基于事故修正系数的山区高速公路事故预测模型

为量化分析山区高速公路线形指标对交通事故发生及严重程度的影响,引入事故修正系数(CMF)概念,提出基于CMF的高速公路交通事故预测模型。验证事故数据服从零膨胀负二项(ZINB)分布,并标定10个不同线形组合路段的基本事故预测模型;在界定理想条件的基础上,借助优势比分析方法,建立10个不同线形组合相对于基本预测模型的CMF模型;通过弹性分析识别出对不同严重程度事故有显著影响的因素,并以此分析山区高速公路线形指标及线形组合的安全效应。研究结果表明：CMF能够定量反映不同线形组合的风险效应,且其值越高,事故率及事故严重程度可能更高;山区高速公路中,平曲线缓坡组合相对安全,平曲线陡坡组合、平曲线竖曲线组合均有较高的事故风险;平曲线与凹型竖曲线组合时的风险会略低于其与凸形竖曲线组合;控制纵坡度、减少平竖曲线的组合均有利于山区高速公路交通安全。     

分光光度法与离子色谱法测定降水中铵离子的对比

采用分光光度法和离子色谱法测定降水中铵离子,比对研究两种方法的测定原理、标准曲线和检出限。结果表明,两种方法对标准样品和实际样品分析测定均能达到质控要求,测定结果基本一致。离子色谱法方便快捷,污染少,结果准确可靠,可以同时测定多种阳离子。     

地铁上盖开发建设项目环境影响评价研究

地铁上盖开发建设项目具有广阔的应用前景,成为目前城市轨道交通建设发展推崇的模式。通过对地铁上盖开发建设项目的特点、环评重点内容总结,着重分析了此类项目噪声、振动、二次结构噪声环评执行的标准及影响分析方法,对此类项目建设开发提出了建议。     

流动注射系统测定海水中Cr~(6+)

设计了Cr6+流动注射自动在线检测系统,并对海水中Cr6+含量的检测条件进行了优化。本系统采用二苯碳酰二肼(DPC)比色原理,通过流动注射技术,结合光电检测、数字信号处理及自动化控制技术,实现了样品的全自动化分析。结果证明,本系统测定速度快(60样/时),线性范围宽(0.004~1.00 mg/L),检出限低(2.17μg/L),精密度高(RSD7.62%),实际水样的加标回收率为92.0%~100.8%。该系统具有简便快速、灵敏稳定、经济环保等优点,适用于海水、地表水、污水等各种水质中Cr6+的在线监测。     

UASB处理生物柴油废水的效果研究

采用升流式厌氧污泥床(UASB)工艺处理地沟油回收制备生物柴油废水,通过试验研究了UASB反应器各个阶段对该类废水的处理效果,并考察了甲基磺酸、对甲基苯磺酸两种预酯化催化剂对该类废水处理效果的影响。结果表明:当进水COD为15g/L、容积负荷为15kg/(m3·d)时,UASB反应器COD的去除率稳定在87%左右,出水VFA为4~6mmol/L,沼气产量为16.8L/d;当容积负荷稳定在5kg/(m3·d),进水甲基磺酸浓度为5500mg/L时,UASB反应器COD的去除率达83%以上,进水对甲基苯磺酸浓度为1 000mg/L时,UASB反应器COD的去除率为58.3%,从废水处理的难易程度角度考虑,建议采用甲基磺酸为预酯化催化剂。     

泥炭腐殖化度的测定方法研究

泥炭腐殖化度能反映沉积物中泥炭的分解程度,常被用作恢复古气候与环境的代用指标。本文对当前泥炭腐殖化度的5种测定方法:化学计算法、碱提取溶液吸光度法、经验公式法、标准曲线计算法和灰度度量法进行了系统分析和比较,重点介绍了碱提取溶液吸光度法,并依据哈尼地区的泥炭数据,对碱提取溶液吸光度法测定泥炭腐殖化度的可行性和可靠性进行了检验。     

