化工废水排放量灰色预测新方法

对偏离灰指数律的原始时序系统，累加生成不是削弱随机波动性影响折唯一途径ＧＭ（１，１）模型也不是预测模型的最佳选择。本文介绍了一种新的生成方式－－线性生成及一种新的预测模型－－ＧＩＭ（１）。某市化工行业废水排放量的预测实例表明，本方法比ＧＭ（１，１），有着更好的预测效果。     

预测某市化工废水排放量的GAM模型

常规ＧＭ（１，１）预测模型已在环境科学领域得到了广泛的应用，但该模型在原始序列偏离指数规律时预测精度较差。用灰色代数曲线型模型（ＧＡＭ模型）提高了某市化工废水排放量预测的精确度。     

GTPM（1）模型在二氧化硫排放量预测中的应用

建立了一种适用于二氧化硫排放量预测的灰色二次幂函数曲线新模型「简称ＧＴＰＭ（１）」。实例应用表明,该模型对已严重偏离光滑离散函数条件的环境系统有着良好的同态性,清度高于ＧＭ（１,１）及ＧＩＭ（１）模型,具有实用价值。     

山东省工业废水排放量GM（1,1）高阶残差预测模型

介绍了ＧＭ（１，１）高阶残差预测模型之建模方法。以山东省工业废水排放量为例，建立了ＧＭ（１，１）高阶残差预测模型。结果表明，ＧＭ（１，１）高阶残差模型经ＧＭ（１，１）模型更贴近实际。     

NLDGM(1,1~r,t)灰色模型与火电厂SO_2排放量预测

根据灰色系统理论的基本原理，探讨了非线性灰色直接模型即NLDGM（1，1r，t）在电力工业一氧化硫排放量预测中的应用。文中给出某大电厂二氧化硫排放量的不同预测方法相比。实例表明，GM（1，1）不宜直接用于二氧化硫排放量预测，而NLDGM（1，1r，t）具有较理想的预测效果。     

灰色摆动序列的GM（1,1）拟合建模法及其应用

建立了灰色摆动序列ＧＭ（１,１）动态指数变换拟合建模方法,对某地工业固体废物产生量的预测结果表明,该法合理有效,切实可行,并有良好的精度。     

大型增压流化率联合循环的发展

７０ＭＷ容量等成功投运为增压流化床联合循环向大型化方向发展奠定了坚实的基础，本文介绍了大型（３５０ＭＷ容量等级）增压流化联合循环技术发展情况，预测了大型增压流化床联合循环发电机组在燃煤发电商业市场的发展前景。     

增敏碘量法同时测定微量Mn(Ⅱ)、 Mn(Ⅶ)、 Cr(Ⅲ)、 Cr(Ⅵ)

介绍了用增敏碘量法同时测定微量的Ｍｎ（Ⅱ）、Ｍｎ（Ⅶ）、Ｃｒ（Ⅲ）和Ｃｒ（Ⅵ）。将样品中的Ｍｎ（Ⅶ）和Ｃｒ（Ⅵ）用Ｎａ２ＳＯ３预先还原,在ｐＨ为３．０的醋酸盐介质中对Ｍｎ（Ⅱ）和Ｃｒ（Ⅲ）用过量ＫＩＯ４氧化（当用Ｈ２Ｐ２Ｏ２－７掩蔽Ｃｒ（Ⅲ）时,只有Ｍｎ（Ⅱ）被氧化）,过剩的ＩＯ－４用钼酸盐掩蔽,加入ＫＩ后,以Ｎａ２Ｓ２Ｏ３滴定游离出的Ｉ２。此法对Ｍｎ的测定范围为２９～１４７０６μｇ／Ｌ,相对标准偏差为０．３１％～１．１８％;对Ｃｒ的测定范围为５９～１０２９４μｇ／Ｌ,相对标准偏差为０．３６％～１．１２％。此法与常规滴定法测定Ｍｎ和Ｃｒ相比,分别可增敏２０倍和１２倍     

评估有机氯化物不利影响的科学准则

评估有机氯化物不利影响的科学准则Ｃ＆ＥＮ，Ｍａｙ３１（１９９３）应美国氯学会和氯协调委员会的要求，加拿大咨询组织ＣａｎｔｏｘＩｎｃ，编写了“评估环境中有机氯化物潜在的不利影响的科学准则”，该准则经过专家组的评议。主要有４个科学准则：（１）物质的化学物...     

