Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.     

A New Approach to Plant Diversity Assessment Combining HPLC Data, Simplex Mixture Design and Discriminant Analysis

The quantitative assessment of plant diversity and its monitoring with time represent a key environmental issue for management and conservation of natural resources. Assessment of plant diversity could be based on chemical analyses of secondary metabolites (e.g. flavonoids, terpenoids), because of the substantial quantitative and qualitative between-individual variability in such compounds. At a geographical scale, the plant populations become widely dispersed, and their monitoring from numerous routine individual analyses could become restricting. To overcome such constraint, this study develops a multivariate calibration model giving the relative frequency of a particular taxon from a simple high-performance liquid chromatography (HPLC) analysis of a plant mixture. The model was built from a complete set of mixtures combining different taxons, according to an experimental design (Scheffé’s matrix). For each mixture, a reference HPLC pattern was simulated by averaging the individual HPLC profiles of the constitutive taxons. The calibration models, based on Bayesian discriminant analysis (BDA), gave statistical relationships between the contributions of each taxon in mixtures and reference HPLC patterns of these mixtures. Finally, these models were validated on new mixtures by using outside plants. This new biodiversity survey approach is illustrated on four chemical taxons (four chemotypes) of Astragalus caprinus (Fabaceae). The more differentiated the taxon, the better predicted its contributions (in mixtures) were by BDA calibration model. This new approach could be very useful for a global routine survey of plant diversity.     

上海市降尘监测中存在的问题

降尘监测是探索大气可自然沉降颗粒物对环境影响的不可缺少的手段之一.降尘监测因其采样设备简便、操作简单易行等优点被广泛运用,但是监测周期长、环节多等因素都会影响降尘监测的准确性.通过对上海市降尘数据分析发现,上海市降尘监测中存在降尘数据波动大、受周边环境影响大、人为破坏多等问题,并就这些问题提出了若干建议和解决办法.     

区域空气自动监测数据审核方法与制度的探索

区域空气自动监测网络地理分布范围大、系统仪器设备众多、监测数据以海量计,如何对数据进行审核是一个值得关注的问题.以粤港珠江三角洲区域空气监测网络的实践为例,探讨了区域空气自动监测的数据审核方法与制度.     

环境空气中VOC_S在线监测法与SUMMA罐采样气相色谱-质谱法比对研究

定性比较了环境空气VOCs在线监测法和SUMMA罐采样GC-MS法的基本原理、检测化合物种类和适用范围,并对标样实验、日均浓度、小时浓度从统计学角度进行了定量比对.研究表明,VOCs在线监测法监测结果与实验室方法有较好可比性,可用于相关领域VOCs的连续监控.     

加强环境监测管理的几点思考

分析了环境监测在环境管理活动各个阶段所发挥的重要作用,以及目前环境监测管理中存在的主要问题,提出了加强监测管理的建议,旨在建设先进的环境监测预警体系,开创环境质量监测工作新局面。     

上海市环境空气质量监测体系规划设计

简述了上海市环境空气质量监测的历史和现状,指出了环境空气质量监测发展需求,构建了上海市空气质量监测系统规划框架;提出应构建上海市环境综合信息和公共数据平台,建设发展地基遥感探空、空基和天基遥感反演技术,建立长三角区域大气复合污染监测体系。     

加强预警监测体系建设 高效应对突发生态环境问题

简述了区域突发生态环境问题的现状与特点以及环境监测应对突发生态环境问题的现状,指出了环境监测应对突发生态环境污染存在的问题。提出,应加快预警监测技术体系建设,丰富预警监测技术手段,重视生物生态监测在预警监测中的作用,提高环境质量综合评价水平,发挥环境信息系统在预警监测中的作用,加强预警监测技术人才培养。     

无线传感器网络在环境监测中的应用

介绍了一种基于无线传感器网络的环境监测系统组成及架构,讨论了系统网络节点、网关的硬件设计,并对基于TinyOS的应用程序组件结构和节点工作流程做了说明。     

水质生物毒性在线监测技术研究进展

从生物分子、细胞、个体、种群和群落水平,系统介绍了国内外研发的水质毒性在线监测技术,归纳分析了各种技术的特点及应用,并提出了其发展前景与趋势。