盐城经济技术开发区污水处理厂提标改造工程设计研究

介绍了盐城经济技术开发区污水厂提标改造工程技术路线及方案.针对污水厂进水中工业废水含量较多的特点,增设水解酸化工艺段,将现状CAST池改造为AAO生物反应池,新建二沉池及混凝沉淀设施,使出水水质稳定达到《城镇污水处理厂污染物排放标准》(GB 18918-2002)中的一级A排放标准.同时增设污泥深度脱水设施,采用化学调理+板框压滤工艺.实际运行表明,经改造后的污水处理厂对各项污染物均取得了较好的去除效果,脱水后污泥的含水率可稳定控制在60%以下.     

遥感技术在灰霾监测中的应用综述

介绍了灰霾遥感监测的基本原理,论述了基于图像变换的TC法、HOT法和基于反演气溶胶光学厚度的灰霾遥感监测技术,以及造成灰霾天气的秸秆燃烧遥感监测方法.指出卫星遥感技术可以提供大尺度、长时间序列的污染物时空分布特征和变化趋势,以及全球性的大气环境综合遥感数据,是灰霾监测与综合治理的重要途径.     

长江口疏浚土掩埋对两种贝类存活的影响

疏浚土处置产生的土丘状浮泥,会掩埋原有底质,底栖生物被掩埋后或死亡,或垂直向迁移重新获得生存机会,而使底栖生物群落得以重建.为评价疏浚土掩埋对底栖生物存活的潜在影响,采用长江口深水航道工程疏浚土模拟掩埋尖紫蛤(Sanguinolaria acuta)、文蛤(Meretrix meretrix),观测两种贝类对不同埋深的反应及其存活情况.结果表明,文蛤和尖紫蛤被掩埋后均表现出垂向迁移行为,文蛤比尖紫蛤表现出了更强的垂向迁移能力,当掩埋深度为8cm时,可100%迁移至疏浚土表层,获得存活机会,而尖紫蛤仅50%左右个体的进出水管伸出疏浚土表层;疏浚土掩埋深度与尖紫蛤死亡率之间有极其显著正相关关系(R2=0.967,P=0.007<0.01),并求得4d-LC50为6.9cm,95%置信区间5.2~8.6cm.试验所设置掩埋深度与文蛤死亡率之间没有表现出显著相关关系,难以通过统计方法获得文蛤的4d-LC50;借鉴毒理学中推定LOEC(最低有影响深度)的方法,推定文蛤的LOED为10cm.研究表明,疏浚土处置后的沉积厚度对底栖动物种群的存亡具有决定性作用,而底栖动物在被掩埋后表现出的垂向迁移能力大小也可影响自身种群及处置区整个底栖动物群落的最终重建几率,并且积极的管理策略对底栖群落重建意义重大.表4图1参22     

曝气深度对河道底泥特性及水质的影响

采用室内模拟实验方法对受污河道底泥和上覆水进行研究,对比分析静置状态X0和不同曝气深度条件下(分别为水体曝气泥水界面上方10 cm,底泥曝气下方5和15 cm处,依次记为X+10、X-5和X-15)河道底泥特性及水质的影响情况。结果表明:底泥曝气较水体曝气而言,能促进水体DO更快恢复;停止曝气,DO浓度也会维持在较高的状态,有利于有机物和氨氮的进一步去除。在相同曝气量下,底泥曝气比水体曝气能更好地去除底泥中污染物,并减少再次释放,且底泥曝气深度越深,处理效果越好,至实验结束时,X-15组上覆水中COD、NH4+-N、TN及TP浓度分别为16.25、3.03、13.39及0.09 mg/L,去除率分别为69.73%、78.36%、45.98%及84.21%;停止曝气后,经曝气处理的底泥对磷的吸附容量显著增加,并且不会再向上覆水中释放污染物,避免引起水体的二次污染。     

一种基于状态向量推理的SDG-HAZOP分析方法

HAZOP是分析系统可靠性的一种有效方法,在石油、化工工业中得到了广泛应用。但人工HAZOP分析存在费时、费力、成本高等缺点,而计算机辅助SDG-HAZOP分析的提出有效地改善了人工分析的弊端,然而传统的计算机辅助SDG-HAZOP是纯定性的分析与推理,分析的结果往往过于冗繁。本文介绍了一种改进的基于状态向量推理的计算机辅助SDG-HAZOP分析方法,该方法基于SDG定性模型,构造了一个计算机自动推理引擎,并引入了状态向量的概念,通过正向反向推理,快速高效地发掘出偏差产生的后果和原因。通过应用实践表明,与人工HAZOP分析法和现有SDG-HAZOP分析方法相比,该方法具有完备性好、评价结果系统性和条理性强等优点。     

