洹河水中痕量有机污染物的研究

采用固相萃取技术 ,对洹河水中痕量有机物进行富集 ,大量的地表水被 C1 8键合相萃取后 ,洗脱液经干燥浓缩用于 GC和 GC/MS分析 ,鉴定出 64种有机物 ,并对苯系物、杂环类等 2 7种主要污染物作了定量测定 ,得出有机物的沿途变化规律。     

水样中痕量十溴联苯醚的分散液-液微萃取条件的优化

采用正交设计和Box-Penhnken响应面设计,对分散液-液微萃取技术萃取水样中痕量十溴联苯醚的条件进行了筛选和优化,得到最佳条件:四氯乙烯为萃取剂(10μl)、丙酮作分散剂(1ml)、pH范围5~9、离子强度,2%NaCl及萃取时间10min。此优化条件下分散液-液微萃取技术的萃取回收率可达92.37%~104.38%,富集倍数为508~611。优化条件下方法的线性范围为0.01~100ng/ml,检出限(S/N=2)为3.0pg/ml,加标回收率为96.25%~102.16%,精密度为5.44%~6.34%。     

村庄下倾斜煤层条带开采方法研究

针对我国"三下"(建筑物下、水体下、铁路下)压煤条带开采的实际情况,根据国内外有关条带开采的实践经验和技术要求,采用极限强度理论和压力拱理论对村庄下倾斜煤层条带开采进行了分开采深度设计,计算得出了条带开采的采出宽度和保留宽度;应用条带开采地表移动参数的模糊优化理论对概率积分法预计参数进行了选取,按照不同的开采深度,对村庄范围内的地表移动和变形值进行预计;根据预计的结果,对计算得出的条带开采尺寸进行检验和优化。研究表明,村庄下分采深条带开采尺寸设计和分采深地表沉陷预计,不仅可以提高地下煤炭资源的采出率,实现村庄在不搬迁情况下安全开采,也可最大限度地减小地下开采对地表建筑物的损害。     

绵竹市地表水环境质量现状及水环境容量分析

本文通过对绵竹市污染源现状调查及地表水环境现状评价,计算并分析了境内主要河流的水环境容量。绵竹市地表水环境污染较为严重,水环境容量短缺已成为绵竹市主要环境制约因素。为实现绵竹市水环境保护与经济社会的可持续发展,需及时采取污染物总量控制、工业污染防治、生活污水处理、控制农村面源污染等一系列措施。     

Effect of long-term changes in soil chemistry induced by road salt applications on N-transformations in roadside soils

Of several impacts of road salting on roadside soils, the potential disruption of the nitrogen cycle has been largely ignored. Therefore the fates of low-level ammonium-N and nitrate-N inputs to roadside soils impacted by salting over an extended period (decades) in the field have been studied. The use of road salts disrupts the proportional contributions of nitrate-N and ammonium-N to the mineral inorganic fraction of roadside soils. It is highly probable that the degree of salt exposure of the soil, in the longer term, controls the rates of key microbial N transformation processes, primarily by increasing soil pH. Additional influxes of ammonium-N to salt-impacted soils are rapidly nitrified therefore and, thereafter, increased leaching of nitrate-N to the local waterways occurs, which has particular relevance to the Water Framework Directive. The results reported are important when assessing the fate of inputs of ammonia to soils from atmospheric pollution.     

Initial Changes in Refilled Lysimeters Built with Metal Polluted Topsoil and Acidic or Calcareous Subsoils as Indicated by Changes in Drainage Water Composition

