基于改进PSR模型的济南市生态安全评价研究

阐述了生态安全与生态健康、生态服务功能、生态风险等概念之间的逻辑联系，指出生态安全是其中的核心内容。考察一个城市的生态安全问题可从纵横向进行分析，尝试从纵向来讨论一个城市的生态安全问题。以济南市为例，采用改进的PSR模型构建济南市生态安全评价指标体系，以及采用层次分析法、熵权法相结合的复合数学模型确定指标权重，计算出2000—2005年的济南市生态安全评价综合指数。结果显示，2000年以来济南市生态安全评价综合指数呈稳定上升的状态，但上升的加速度很小。预测分析了济南市短期生态安全状况，提出了实现济南市生态系统安全的建议。     

运用活性污泥一号模型对缺氧——好氧生物废水处理工艺的模拟

随着污水生物处理技术的进步,很多相关的数学模型被开发出来用以描述污水生物处理工艺的机理,并指导其设计和运行管理.最为著名和应用广泛的当属国际水质协会(IAWQ)推出的活性污泥数学模型系列(Activated Sludge Model 1～3),即ASM模型.通过以反应器动力学为基础,使用活性污泥一号模型(ASM1)对缺氧-好氧生物废水处理工艺建立数学模型并且加以模拟的结果,得出了在不同的工况参数和反应条件(分别是污泥龄,缺氧池与好氧池的体积比,回流和内回流)下各级反应器中污染物质(主要是可溶性有机污染物,氨氮和硝态氮)浓度的变化规律,可以为实际工艺的设计与运行提供参考和依据.     

模糊综合评判在达州市环境空气质量评价中的应用

运用模糊综合评判的方法,选取二氧化硫、二氧化氮和可吸入颗粒物作为评价因子,参照我国环境空气质量标准,通过建立各污染物的隶属函数和权重集,计算出各污染物的隶属度和权重分配系数,进而对达州市空气质量进行模糊综合评判。并将模糊综合评判法与空气污染指数分析所得结果进行比较。     

基于模糊数学的矿业城市地表水污染风险评价

根据模糊数学方法,建立了水污染风险模糊综合评价数学模型,以煤炭资源型城市阜新为研究对象,选取辽河流域阜新段1996～2005年枯水期和丰水期水质状况平均值进行水污染风险评价。旨在定量分析评价阜新地区地表水环境质量现状和存在的问题。结果表明：辽河阜新段水质在1996～2005年间波动较大,呈水质日益恶化的状态。水体主要污染物为有机物、氨氮和溶解性铁,总体来说各污染物变化规律各不相同,总磷、BOD5、溶解性铁呈递增趋势,其他污染物质都呈波动性变化。     

两种化感物质联合抑藻的模型建立及数学最优化

在化感物质焦性没食子酸和亚麻酸单独抑藻的基础上,将两种化感物质按不同初始浓度组合进行联合抑藻的实验.根据实验过程中藻密度的变化趋势及特征,采用微元分析法,通过相应的偏微分方程,建立了化感物质复合抑藻时的数学模型.结果表明,该模型能够有效地分析和预测焦性没食子酸与亚麻酸在一定浓度范围内联合抑藻时藻密度随时间的变化规律.根据该模型还可以预测不同时间节点上,化感物质复合抑藻的半抑制浓度(EC50)、最小有效浓度(MIC),以及联合抑藻的最佳浓度组合和在成本控制下的联合抑藻最佳浓度组合等.该研究对指导制备高效、经济的复合生物抑藻剂及其应用均具有一定的理论意义和实用价值.     

东平湖及上游河段水质分析预测

运用水质数学模型,对东平湖及上游河段各控制断面的水质进行了预测和验证,说明了该预测方案的科学性和可行性。并分析了预测中误差存在的原因,提出了改进措施。     

On modelling the global copper mining rates,market supply,copper price and the end of copper reserves

The world supply and turnover of copper was modelled using simple empirical estimates and a COPPER systems dynamics model developed for this study. The model combines mining, trade markets, price mechanisms, population dynamics, use in society and waste as well as recycling, into a whole world system. The degree of sustainability and resource time horizon was estimated using four different methods including (1) burn-off rates, (2) peak discovery early warning, (3) Hubbert's production model, and (4) COPPER, a system dynamics model. The ultimately recoverable reserves (URR) have been estimated using different sources that converge around 2800 million tonne, where about 800 million tonne have already been mined, and 2000 million tonne remain. The different methods independently suggest peak copper mine production in the near future. The model was run for a longer period to cover all systems dynamics and delays. The peak production estimates are in a narrow window in time, from 2031 to 2042, with the best model estimate in 2034, or 21 years from the date of writing. In a longer perspective, taking into account price and recycling, the supply of copper to society is estimated to run out sometime after 2400. The outputs from all models put focus on the importance of copper recycling so that society can become more sustainable with respect to copper supply.     

喷射诱导气浮用于废水脱油的动力学研究

喷射诱导气浮应用于污水脱油前景广阔。建立了数学模型，进行了单级间歇模拟实验，测定了脱油动力学常数及极限脱油浓度。验证了脱油动力学方程，利用实验结果，得到了用以计算多模型中参数的关联式。所提出的数学模型为建立设计计算和药剂评价方法提供了依据。     

Smart meters for enhanced water supply network modelling and infrastructure planning

To design water distribution network infrastructure, water utilities formulate daily demand profiles and peaking factors. However, traditional methods of developing such profiles and peaking factors, necessary to carry out water distribution network modelling, are often founded on a number of assumptions on how top-down bulk water consumption is attributed to customer connections and outdated demand information that does not reflect present consumption trends; meaning infrastructure is often unnecessarily overdesigned. The recent advent of high resolution smart water meters allows for a new novel methodology for using the continuous ‘big data’ generated by these meter fleets to create evidence-based water demand curves suitable for use in network models. To demonstrate the application of the developed method, high resolution water consumption data from households fitted with smart water meters were collected from the South East Queensland and Hervey Bay regions in Australia. Average day (AD), peak day (PD) and mean day maximum month (MDMM) demand curves, often used in water supply network modelling, were developed from the herein created methodology using both individual end-use level and hourly demand patterns from the smart meters. The resulting modelled water demand patterns for AD, PD and MDMM had morning and evening peaks occurring earlier and lower main peaks (AD: 12%; PD: 20%; MDMM: 33%) than the currently used demand profiles of the regions’ water utility. The paper concludes with a discussion on the implications of widespread smart water metering systems for enhanced water distribution infrastructure planning and management as well as the benefits to customers.