海水生物滤器氨氮沿程转化规律模型

生物滤器是海水循环水养殖系统中的核心水处理单元,其主要用于去除对养殖生物有害的氨氮、有机物等.本研究基于吸附原理和一级反应生物膜理论构建了氨氮在生物滤器中沿程转化规律的数学模型,并通过实验加以验证.实验所用生物滤器采用竹制空心生化球填料,装填高度为70 cm,在pH为7.1～7.6,DO为5～7 mg.L-1,气水比20∶1左右,有机负荷约为4g.(m3.h)-1,水力停留时间(HRT)为1 h条件下,生物滤器中氨氮的去除主要发生在填料高度0～10 cm处,10～70 cm处氨氮去除量很少.进水氨氮质量浓度的增大和水力停留时间的降低都会导致出水氨氮质量浓度增大.此外,模型对进水氨氮质量浓度较低时的沿程出水氨氮质量浓度具有很好的预测效果;当进水氨氮质量浓度较高时,预测值略低于实际结果.     

人工湿地净化海水养殖外排水影响因素与效果实验研究

以海水养殖外排水为处理对象,构建芦苇复合垂直流人工湿地模拟系统进行处理效果的影响因素(盐度,水力负荷,污染负荷)实验。植物选择芦苇,种植密度为48株/m2,基质填料选择细纱、蛭石、高炉矿渣、沸石和砾石。实验结果显示,随着盐度的升高,人工湿地对CODMn和NH4-N的去除率差异不显著(P>0.05),对PO4-P的去除率在逐渐降低,变化显著(P<0.05),但芦苇表现出较强的耐盐性,在盐度20时生长良好。随着水力负荷的增加,人工湿地对CODMn、NH4-N和PO4-P的去除率呈现出降低的趋势,变化显著(P<0.05);而当污染负荷增加时,去除率呈现出先增加后降低的趋势。综合考虑运行合理性及运行效果,得出合理工况为盐度20,水力负荷0.4 m3/(m2.d),污染负荷CODMn 10 mg/L,NH4-N 2 mg/L,PO4-P 0.5 mg/L。在此工况下,系统稳定运行2个月,显示人工湿地对海水养殖外排水中的污染物具有较好的去除效果。     

离心场环境下液压振动台试验设备的研制

本文主要介绍了离心机液压振动台系统的设计思想、构成和工作原理以及主要技术指标、特点和意义.     

利用人工湿地系统深度处理城市污水尾水

利用垂直复合流模拟人工湿地系统对城市污水厂尾水进行深度处理实验研究,植物床选用美人蕉、菖蒲、茭草、芋头和象草混合栽种,采用石英砂为主体填料。实验研究表明:人工湿地系统在停留时间为24h,水力负荷为0.4m3(m2·d)的运行条件处理效果较佳,在此条件下连续稳定运行10个月,处理后的尾水主要指标达到(GBT189212002)标准。     

土柱淋洗法修复铬污染土壤的水力梯度优化试验

针对重金属污染土壤的修复,淋洗法是一种比较成熟的方式,但目前研究主要聚焦于淋洗剂的选择,而关于水力停留时间对淋洗效果影响的研究相对较少.水力梯度是影响水力停留时间的重要因素,优化水力梯度能够缩短修复周期,降低淋洗成本,有效提高淋洗效率,为现场淋洗修复工程应用提供参考.本文针对人工制备的不同质地的铬污染土壤进行了土柱淋洗...     

回灌运行参数对新鲜垃圾渗滤液的影响研究

采用模拟试验装置考察回灌频率与回灌水力负荷对新鲜垃圾柱渗滤液的影响,试验结果表明:高频率回灌将导致新鲜垃圾柱渗滤液初期酸化阶段的低pH值和甲烷化阶段的高pH值。高水力负荷将导致新鲜垃圾柱渗滤液pH值下降。因此在新鲜垃圾填埋单元自身回灌初期应采取低频率小水力负荷。     

