桂林中小河流洪涝气象风险预警系统设计

基于自动站、数值预报和雷达估测降水等多种雨量资料,利用ArcGIS技术提取河流的经纬度、流域范围,利用泰森多边形技术计算流域面雨量,结合对桂林中小河流域的历史暴雨洪涝风险个例分析结果,确定临界面雨量,建立桂林中小河流域洪涝灾害风险等级预警系统。利用数学内插技术进行雨量精细化插值,实现全市100多个水库、200多条河流关键点的雨量监测、预报、预警。利用Web和GIS技术实现桂林中小河流洪涝预警网页发布。     

液位系统的辅助变量复合建模方法研究

针对发电过程控制策略设计和计量方法研究过程中,对系统模型要求越来越高的现状,基于辅助变量最小二乘(RIVLS)辨识方法,提出一种分别以一阶惯性加纯滞后模型(FOPDT)和二阶惯性加纯滞后模型(SOPDT)为基本组成部分,以建模误差的均方差为加权因子的复合建模方法,并通过实验室液位系统建模仿真过程,证明新算法的有效性。仿真结果表明:该方法具有提高建模准确性的作用,该建模方法可以扩展应用于其它对模型精度要求较高的生产过程中。     

催化氧化技术治理苯化工装置和罐区含氮挥发性有机物废气

采用催化氧化技术对某石化企业苯胺、硝基苯等生产装置和罐区的含氮挥发性有机物(NVOCs)废气进行集中处理,建成了一套20 000 Nm~3/h规模的安全高效处理装置。采用自主研发的WSH-2N型蜂窝状Pt-Pd-Ce催化剂,在高效氧化有机物的同时,高选择性地将有机氮转化为N_2。运行结果表明,净化气非甲烷总烃质量浓度低于15 mg/m~3,非甲烷总烃去除率大于99%,NO_x质量浓度低于10 mg/m~3,苯、苯胺、硝基苯、环己烷等特征有机污染物浓度均低于检出限,各项指标优于国内外现有技术。     

动态污水处理过程的多模型动态矩阵控制

针对活性污泥法污水处理系统的强耦合和动态变化特性,提出一种用于前置反硝化脱氮工艺的多模型动态矩阵(DMC)解耦控制方法;通过K-均值聚类分析法对外界入水中氨氮浓度进行聚类,获得以聚类中心为入水氨氮浓度的静态模型集合,分别设计线性DMC解耦控制器;再以当前时刻外界进水氨氮浓度和聚类中心为基本元素,构造切换函数,实现多模型切换。将该方法应用于活性污泥1号模型(ASM1)中,获得了较好的动态仿真效果。     

云南宁洱6.4级地震灾区范围的快速判断

采用云南175个历史强震的等震线图、云南数字等震线模型和云南1：400万活动断裂资料,对常规正圆法灾区范围量化与数字等震线模型灾区范围量化得到的云南宁洱6．4级地震灾区范围进行了对比,分析了地震等震线长轴方向与活动断裂的关系。结果表明,灾害地震的灾区范围用等震线模型来量化比常规用正圆来量化更加符合地震的客观情况。     

Evaluation of the RAMS continuous monitor for determination of PM2.5 mass including semi-volatile material in Philadelphia,PA

The real-time ambient mass sampler (RAMS) is a continuous monitor based on particle concentrator, denuder, drier, and tapered element oscillating microbalance (TEOM) monitor technology. It is designed to measure PM2.5 mass, including the semi-volatile species NH4NO3 and semi-volatile organic material, but not to measure PM2.5 water content. The performance of the RAMS in an urban environment with high humidity was evaluated during the July 1999 NARSTO-Northeast Oxidant and Particles Study (NEOPS) intensive study at the Baxter water treatment plant in Philadelphia, PA. The results obtained with the RAMS were compared to mass measurements made with a TEOM monitor and to constructed mass obtained with a Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) sampler designed to determine the chemical composition of fine particles, including the semi-volatile species. An average of 28% of the fine particulate material present during the study was semi-volatile organic material lost from a filter during particle collection, and 1% was NH4NO3 that was also lost from the particles during sampling. The remaining mass was dominantly nonvolatile (NH4)2SO4 (31%) and organic material (37%), with minor amounts of soot, crustal material, and nonvolatile NH4NO3. Comparison of the RAMS and PC-BOSS results indicated that the RAMS correctly monitored for fine particulate mass, including the semivolatile material. In contrast, the heated filter of the TEOM monitor did not measure the semi-volatile material. The comparison of the RAMS and PC-BOSS data had a precision of +/-4.1 microg/m3 (+/-9.6%). The precision of the RAMS data was limited by the uncertainty in the blank correction for the reversible adsorption of water by the charcoal-impregnated cellulose sorbent filter of the RAMS monitor. The precision of the measurement of fine particulate components by the PC-BOSS was +/-6-8%.     

废弃酸碱精制实现变压器油清洁生产

利用糠醛精制代替酸碱精制实现变压器油清洁生产，每年减少废渣排放5454t，减少加工损失5454t，取得了良好的环保效益和经济效益。     

Evaluation of the RAMS Continuous Monitor for Determination of PM2.5 Mass Including Semi-Volatile Material in Philadelphia,PA

Abstract

The real-time ambient mass sampler (RAMS) is a continuous monitor based on particle concentrator, denuder, drier, and tapered element oscillating microbalance (TEOM) monitor technology. It is designed to measure PM_2.5 mass, including the semi-volatile species NH₄NO₃ and semi-volatile organic material, but not to measure PM_2.5 water content. The performance of the RAMS in an urban environment with high humidity was evaluated during the July 1999 NARSTO-Northeast Oxidant and Particles Study (NEOPS) intensive study at the Baxter water treatment plant in Philadelphia, PA. The results obtained with the RAMS were compared to mass measurements made with a TEOM monitor and to constructed mass obtained with a Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) sampler designed to determine the chemical composition of fine particles, including the semi-volatile species. An average of 28% of the fine particulate material present during the study was semi-volatile organic material lost from a filter during particle collection, and 1% was NH₄NO₃ that was also lost from the particles during sampling. The remaining mass was dominantly nonvolatile (NH₄)₂SO₄ (31%) and organic material (37%), with minor amounts of soot, crustal material, and nonvolatile NH₄NO₃. Comparison of the RAMS and PC-BOSS results indicated that the RAMS correctly monitored for fine particulate mass, including the semi-volatile material. In contrast, the heated filter of the TEOM monitor did not measure the semi-volatile material. The comparison of the RAMS and PC-BOSS data had a precision of ±4.1 μg/m³ (±9.6%). The precision of the RAMS data was limited by the uncertainty in the blank correction for the reversible adsorption of water by the charcoal-impregnated cellulose sorbent filter of the RAMS monitor. The precision of the measurement of fine par-ticulate components by the PC-BOSS was ±6-8%.     

Ti-SnO_2电解快速去除熄焦循环水中COD

以Ti-SnO2电极作为阴阳极,利用电解池对焦化厂熄焦循环水COD进行去除。极板间距为1 cm,6个极片组成电解池,处理熄焦循环水。实验结果表明:废水被稀释1倍时,污染物的浓度有利于COD的去除;最佳去除条件是电解电压为11 V,p H值为6;当电解时间为0.5 h时,废水的COD由230 mg/L降低到138 mg/L,满足《炼焦化学工业污染物排放标准》中规定的焦化生产废水经处理后用于熄焦时对COD的要求;电解时间增加到2 h,废水的COD由230 mg/L降低到66 mg/L,去除率达到80%。