基于行人占据区域的泰森多边形人员密度统计方法

行人动力学的研究一直是火灾下人员疏散研究的重要内容。研究者通过大量观测和可控实验,获得行人的运动行为特征,揭示人员运动规律,但是仍然缺乏足够的定量校准的实验数据。在总结了前人对于实验中全局密度与局部密度统计方法的基础上,基于泰森多边形方法,结合人际关系距离与视野的观念,提出了一种行人占据多边形的速度密度统计方法。通过对平均密度平均速度的比较发现,方法得到的结果比传统统计方法得到的结果波动更小且更接近于连续变化、在密度低时比泰森多边形方法的结果更符合实际情况;而对于个人的速度密度散点图,结果也比泰森多边形方法的结果更为集中,尤其是除去了密度小而速度低的不合理数据点。     

臭氧氧化法连续处理焦化废水生化出水

采用连续通入废水和臭氧的方式,利用臭氧氧化法深度处理焦化废水生化出水(COD为151~183 mg/L、pH约为8),并通过添加羟基自由基抑制剂叔丁醇探究了臭氧氧化的机理。在不调节废水pH、臭氧投加量12.15mg/L、废水流量2 mL/min的最佳条件下,COD去除率达54.5%,出水COD达到GB 16171—2012《炼焦化学工业污染物排放标准》。稳定运行时,降解1 kg COD需投加臭氧741.1 mg。臭氧氧化过程中,臭氧自身氧化和羟基自由基氧化同时存在,且以羟基自由基氧化为主。反应过程符合准一级动力学模型,反应速率常数为0.01 min~(-1)。     

石墨烯与抑癌基因p53 DNA片段相互作用的分子模拟与光谱学验证

石墨烯(graphene,G)及其衍生物由于具有独特的理化性质,被广泛应用于能源、生物医学等领域,但尚缺乏其对生物体和环境潜在危害的研究。采用分子动力学模拟并结合光谱学方法(紫外可见吸收光谱、紫外变温实验及荧光光谱),分析了石墨烯与抑癌基因p53启动子区DNA片段(p53-DNA)间的相互作用,并探讨了相关作用机制。石墨烯的部分芳香环与p53-DNA碱基的芳香环之间存在π-π堆积作用,两者可以通过嵌插作用进行结合,同时还通过沟槽作用进一步结合。光谱实验进一步证实,在石墨烯作用下,p53-DNA的熔点(Tm)值升高,EB-DNA体系发生静态荧光淬灭,说明石墨烯能与p53-DNA结合;同时,p53-DNA与石墨烯结合后在260 nm处的吸光度升高,说明石墨烯对p53-DNA的双螺旋结构具有一定的破坏作用。上述研究结果从分子水平上分析了石墨烯与p53-DNA间的相互作用机制,有助于进一步阐明石墨烯的毒性作用机理。     

土地城市化背景下武汉市资源环境承载力仿真研究

运用Vensim软件,通过构建"土地城市化-资源环境承载力"系统动力学模型对不同情景下武汉市资源环境承载力的发展趋势进行仿真,为土地城市化背景下武汉市未来发展方向提供参考。结果显示,协调发展型是最适合武汉市的发展模式,而现状延续型、政绩驱动型和生态环保型情景下武汉市资源环境承载力到2020年均将面临超载压力。武汉市在适当加速推进土地城市化的同时应注重增加耕地面积、加强基础设施建设、降低资源消耗和污染排放,确保资源环境承载系统平稳运行。     

Untangling the proximate causes and underlying drivers of deforestation and forest degradation in Myanmar