都匀毛尖茶土壤中总磷含量的调查研究

目的:调查都匀毛尖茶土壤中总磷的含量;方法:以贵州省都匀市毛尖茶产地--螺丝壳山的土壤为研究对象,采用酸法消解,用钼酸铵分光光度法于700 nm波长处测定土壤中总磷含量;结果:都匀螺丝壳山中土壤中总磷含量在177.58 mg·kg-1~353.92 mg·kg-1之间;结论:都匀毛尖茶土壤中的总磷含量在全国基本水平范围以内,总磷含量与土壤的类型、土壤所处海拔高度无明显关系。     

构造湿地在污水处理厂二级出水后的深度处理应用研究

中国大部分污水处理厂目前均采用二级处理工艺,主要去除碳源污染物,而消解氮、磷类污染物的效果较差.在传统二级处理工艺基础上,对中水进行三级深度处理,BOD5、SS以及COD类污染物去除效果明显,但运行成本较高,处理量受限.人工构造湿地利用基质-植物-微生物复合生态系统的物理、化学和生物的三重协同作用,通过过滤、吸附与沉淀等作用,以及微生物同化分解和植物吸收转化等途径,可有效去除污水中的氮、磷、SS、有机物及重金属等污染物,且具有低投资、低运转费、低维持成本等特点.     

亚甲基蓝分光光度法测定废水硫化物的不确定度评定研究

分析了应用亚甲基蓝分光光度(GB/T16489-1996)测定废水硫化物测试过程中不确定度影响因素,主要来源为硫化物标准溶液、标准曲线拟合、随机效应、分光光度计和取样体积这五部分。本测量合成相对标准不确定度0.025 9;其中由测定样品质量引入的不确定度为0.024 7;由样品体积引入的不确定度为0.007 7。本次废水中硫化物测量结果为:0.110±0.006 mg/L,k=2(包含概率约为95%)。     

Compositions and sources of organic acids in fine particles (PM2.5) over the Pearl River Delta region, south China

Organic acids as important constituents of organic aerosols not only influence the aerosols' hygroscopic property, but also enhance the formation of new particles and secondary organic aerosols. This study reported organic acids including C14–C32fatty acids, C4–C9dicarboxylic acids and aromatic acids in PM2.5collected during winter 2009 at six typical urban, suburban and rural sites in the Pearl River Delta region. Averaged concentrations of C14–C32fatty acids, aromatic acids and C4– C9 dicarboxylic acids were 157, 72.5 and 50.7 ng/m3, respectively. They totally accounted for 1.7% of measured organic carbon. C20–C32fatty acids mainly deriving from higher plant wax showed the highest concentration at the upwind rural site with more vegetation around, while C14–C18fatty acids were more abundant at urban and suburban sites, and dicarboxylic acids and aromatic acids except 1,4-phthalic acid peaked at the downwind rural site. Succinic and azelaic acid were the most abundant among C4–C9dicarboxylic acids, and 1,2-phthalic and 1,4-phthalic acid were dominant aromatic acids. Dicarboxylic acids and aromatic acids exhibited significant mutual correlations except for 1,4-phthalic acid, which was probably primarily emitted from combustion of solid wastes containing polyethylene terephthalate plastics. Spatial patterns and correlations with typical source tracers suggested that C14–C32fatty acids were mainly primary while dicarboxylic and aromatic acids were largely secondary. Principal component analysis resolved six sources including biomass burning, natural higher plant wax, two mixed anthropogenic and two secondary sources; further multiple linear regression revealed their contributions to individual organic acids. It turned out that more than 70% of C14–C18fatty acids were attributed to anthropogenic sources, about 50%–85% of the C20–C32fatty acids were attributed to natural sources, 80%–95% of dicarboxylic acids and 1,2-phthalic acid were secondary in contrast with that 81% of 1,4-phthalic acid was primary.