Soil translocation for recultivation of soil removed from construction sites and for the preparation of refilled lysimeters inevitably involves disturbance of soil structure, and, if intermediate storage is included, also drying and rewetting of the soil. We report on an experiment with model forest ecosystems, where uncontaminated forest subsoils were covered with non-contaminated or freshly heavy metal (mainly Zn and Cu) contaminated topsoil in large lysimeters. Monitoring of the chemical composition of the drainage water revealed two distinct soil conditioning phases. During an initial phase of about a year strongly elevated nitrate and sulfate concentrations occurred that were attributed to a mineralisation flush caused by the increased accessability of mineralisable nitrogen and sulfur in destroyed aggregates. These effects were significantly larger in lysimeters with calcareous subsoil than in those with acidic subsoil. The second phase was characterised by a gradual decrease in dissolved organic carbon and sulfate concentrations, in particular in the acidic subsoil. This decrease may be attributed to the depletion of pools made accessible during aggregate destruction or the formation of new aggregates. These chemical changes had only little effects on the concentrations of copper and zinc in the drainage water. Based on our results, it can be concluded that large refilled lysimeters can be used for many purposes without risk of compromised results, if a conditioning phase of about 1 year with sufficiently moist soil conditions is respected. Nevertheless, gradual changes in soil chemical characteristics still occur after this initial phase. Implications for the recultivation of sites using relocated soils are discussed.     

人工神经网络在预测深基坑周边地表沉降变形中的应用研究

深基坑开挖引起的周边地表变形预测是一个复杂非线性问题,引起地表沉降的影响因素很多,各因素之间呈高度的非线性关系。传统的基坑用边地表沉降变形预测方法存在着一定的局限性,其预测精度有待提高,而人工神经网络是一种多元非线性动力学系统,可以灵活方便地对多成因的复杂未知系统进行高度建模,实现全面考虑各种主要影响因素的深基坑周边地表沉降变形预测。本文介绍了误差反向传播(BP)网络模型的结构、学习过程及其算法的改进,径向基函数(RBF)网络模型的结构及其学习过程;分析了影响深基坑开挖周边土体沉降变形的主要影响因素;以25个基坑工程的地表沉降实测资料为训练样本,建立了11个输入影响因素的BP神经网络模型和RBF神经网络模型,通过对样本的学习训练过程及对5个检验样本的预测精度,说明了人工神经网络用于预测基坑周边地表沉降的可行性和准确性。     

压力板仪法测土-水特征曲线试验研究

非饱和土土-水特征曲线(SWCC)表示了土中含水量与吸力之间的关系。针对非饱和土干-湿循环过程中的吸力变化特征,开展试验研究。采用体积压力板仪实现非饱和土的脱湿和吸湿过程。试验成果显示:(1)土-水特征曲线是不稳定的,它与土体含水率的变化路径有关;(2)在干湿循环过程中,相同的基质吸力具有不同的含水量。     

水合氧化铁对痕量铀的吸附行为

研究了水合氧化铁的制备条件及其对痕量铀的吸附行为,结果表明,当加碱温度和反应温度均为80℃时,吸附剂具有最大比表面积172．8m^2.g^-1,当吸附平衡时间为30min,吸附温度为90－95℃,溶液pH≈6时,铀吸附量可达122mg.g^-1,但吸附体系中硼酸和硫酸镁的存在导致铀吸附量下降。     

空间分辨率与精度协同改进的卫星AOD产品降尺度模型

针对现有卫星气溶胶光学厚度(AOD)产品空间分辨率和精度往往难以满足大气污染精细治理实际需求,提出了一种耦合偏差校正的统计降尺度改进模型(SDBC).该模型基于“空间尺度不变性假设”引入相关驱动因子的额外空间信息实现AOD降尺度,并在此基础上通过偏差校正进一步提升降尺度产品的精度.以1km分辨率MAIAC AOD产品为例,在北京、大湾区、台湾岛3个典型地区开展模型验证.结果表明:(1)DEM、NDVI、人口数量和土地覆盖是影响AOD变化的细节因子,在SDBC空间降尺度过程中引入可将AOD产品的空间分辨率有效提升至500m,且降尺度产品验证R2最高可达0.88;(2)顾及卫星观测几何、质量标识、大气水蒸气柱、气溶胶模式等因子的偏差校正则可进一步提升降尺度AOD产品的精度,3个地区的验证R2均在0.85以上,最高可达0.93;(3)信息熵评估结果显示SDBC模型生成的500m AOD产品提高了原始MAIAC AOD产品的空间信息量.在保留了公里级产品AOD的空间分布格局的基础上,SDBC产品也增强了细节和纹理特征、改善了边界现象和马赛克效应.研究结果证实SDBC模型能有效协同改进现有卫星A...