Effects of cadium, zinc and lead on soil enzyme activities

Heavy metal （HM） is a major hazard to the soil-plant system. This study investigated the combined effects of cadium （Cd）, zinc （Zn） and lead （Pb） on activities of four enzymes in soil, including calatase, urease, invertase and alkalin phosphatase. HM content in tops of canola and four enzymes activities in soil were analyzed at two months after the metal additions to the soil. Pb was not significantly inhibitory than the other heavy metals for the four enzyme activities and was shown to have a protective role on calatase activity in the combined presence of Cd, Zn and Pb; whereas Cd significantly inhibited the four enzyme activities, and Zn only inhibited urease and calatase activities. The inhibiting effect of Cd and Zn on urease and calatase activities can be intensified significantly by the additions of Zn and Cd. There was a negative synergistic inhibitory effect of Cd and Zn on the two enzymes in the presence of Cd, Zn and Pb. The urease activity was inhibited more by the HM combinations than by the metals alone and reduced approximately 20%--40% of urease activity. The intertase and alkaline phosphatase activities significantly decreased only with the increase of Cd concentration in the soil. It was shown that urease was much more sensitive to HM than the other enzymes. There was a obvious negative correlation between the ionic impulsion of HM in soil, the ionic impulsion of HM in canola plants tops and urease activity. It is concluded that the soil urease activity may be a sensitive tool for assessing additive toxic combination effect on soil biochemical parameters.     

最优环境工程方案遴选模型的建立与应用

根据层次分析法的原理,建立了遴选最优环境工程方案的层次结构模型。模型兼顾了效益与投资,不仅简化了专家或决策者的判断难度,而且判断结果直观,各方案的优劣对比清晰。给合某啤酒废水治理工程项目,介绍了层次分析模型应用于工程方案遴选中的计算过程。结果表明,应用此模型对环境工程方案进行优选比较科学、简便。     

稀释倍数法测定污水色度的方法

研究选择了有代表性的6种色调的污水样品为研究对象,系统比较了不同色调、不同人员、不同稀释方法对测定结果的影响。选用红、橙、黄、绿、蓝、紫6种不同色调的样品进行测定,绿色、蓝色和黄色的测定结果分散在2个倍数之间,其中绿色的集中度高达84%。红色、橙色、紫色分散在3个倍数之间,紫色的集中度高达100%。对比自然倍数稀释法、偶数倍稀释法和2n倍稀释法,这3种方法同时测定红色调的样品,其测定结果的区间是相同的,集中区域内的人员分别占总人数的71%、83%和94%。结果表明:用1名实验人员使用自然倍数稀释法对样品进行单次分析作为色度测定的方法是有效的。     

郑州市PM2.5浓度时空分布特征及预测模型研究

利用统计学原理和GIS技术,对郑州市2013年8月17—12月31日期间PM2.5浓度时空分布特征进行分析,同时结合气象资料与前一日污染数据,建立人工神经网络反向传播算法模型(BP-ANN)和多元线性回归模型用于该市细颗粒物污染的短期预测。结果表明,郑州市PM2.5浓度日变化呈单峰模式,随逆温现象的发生和交通的密集于上午11:00达到峰值,午后逐步下降。在工作日、周末与国庆节的对比中,国庆节期间颗粒物污染浓度高出平日32.8%,表明人为活动的加剧影响PM2.5的排放;周末与工作日期间无显著差异。在空间分布上,金水区、管城回族区污染最为严重,工业燃煤、地铁施工等源排放是造成污染的主要原因;位于远郊的岗里水库,受秸秆焚烧和市区污染输送等影响,PM2.5浓度亦维持较高水平。最后,研究将所构建的BP-ANN预测模型和多元线性回归模型对比,结果发现两模型在建模阶段预测值与真实值的拟合一致性指标分别为0.944、0.918,均方根误差分别为59.788、70.611;验证阶段拟合一致性指标分别为0.854、0.794,平均绝对误差分别为25.298、32.775,表明BP-ANN模型在预测郑州市PM2.5污染过程中更具优势。     

微纳米气液分散体系氧化脱除天然气汽车尾气中的复合污染物

采用微纳米气液分散体系对天然气汽车尾气中的复合污染物进行氧化脱除.实验结果表明:CH4、NO和SO2的脱除率均随着吸收液中NaCl、十二烷基硫酸钠(SDS)、Fe2+和Mn2+投加量的增加而先升后降,在酸性和碱性条件下均随着pH的增大呈先升后降的趋势;进气CH4、NO、SO2质量浓度为429,267,571 mg/m3...     

