生物滤池和常规工艺对某地表水中不同分子量有机物的去除

采用生物滤池和常规处理对受污染的某地表水进行试验研究 ,用膜过滤法对其出水进行了分子量分析 ,考察了 2个处理单元对不同分子量区间有机物的去除效果。结果表明 :原水中分子量小于 1 0 0 0的有机物占总 DOC的 78.2 9% ;生物滤池对分子量小于50 0、50 0～ 1 0 0 0和 >60 0 0 0的有机物去除率分别为 54.9%、36.1 %和 2 0 .7% ;常规处理对以上分子量区间有机物的去除率分别为1 5.3%、- 2 0 %和 48.75%。     

利用印染厂碱减量废水脱硫试验及其应用研究

介绍了化纤印染厂坯布前处理工序产生的碱减量废水作锅炉烟气SO2脱硫剂的试验研究结果，分析了碱减量废水脱硫反应过程及其机理，同时设计了一套经济适用的新型的文丘里旋流湿式脱硫除尘器。工业性试验运行结果表明，利用碱减量废水脱硫以废治废，经济效益和环境效益显著。     

模糊数学法在环境质量评价中的应用 --以天津滨海新区为例

模糊评价能有效的解决评价标准边界模糊和监测误差对评价结果的影响,具有一定的科学性、合理性.运用模糊数学法对天津滨海新区环境质量各因素进行定级评价,将各因素评价结果采用公式计数法进行二级赋权,较为客观评价了总体环境质量级别,为综合治理提供科学依据.     

以人为因素为中心的航空安全多级模糊综合评价

在航空安全中,根据SHEL模型,以人为因素为中心,列出影响航空安全的一级和二级指标进行多级模糊综合评价,得出各指标对航空安全的影响权重,从而采取相应措施,即加强组织内的横向纵向沟通交流,加大机务方面的培训力度,严格按照标准操作程序,形成公正合理、积极向上的企业文化,以提高航空安全.     

在役化工装置安全评价模式的研究

根据在役装置安全评价的两类目的,分析现有在役化工装置安全评价模式中存在的不足;提出在役化工装置安全评价的一个新思路和新模式;给出了基于新模式的安全评价程序,并对该评价程序各个步骤及采用的评价方法组合进行了较为详细的讨论,其关键是建立评价指标体系。该评价模式既能查找出装置中存在的具体安全隐患,也能给出装置总的安全评价结论。同时指出,安全评价指标体系的建立和完善应成为安全管理的一项标准化、基础性工作。该评价模式的思路不仅适用于在役化工装置的安全评价,也适用于其他系统安全现状评价,是对进一步完善当前安全现状评价工作的一个有益尝试。     

基于神经网络和遗传算法的城市火灾风险评价模型

以消防安全工程学与系统安全工程理论为基础,结合我国城市发展特征及消防安全管理状况,建立了城市区域火灾风险评价指标体系;针对神经网络易陷入局部极小而引起评价指标权值分布不合理的缺陷,提出了基于神经网络和遗传算法的城市火灾风险评价模型,该模型以火灾发生的可能性以及灾后的严重程度为输入单元,火灾风险等级为输出单元,采用误差反算法训练BP网络,最终得出火灾风险等级范围,有效地解决了城市火灾的动态性和非线性特征;研究实例证明了该模型的有效性,可为城市的消防安全管理提供确实可行的参考依据。     

TraK装置测定废水中的BOD_5

在对废水中的BOD5进行常规分析时,采用化学稀释法操作繁琐,对稀释倍数估计易发生错误。而利用TraK装置测试样品时,无须进行稀释和化学分析。用该装置对标准样品BOD5的测定结果表明:准确度相对误差为-3.3%～4.3%,精密度的相对误差为-3.5%～5.6%。该仪器测试性能可靠,数据准确度、精密度合格。与化学法对照分析表明,相对误差都在容许范围内,即在可接受范围内。     

基于模糊模式识别的模糊综合评价在高层建筑火灾危险评价中的应用

针对高层建筑火灾危险的特点,建立了高层建筑火灾危险评价的指标体系,并应用层次分析法确定了其权重。根据高层建筑火灾危险评价系统具有多因素、多层次的特点,采用模糊综合评价方法;针对模糊综合评价的不足之处,提出把权广义距离之和最小模糊模式识别运用到模糊综合评价当中,建立了基于模糊模式识别的模糊综合评价模型;该评价模型避免了单因素矩阵的确定和模糊算子的选择问题,用安全状态特征值来表征最终的评价结果,能使评价结果更加准确,可操作性强。通过对陕西某高层建筑火灾危险评价实例证明,该模型具有较好的应用价值,为日常的安全管理和性能化防火设计提供了有用依据。     

Effects of organic matter on Leymus chinensis germination,growth, and urease activity and available nitrogen in coastal saline soil

ABSTRACT

The present study was carried out to investigate the effect of three organic matters (stalk powder, microbial fertilizer, and manure) on Leymus chinensis germination, growth, and urease activity and available nitrogen (N) in coastal saline soil. The study was conducted in a completely randomized design with eight treatments: J₀V₀Y₀, J₁V₀Y₀, J₀V₁Y₀, J₀V₀Y₁, J₁V₁Y₀, J₁V₀Y₁, J₀V₁Y₁, J₁V₁Y₁. The notations were based on the quantities of each agent added to 1 kg of coastal saline soil: J₀ – no straw powder, J₁ – 0.2 kg straw powder, Y₀ – no manure, Y₁ – 0.3 kg manure, V₀ – no microbial fertilizer, V₁ – 0.2 L microbial fertilizer, each in quantic repeat. L. chinensis was sown as 50 seeds per pot. Results indicated that addition of organic agents exerted a significantly enhanced germination, increase in fresh weight and elevated soil urease activity. Soil available N levels were significantly positively correlated with soil urease activity and fresh weight, but not with germination rate. It is noteworthy that the halophyte L. chinensis showed improved characteristics when grown in coastal saline soil with addition of organic amendments.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.