阳离子嫩黄染料与苯酚在活性炭上竞争吸附的研究

用阳离子嫩黄染料和苯酚作为分子量差异悬殊的两种机吸附质，研究它们在两种国产活性炭上的吸附性能。在双组分竞争吸附中，阳离子嫩黄染吸附占明显优势，而 酚的吸附量则比在单组分系统时要小。本文还用理想吸附溶液（ＩＡＳ）模型对双组分竞争吸附作了预测。     

Evaluating waste disposal systems

Waste disposal systems conventionally exhibit many problems, such as difficulties in finding final disposal sites for incinerator residues and the issue of how to recycle waste materials. Some new technologies have been developed to solve such problems, including ash melting and gasification melting. Furthermore, to improve the power generation efficiency of waste treatment facilities so that their energy is used more efficiently, combined stoker/gas turbine power generation (super waste power generation) technology has been developed. Through examination of two cases in this study, environmental impacts and costs were determined using lifecycle assessment (LCA) and lifecycle cost (LCC) methods in a model city. In case 1, a stoker furnace was compared to a combined stoker/gas turbine system. In case 2, a stoker furnace plus ash melting system was compared to a gasification melting system. The results demonstrate that the stoker furnace has a lower environmental impact than the combined stoker/gas turbine system in case 1, and that the stoker plus ash melting system costs less than the gasification melting system in case 2, but both systems had strong impacts on the environment.     

LCA to choose among alternative design solutions: The case study of a new Italian incineration line

At international level LCA is being increasingly used to objectively evaluate the performances of different Municipal Solid Waste (MSW) management solutions. One of the more important waste management options concerns MSW incineration. LCA is usually applied to existing incineration plants.In this study LCA methodology was applied to a new Italian incineration line, to facilitate the prediction, during the design phase, of its potential environmental impacts in terms of damage to human health, ecosystem quality and consumption of resources. The aim of the study was to analyse three different design alternatives: an incineration system with dry flue gas cleaning (without- and with-energy recovery) and one with wet flue gas cleaning. The last two technological solutions both incorporating facilities for energy recovery were compared. From the results of the study, the system with energy recovery and dry flue gas cleaning revealed lower environmental impacts in relation to the ecosystem quality.As LCA results are greatly affected by uncertainties of different types, the second part of the work provides for an uncertainty analysis aimed at detecting the extent output data from life cycle analysis are influenced by uncertainty of input data, and employs both qualitative (pedigree matrix) and quantitative methods (Monte Carlo analysis).     

电网环境保护管理信息系统的设计与实现

为了对输变电工程中的大量资料进行信息化动态管理,对电磁环境参数进行预测分析,为电网决策、管理、运行提供依据,建立电网环境保护信息管理系统。阐述系统的构建、实现及运用Matlab工具进行电磁环境参数预测模型的求解,通过系统集成完成信息管理和预测分析模型系统的开发,实现电网环境保护的决策分析。以可听噪声预测模型构建为例,在C#.NET平台上调用Matlab工具箱,实现了输电线路可听噪声的预测分析。     

Numerical simulation of landfill aeration using computational fluid dynamics

The present study is an application of Computational Fluid Dynamics (CFD) to the numerical simulation of landfill aeration systems. Specifically, the CFD algorithms provided by the commercial solver ANSYS Fluent 14.0, combined with an in-house source code developed to modify the main solver, were used. The unsaturated multiphase flow of air and liquid phases and the biochemical processes for aerobic biodegradation of the organic fraction of municipal solid waste were simulated taking into consideration their temporal and spatial evolution, as well as complex effects, such as oxygen mass transfer across phases, unsaturated flow effects (capillary suction and unsaturated hydraulic conductivity), temperature variations due to biochemical processes and environmental correction factors for the applied kinetics (Monod and 1st order kinetics). The developed model results were compared with literature experimental data. Also, pilot scale simulations and sensitivity analysis were implemented. Moreover, simulation results of a hypothetical single aeration well were shown, while its zone of influence was estimated using both the pressure and oxygen distribution. Finally, a case study was simulated for a hypothetical landfill aeration system. Both a static (steadily positive or negative relative pressure with time) and a hybrid (following a square wave pattern of positive and negative values of relative pressure with time) scenarios for the aeration wells were examined. The results showed that the present model is capable of simulating landfill aeration and the obtained results were in good agreement with corresponding previous experimental and numerical investigations.     

