Zouk and Fiaa (106.88 and 97.68 ng/m³ respectively). Moreover, the biogenic secondary aerosols revealed higher concentrations in summer. The total terpene concentration varied between 131 ng/m³ at Zouk Mikael in winter to 469 ng/m³ at Fiaa in summer. Additionnally, the concentrations of the dicarboxylic acids especially for adipic and phthalic acids were more influenced by anthropogenic sources.The analysis of molecular markers and diagnostic ratios indicated that the sites were strongly affected by anthropogenic sources such as waste open burning, diesel private generators, cooking activities, road transport, power plant, and industrial emissions. Moreover, results showed different pattern during winter and summer seasons. Whereas, higher concentrations of biogenic markers were clearly encountered during the summer period.