上海市餐厨垃圾处理管理思路剖析

根据<上海市餐厨垃圾处理管理办法>,分析了加强餐厨垃圾处理管理的思路,包括对物流、资金流和信息流的控制,从而实现餐厨垃圾产生环节、收集运输环节、处置环节的有效监管,维护公共卫生安全.     

A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1

Abstract: Water resources planning and management efficacy is subject to capturing inherent uncertainties stemming from climatic and hydrological inputs and models. Streamflow forecasts, critical in reservoir operation and water allocation decision making, fundamentally contain uncertainties arising from assumed initial conditions, model structure, and modeled processes. Accounting for these propagating uncertainties remains a formidable challenge. Recent enhancements in climate forecasting skill and hydrological modeling serve as an impetus for further pursuing models and model combinations capable of delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The framework presented here proposes integration and offline coupling of global climate models (GCMs), multiple regional climate models, and numerous water balance models to improve streamflow forecasting through generation of ensemble forecasts. For demonstration purposes, the framework is imposed on the Jaguaribe basin in northeastern Brazil for a hindcast of 1974‐1996 monthly streamflow. The ECHAM 4.5 and the NCEP/MRF9 GCMs and regional models, including dynamical and statistical models, are integrated with the ABCD and Soil Moisture Accounting Procedure water balance models. Precipitation hindcasts from the GCMs are downscaled via the regional models and fed into the water balance models, producing streamflow hindcasts. Multi‐model ensemble combination techniques include pooling, linear regression weighting, and a kernel density estimator to evaluate streamflow hindcasts; the latter technique exhibits superior skill compared with any single coupled model ensemble hindcast.     

Evaluating water quality investments using cost utility analysis

This study borrows concepts from healthcare economics and uses cost utility analysis (CUA) to select an optimum portfolio of water quality enhancement projects in Perth, Western Australia. In CUA, costs are handled via standard discounted cash flow analysis, but the benefits, being intangible, are measured with a utility score. Our novel methodology combines CUA with a binary combinatorial optimisation solver, known as a 'knapsack algorithm', to identify the optimum portfolio of projects. We show how water quality projects can be selected to maximise an aggregate utility score while not exceeding a budget constraint. Our CUA model applies compromise programming (CP) to measure utility over multiple attributes in different units. CUA is shown to provide a transparent and analytically robust method to maximise benefits from water quality remediation investments under a constrained budget.     

Exploration of relationships between phytoplankton biomass and related environmental variables using multivariate statistic analysis in a eutrophic shallow lake： A S-year study

Understanding the process of the changing phytoplankton patterns can be particularly useful in water quality improvement and management decisions. However, it is generally not easy to illustrate the interactions between phytoplankton biomass and related environmental variables given their high spatial and temporal heterogeneity. To elucidate relationships between them, in a eutrophic shallow lake, Taihu Lake, relative long-term data set of biotic and abiotic parameters of water quality in the lake were conducted using multivariate statistical analysis within seasonal periodicity. The results indicate that water temperature and total phosphorus （TP） played governing roles in phytoplankton dynamics in most seasons （i.e. temperature in winter, spring and summer; TP in spring, summer and autumn）; COD （chemical oxygen demand） and BOD （biological oxygen demand） presented significant positive relationships with phytoplankton biomass in spring, summer and autumn. However, a complex interplay was found between phytoplankton biomass and nitrogen considering significant positive relationships occurring between them in spring and autumn, and conversely negative ones in summer. As the predatory factor, zooplankton presented significant grazing-pressure on phytoplankton biomass during summer in view of negative relationship between them in the season. Significant feedback effects of phytoplankton development were identified in summer and autumn in view that significant relationships were obser,qed between phytoplankton biomass and pH, Trans （transparency of water） and DO. The results indicate that interactions between phyto：plankton biomass and related environmental variables are highly sensitive to seasonal periodicity, which improves understanding of different roles of biotic and abiotic variables upon phytoplankton variability, and hence, advances management methods for eutrophic lakes.     

高职《旅游学概论》课程教学改革研究

基于对高职《旅游学概论》在教学中存在的诸多问题进行的分析,结合高职旅游专业学生的特点,对教学内容、教学方法、考核方式等几方面的改革和创新进行了阐述。     

城市土地资源可持续利用评价指标体系构建

土地资源可持续发展的核心内容是如何将一个概念转换成可操作的管理模式，即建立一套切实可行的指标体系。目前，我国关于土地可持续发展的指标体系评价处于探索阶段，还没有形成一套较成熟的评价方法。基于对于我国土地可持续发展的指标体系研究，构建了一套有关城市土地可持续利用的评价指标体系。     

国外环保投资预测方法研究综述

国外在环保投资方面有着丰富的经验,环保投资预测模型或者方法对中国有着良好的借鉴价值。首先介绍了不同国家和国际组织—中国、美国、英国、日本、德国、欧盟的环保投资的特征与内涵,其次详细分析了国外环保投资的三种预测方法,主要有OECD的FEASIBLE模型、投入产出法、均匀污染法,并且从预测内容、预测范围和预测时间、预测精度、数据要求等方面对不同方法的优缺点进行了对比分析,最后为中国环保投资预测研究提出了一些建议。     

持久性有机污染物的主要特征和研究进展

概述了持久性有机污染物(POPs)在环境中的主要存在类型、生态行为特征、污染效应和对环境生物体的健康危害特性及我国在该领域的主要研究进展.重点介绍了二NFDA7英类化合物的生态毒性表示法、主要处置技术与相关的检测方法等研究进展.我国POPs相关的基础研究相对滞后,要履行好POPs公约,还面临诸多需要解决的现实问题.当前开展适合我国国情的POPs物质的环境调查监测、环境安全与健康毒理学研究并建立相关的环境控制基准和评估体系十分必要.      

Aqualab水质自动监测系统的维护与校准

介绍Aqualab水质自动监测系统的维护过程和校准步骤,通过正确的维护与校准,可以保证仪器的正常运转,保证监测数据的公正性和可靠性。