Political transitions often trigger substantial environmental changes. In particular, deforestation can result from the complex interplay among the components of a system—actors, institutions, and existing policies—adapting to new opportunities. A dynamic conceptual map of system components is particularly useful for systems in which multiple actors, each with different worldviews and motivations, may be simultaneously trying to alter different facets of the system, unaware of the impacts on other components. In Myanmar, a global biodiversity hotspot with the largest forest area in mainland Southeast Asia, ongoing political and economic reforms are likely to change the dynamics of deforestation drivers. A fundamental conceptual map of these dynamics is therefore a prerequisite for interventions to reduce deforestation. We used a system‐dynamics approach and causal‐network analysis to determine the proximate causes and underlying drivers of forest loss and degradation in Myanmar from 1995 to 2016 and to articulate the linkages among them. Proximate causes included infrastructure development, timber extraction, and agricultural expansion. These were stimulated primarily by formal agricultural, logging, mining, and hydropower concessions and economic investment and social issues relating to civil war and land tenure. Reform of land laws, the link between natural resource extraction and civil war, and the allocation of agricultural concessions will influence the extent of future forest loss and degradation in Myanmar. The causal‐network analysis identified priority areas for policy interventions, for example, creating a public registry of land‐concession holders to deter corruption in concession allocation. We recommend application of this analytical approach to other countries, particularly those undergoing political transition, to inform policy interventions to reduce forest loss and degradation.     

高浓度PASC复合混凝剂的混凝动力学研究

以铝酸钠为碱化剂,合成了具有不同 Si/Al摩尔比的聚硅氯化铝复合混凝剂(PASC),采用透光率脉动检测技术并结合混凝效能和Zeta电位的测定结果,对PASC以及聚合氯化铝(PAC)、参比PACref在混凝过程中絮集物形成和增长的变化差异作了对比研究.结果表明,混凝过程中,Zeta电位、剩余浊度以及混凝指数密切相关.采用铝酸钠为碱化剂合成并引入硅酸钠的混凝剂,有利于提高凝聚速度和絮集物颗粒大小.在Si/Al摩尔比为0.10时处理效果达到最佳.     

A System Dynamics Model for the Environmental Management of the Sepetiba Bay Watershed, Brazil

In the recent past, the Sepetiba Bay watershed, located in the Rio de Janeiro State, Brazil has experienced rapid industrial development and population growth, as well as an increase in water pollution and environmental degradation. To analyze the complex interrelationships among the agents affecting the Sepetibza Bay environment, a system dynamics model was developed. The model builds on extensive studies conducted for the watershed, and simulates different hypotheses of economic growth and of demographic expansion. Thus, it can be used as a decision support tool for the identification of investment priorities and policy analyses under various scenarios. In order to provide a comprehensive approach to the environmental management of the Sepetiba Bay watershed, the model had to consider only the most relevant aspects of the behavior and the key interactions among agents operating in the watershed. In this article, the model’s structure is presented together with some of its main results.     

循环流动系统的压力调节及能量消耗问题

本项目对立式循环流动系统内气体压力、流量变化的调节控制方法,通风机的能量消耗等实际工程问题,进行了一系列的试验研究。其研究成果可以用于其他工程设计项目,对提高我国通风除尘系统的设计质量有一定的现实意义。     

纤维束滤床直接过滤动力学模型

应用单位床单元概念和圆柱池多孔介质模型,推导得到上向流纤维束滤床初始过滤系数表达式,其中收集效率由操作参数构成的无量纲数群关联得到,并据此探讨了悬浮颗粒的去除机理.假设过滤系数是滤床比表面积和空隙流速的函数,推得过滤系数的半经验公式,进而得到了过滤动力学模型.模型中的参数被赋予了明确的物理意义,且能反映操作条件对动力学行为的影响.在不同尺寸悬浮颗粒和不同表观滤速下进行了过滤实验.模型预测值与实验结果比较表明,二者具有一致性.     

Forest cover change and fragmentation using Landsat data in Maçka State Forest Enterprise in Turkey

In this study, Grey model (GM) and artificial neural network (ANN) were employed to predict suspended solids (SSeff) and chemical oxygen demand (CODeff) in the effluent from a wastewater treatment plant in industrial park of Taiwan. When constructing model or predicting, the influent quality or online monitoring parameters were adopted as the input variables. ANN was also adopted for comparison. The results indicated that the minimum MAPEs of 16.13 and 9.85% for SSeff and CODeff could be achieved using GMs when online monitoring parameters were taken as the input variables. Although a good fitness could be achieved using ANN, they required a large quantity of data. Contrarily, GM only required a small amount of data (at least four data) and the prediction results were even better than those of ANN. Therefore, GM could be applied successfully in predicting effluent when the information was not sufficient. The results also indicated that these simple online monitoring parameters could be applied on prediction of effluent quality well.