参数完全不确定系统在未知输入下的损伤识别

由于各种因素的影响,实际结构系统与计算模型有着不小的差异。本文针对结构系统参数及基底输入完全未知情况下的损伤识别问题,构造了与质量无关的结构规格化刚度参数和阻尼参数,提出了关于结构规格化参数和层间质量比的非线性最小二乘迭代优化识别方法,并给出了用规格化参数进行识别损伤和地震动反演的公式。算例表明本方法是有效的。     

多目标规划及其在危险废物管理中的应用

多目标规划是处理多指标函数的重要方法,是目前国内外研究较多的一种规划方法。本文对国内外多目标规划的理论、求解和应用等方面进行了综述。结合多目标规划的特点和危险废物管理的特性,分析了危险废物全过程系统规划管理方法,确定了目标函数、决策变量、约束条件,建立了一个综合考虑了费用和环境影响相关目标的复合效用函数的危险废物全过程多目标系统规划模型,并分析了模型参数的选择。最后,将多目标规划模型应用于重庆市危险废物系统管理中。该模型的合理应用对我国区域性危险废物科学的管理具有参考价值。     

次级河流回水区叶绿素a与影响因子的多元分析——以临江河为例

为了对次级河流回水区富营养化进行深入研究,把长江次级河流之一的临江河回水区为研究对象,根据2007年10月至2008年9月临江河回水区中游叶绿素a含量及其水质理化指标的监测数据,分析了临其叶绿素a浓度的时间分布,对叶绿素a浓度及影响因子进行相关分析,找出与叶绿素a显著相关的环境因子并建立多元逐步回归模型。结果表明：临江河回水区叶绿素a浓度峰值主要集中在5月上旬至9月下旬,变化范围为227～661 mg/m3。临江河回水区叶绿素a浓度变化受多个环境因子共同影响,与水温、流速、透明度、COD、总磷之间显著相关,而与总氮相关性不显著。经过叶绿素a及其影响因子的相关分析,建立了以水温、流速和总磷为自变量,叶绿素a浓度为应变量的逐步线性回归模型,模型初步验证结果表明：多元逐步回归模型可以用来描述临江河回水区叶绿素a浓度的变化。通过对临江河回水区叶绿素a及其影响因子的分析,控制临江河回水区水体中磷含量应是其富营养化防治工作的重点,防治工作应主要在春末和整个夏季,尤其是在5、6月份。     

TiO_2光催化同时脱硫脱硝效率影响因素研究

基于多元线性回归,对TiO2光催化同时脱硫、脱硝效率进行了预测研究.在最佳实验条件下,预测了不同SO2和NOx浓度的光催化脱除效率.依据正交试验结果,确定了最佳运行工况,将温度、湿度、SO2和NOx浓度对同时脱硫、脱硝效果的影响程度划分为3个等级,在此基础上有针对性地提出了可行措施.     

Developing Peak Discharges for Future Flood Risk Studies Using IPCC's CMIP5 Climate Model Results and USGS WREG Program

Extreme climate events, floods, and drought, cause huge impact on daily lives. In order to produce society resilient to extreme events, it is necessary to assess the impact of frequent and high intensity storm events on design parameters. This article describes a methodology to develop future peak “design discharges” throughout the United States that can be used as a guidance to map future floodplains. In order to develop a lower and upper limit for anticipated peak flow discharges, two future growth scenarios — Representative Concentration Pathways (RCPs)‐RCP 2.6 and 8.5 were identified as the weak and strong climate scenario respectively based on the output from the global climate models. The Generalized Least Square technique in United States Geological Survey's Weighted Multiple Regression (WREG) program was used to develop regression equations that relate peak discharges to basin and climate parameters of the contributing watershed. The design discharges reflect the most recent climate model results. Number of frost days, heavy rainfall days, high temperature days, and snow depth were found to be the common extreme climate parameters influencing the regression equations. This methodology can be extended to other flood frequency events if rainfall data is available. The future discharges can be utilized in hydraulics models to estimate floodplains that can assist in resilient infrastructure planning and outline climate change adaptation strategies.