Volatilization and Biodegradation of VOCs in Membrane Bioreactors (MBR)

Volatilization and biodegradation are major competitive volatile organic compound (VOC) removal mechanisms in biological wastewater treatment process, which depend on compound specific properties and system design/operational parameters. In this study, a mathematical model was used to determine major removal pathways at various organic loading rates (OLR), solids residence time (SRT) and dissolved oxygen (DO) concentrations in a biological process for vinyl acetate. Model results showed that biological treatment process should be designed with long SRT, high OLR and low DO concentrations to maximize biodegradation and minimize volatilization of VOCs. Unless a VOC is toxic to microorganisms under the given conditions, low VOC emission rates are an inherent advantage of MBRs, which operate at higher OLR and longer SRT compared to conventional activated sludge process. A lab scale membrane bioreactor (MBR) was operated at varying OLR to investigate the relative volatilization and biodegradation rates for acetaldehyde, butyraldehyde and vinyl acetate. Synthetic wastewater containing three VOCs was introduced to the MBR. The DO concentration and SRT was maintained at 2.0 mg L^{− 1} and 100 days, respectively. The overall VOC removal rate was more than 99.7% for three VOCs at all the OLR. For vinyl acetate, the biodegradation rate increased from 93.87 to 99.40% and the volatilization removal rate decreased from 6.09 to 0.59% as OLR was increased from 1.1 to 2.0 kg COD m^{− 3} d^{− 1}. It was confirmed that a MBR can be a promising solution to reduce VOC emissions from wastewater.     

An inexact multi-objective dynamic model and its application in China for the management of municipal solid waste

With the development of science and technology, solid waste management has become a serious environmental problem for most communities all over the world. This paper presents a multi-objective optimization model for the management of municipal solid waste (MSW) via an uncertainty approach. In this model, the system cost of solid waste management and the environmental impact are considered as the main objectives, and some necessary constraints based on the characteristics of China are included; additionally, Pollution loss theory is applied to evaluate the environmental impact.This model is applied to the City of Fo Shan, China. Compared with the primary project of Fo Shan, which is provided by the government, the results of the optimization procedure show that the overall system cost could be reduced by $1–2.4/ton, i.e., $3.7 million/yr. The model presented in this paper was proven to be an effective response to the multi-objective solid waste management problem, and provides a new technique to optimize MSW management and operation. Why is the optimization result better? By analyzing the modelling with respect to function, constraints, and results, we conclude that the profit would be augmented due to the amount of the waste that would be treated by recycling technology, which would increase rapidly during the planning time; thus, the total system cost could be reduced accordingly.     

A historical perspective of Global Warming Potential from Municipal Solid Waste Management

The Municipal Solid Waste Management (MSWM) sector has developed considerably during the past century, paving the way for maximum resource (materials and energy) recovery and minimising environmental impacts such as global warming associated with it. The current study is assessing the historical development of MSWM in the municipality of Aalborg, Denmark throughout the period of 1970 to 2010, and its implications regarding Global Warming Potential (GWP₁₀₀), using the Life Cycle Assessment (LCA) approach. Historical data regarding MSW composition, and different treatment technologies such as incineration, recycling and composting has been used in order to perform the analysis. The LCA results show a continuous improvement in environmental performance of MSWM from 1970 to 2010 mainly due to the changes in treatment options, improved efficiency of various treatment technologies and increasing focus on recycling, resulting in a shift from net emission of 618 kg CO₂-eq. tonne^?1 to net saving of 670 kg CO₂-eq. tonne^?1 of MSWM.     

COASTMAP: An integrated monitoring and modeling system to support oil spill response

One of the most difficult tasks in oil spill response modeling is to provide accurate estimates of the currents and winds during the spill event. This is typically done in an ad-hoc, subjective manner combining very limited field observations with simplified hydrodynamic and meteorological models. As an alternative an integrated environmental monitoring and modeling system, called COASTMAP, is presented. COASTMAP allows the user to collect, manipulate, display, and archive real-time environmental data through an embedded geographic information system and environmental data management tools; to perform simulations with a suite of environmental models (e.g. hydrodynamics, meteorological) in order to predict dynamics in the operational area and to assimilate real-time data into the models to allow hindcasting, nowcasting and forecasting. COASTMAP, operational on a personal computer, is controlled by mouse/keyboard through a series of menus and uses color graphics to present model predictions (plots, graphs, animations) and the results of data analyses. The software is designed using a shell based architecture making application to any geographic location simple and straightforward.In the present paper, COASTMAP is linked with OILMAP to provide a fully operational, real-time system that allows prediction of circulation, winds and oil spill trajectory and fate for estuarine and coastal sea areas. System performance is illustrated by the simulation of the trajectory of oil tracking buoys during two experiments performed in the lower west passage of Narragansett Bay. Simulation results using several forecast procedures, with/without real-time data, are presented.