基于震后低压变化的供水管网功能可靠度分析

供水管网的抗震功能是指供水管网在地震作用下能够满足震后城市特定用水需要(需水量和水压)的能力。地震发生后,供水管网一般处于低压供水状态,使得管网中部分用户的水压和水量不能得到全部满足,导致管网部分节点的实际配水量小于需水量。为此,在传统的管网水力分析基础上考虑节点流量随节点水压的动态变化,通过求解非线性水力方程组,得到管网节点实际流量和水压;同时,借鉴结构可靠度分析方法,引入供水管网系统随机水力模型,给出了震后供水管网功能可靠度分析的一次二阶矩方法。以一实际管网为例,演示了震后低压供水时管网功能可靠度分析的应用方法。     

The effect of industry activities on public support for ‘fracking’

Research suggests that previous, current, and prospective extractive industry activities influence perceptions of new development. Studies that have drawn this conclusion, however, have usually focused on specific projects in specific communities. Here, these factors are examined on an aggregate, national scale. Combining geospatial data on extractive industry activities and survey data from a nationally representative sample (N = 1061), the influence of extractive industry activities on support for fracking is studied. While limited evidence is found for the impact of proximity to oil and gas wells or production on support for fracking, employment levels in the natural resources and mining sector in the respondent’s county and residence in an area experiencing active oil and gas development significantly increase support for fracking. The results highlight the role of spatial and community factors in shaping support for energy development.     

Monte Carlo analysis of field water flow comparing uni- and bimodal effective hydraulic parameters for structured soil

Soil structure critically affects the hydrological behaviour of soils. In this paper, we examined the impact of areal heterogeneity of hydraulic properties of a structured soil on soil ensemble behaviour for various soil water flow processes with different top boundary conditions (redistribution and drainage plus evaporation and infiltration). Using a numerical solution of the Richards' equation in a stochastic framework, the ensemble characteristics and flow dynamics were studied for drying and wetting processes observed during a time interval of ten days when a series of relatively intense rainfall events occurred. The effects of using unimodal and bimodal interpretative models of hydraulic properties on the ensemble hydrological behaviour of the soil were illustrated by comparing predictions to mean water contents measured over time in several sites at field scale. Although the differences between unimodal and bimodal fitting are not significant in terms of goodness of fit, the differences in process predictions are considerable with the bimodal soil simulating water content measurements much better than unimodal soil. We also investigated the relative contribution of the soil variability of each parameter on the variance of the water contents obtained as the main output of the stochastic simulations. The variability of the structural parameter, weighting the two pore space fractions in the bimodal interpretative model, has the largest contribution to water content variance. The contribution of each parameter depends only partly on the coefficient of variation, much more on the sensitivity of the model to the parameters and on the flow process being observed. We observed that the contribution of the retention parameters to uncertainty increases during drainage processes; the opposite occurs with the hydraulic conductivity parameters.     

Adaptive Management of Stream Channel Maintenance at Bridge Crossings in the Northern Tier Region,Pennsylvania1

Abstract: An adaptive management framework is applied to the problem of identifying mitigation measures for sediment deposition near bridge crossings in small streams in the Northern Tier region of northern Pennsylvania. The presence of the rigid bridge infrastructure introduces a challenge for applying adaptive management practices, because the integrity of the bridge structure itself has to be maintained regardless of the mitigation practices used in the stream channel near the bridge. In an effort to overcome the unacceptable risk that field‐scale adaptive management experiments present to rigid bridge infrastructure, an adaptive management approach for laboratory‐scale experimentation of mitigation methods at bridge crossings in the Northern Tier region is presented as a way to decrease the level of uncertainty about channel response to mitigation measures and increase the rate of learning about the effectiveness of these measures. Four cycles of adaptive management experiments are discussed to demonstrate that this approach results in fast and efficient learning about channel response to mitigation methods for the given conditions. The value of monitoring and of assessment of monitored data in the overall efficiency of the adaptive management approach is highlighted. Assessment of what was learned in the adaptive management experiment cycles presented here leads to new directions to continually improve management policies and practices in stream channels at bridge crossings in the Northern Tier region. The adaptive management process, rather than continuing with a normally risk‐averse management approach, results in opportunities for learning new information about a system’s response.