极端冰雪条件下的顺层岩质边坡滑移稳定性分析

推导了典型岩石边坡在极端冰雪条件下的滑移稳定系数的表达式;通过计算分析,揭示了岩石边坡滑移稳定系数随裂隙内水深、坡高、坡角、滑面倾角等因素变化的规律及与冻深的关系,并绘制岩石边坡滑移稳定系数与边坡几何要素之间的关系图.研究表明,当考虑极端冰雪灾害影响时,岩石边坡滑移稳定系数发生较为明显的变化:随裂隙饱水程度、坡面角、主...     

不同水层光照强度对4种沉水植物生长的影响

选取金鱼藻(Ceratophyllum demersum)、轮叶黑藻(Hydrilla verticillata)、水盾草(Cabombacaroliniana)、苦草(Vallisneria gigantean)为试验材料,研究不同水层的光照强度对其存活率、株高、生物量等的影响,旨在找出这4种沉水植物在自然条件下的最...     

Land Cover Changes as a Result of Environmental Restrictions on Nitrate Leaching in Dairy Farming

Nitrate leaching forms an important environmental problem because it causes pollution of groundwater and surface water, and adds to already problematic eutrophication. This study analyses the impact of reductions in nitrate leaching on land cover decisions of dairy farms, of which the activities make an important contribution to nitrate leaching. As the level of nitrate leaching depends on groundwater depth as well as on the supply of nitrogen, spatial variation in groundwater levels will cause a spatial variation in land cover under restrictions on nitrate leaching. A non-linear partial optimisation model for the economic and ecological aspects of the problem were used to show how land cover and dairy farms' financial balances change when nitrate losses are reduced. The model is spatially explicit, and describes nitrate leakage and yields of maize and grass as a function of groundwater depth, including the effects of various grazing systems. The model analyses the decisions of a risk neutral agent who minimises costs under the following constraints: (i) production, feed requirements and mass balances for fodder; (ii) constraints for nitrate leaching. Economic costs are attributed to increased costs of fodder and processing of manure when nitrate restrictions are tightened. An important result of the study is the variation in compliance costs and land cover for maize and grass production brought about by spatial variation in groundwater depth. While the effects are negligible for some shallow groundwater classes, it is extremely difficult in other classes – if not impossible – to obtain the EU standard of maximum admissible losses of 34 kg N ha^–1 at low costs. The study shows an important reduction in land cover by maize.     

浅谈地表水透明度监测结果与现场光线的关系

在实际工作中我们发现现场光线影响塞氏盘透明度测定结果，本文对透明度与现场光线的关系进行了探讨，并提出了建议。     

Calibrating a Basin‐Scale Groundwater Model to Remotely Sensed Estimates of Groundwater Evapotranspiration

Remotely sensed vegetation indices correspond to canopy vigor and cover and have been successfully used to estimate groundwater evapotranspiration (ET_g) over large spatial and temporal scales. However, these data do not provide information on depth to groundwater (dtgw) necessary for groundwater models (GWM) to calculate ET_g. An iterative approach is provided that calibrates GWM to ET_g derived from Landsat estimates of the Enhanced Vegetation Index (EVI). The approach is applied to different vegetation groups in Mason Valley, Nevada over an 11‐year time span. An uncertainty analysis is done to estimate the resulting mean and 90% confidence intervals in ET_g to dtgw relationships to quantify errors associated with plant physiologic complexity, species variability, and parameter smoothing to the 100 m GWM‐grid, temporal variability in soil moisture and nonuniqueness in the solution. Additionally, a first‐order second moment analysis shows ET_g to dtgw relationships are almost exclusively sensitive to estimated land surface, or maximum, ET_g despite relatively large uncertainty in extinction depths and hydraulic conductivity. The EVI method of estimating ET_g appears to bias ET_g during years with exceptionally wet spring/summer conditions. Excluding these years improves model performance significantly but highlights the need to develop a methodology that accounts not only on quantity but timing of annual precipitation on phreatophyte greenness.