集成膜法回收钛白废酸中硫酸

对扩散渗析回收钛白废酸中硫酸与减压膜蒸馏联合浓缩废酸进行了实验研究。结果表明,扩散渗析的酸回收率、回收酸浓度和亚铁泄漏率随料液流量的增大而减小,而酸渗析速度及酸对硫酸亚铁的分离系数却随之增大;随水料比的增大,酸回收率、酸渗析速率和亚铁泄漏率增大,回收酸浓度及酸对硫酸亚铁的分离系数减小;在选定实验条件下,硫酸浓度为1.92 mol/L的钛白废酸,先经扩散渗析进行酸盐分离,然后经减压膜蒸馏浓缩,可得到硫酸质量百分浓度为65%以上的浓缩废酸,达到了返回钛白生产使用的要求。     

基于风洞平台实验的大型罐区溢油事故后的油气扩散模拟

通过研究江苏省境内某实体罐区发生溢油事故后油气蒸发的扩散规律,掌握罐区空气浓度的变化,以达到保障罐区环保与安全的目的.基于风洞平台实验,测定油气蒸发速率并通过实验风场数据验证数值模型的准确性,建立与实际油库1∶1的大型罐区模型,使用UDF编译环境风方程导入.通过CFD数值模拟,重点分析了罐区发生溢油事故后油气扩散规律、储罐间的油气积聚现象、风速对油气扩散及油气质量分数的影响.结果表明:在风速影响下,罐间会形成涡流,导致油气的积聚,形成危险区域;防火堤对油气扩散存在阻滞作用,而背风侧会使油气聚集;风速越小,油气扩散越慢,油气质量分数越高;风速越大,油品的蒸发速率越大,油气扩散越快,油气质量分数越小.本研究成果可为罐区设计、油库运行及安全环保管理提供参考.     

街道峡谷机动车尾气污染扩散模拟与影响因子分析研究

为预测和分析街道峡谷污染物浓度,研究了街道峡谷污染物浓度影响因子.利用重庆市交通干线街道峡谷两侧NOx浓度的监测数据,验证了街道峡谷机动车尾气污染扩散模型--OSPM模型.风速转换系数修正后的OSPM模型的模拟值与实测值的R达0.862 58;风场因子验证了风速转换系数修正后的OSPM模型能较好地模拟重庆市街道峡谷的污染物浓度,一定程度上能满足环境空气质量评价要求.同时,通过分析OSPM模型的影响因子,提出了控制街道峡谷机动车尾气污染状况的建议.     

气象条件对点源排放二噁英模拟的影响规律研究

为了对点源排放的固相颗粒物上二噁英大气扩散规律进行认识,选择周边为复杂地形的杭州某危险废物处置设施为研究对象。使用AERMOD模型,人为设置一系列风速、风向条件,并假定二噁英均在PM2.5上,进而分析PM2.5上二噁英在这些设定的气象条件下的扩散规律,从而认识其扩散规律。结果显示:(1)风速风向对最大落地浓度、最大落地浓度点距离排放源的距离(简称最大落地点距离)的影响较大,而地貌的不同也会有一定影响。(2)3.0m/s的风速时最大落地点距离达到最大(约800m),5.0m/s的风速时最大落地浓度达到最大。(3)地形的改变对最大落地点距离的影响有限。(4)在特定风速情况下,沿风向方向,二噁英落地浓度会出现双峰现象。     

高架连续点源落地浓度预测中风速的确定

高架连续点源污染物排放落地浓度是大气环境影响预测的主要内容。由于大气污染物扩散明显受气象条件尤其是风速的影响，而现有预测模型中对于风速的取值都是按经验值来确定的。通过分析在不同气象和烟源条件下，平均风速的计算方法对烟羽抬升高度以及最大落地浓度产生的影响，与实测值相比较确定了风速取值的合理方法，缩小了预测偏差。     

挥发性污染物苯在水气界面耦合扩散的浓度分布

为研究苯水体泄漏后水气污染的浓度时空分布，利用挥发性污染物水气耦合扩散模型进行预测计算，预测结果与水槽实验相结合，准确地描述了苯在水气界面耦合扩散的浓度分布规律：沿水流方向（x轴）浓度随时间向前推移，距离投放点越远，浓度峰值越小，出现时刻越晚；沿水流深度方向（y轴）浓度分布关于投放点z=0.20 m纵断面对称，在水气界面和空间变化界面（水槽边缘）浓度出现极小值，随着挥发量的增加，浓度峰值出现的位置由水中推移至大气中；沿水流宽度方向（z轴）浓度由投放点向两侧推移。分析了亨利常数、水流速度及风速对苯耦合扩散浓度分布的影响。     

关于建立城市风速廓线模式的方法

在近地层,风速是随高度变化的,表示风速随高度变化的曲线称为风速廓线,风速廓线的数学表达式称为风速廓线模式。在Holland烟气抬升公式和Suton扩散公式中,风速廓线模式对于确定烟气抬升高度△h和扩散参数Cy、Cz有着要重作用。因此,风速廓线模式的建立是大气扩散研究中不可缺少的一项工作。     

杭州城市可吸入颗粒物污染与气象条件关系的分级评价和BP神经网络评估

为了解杭州城市环境空气质量与气象条件之间的关系,利用杭州市区2003-2007年的可吸入颗粒物(PM10)浓度数据和气象资料,通过分级评价的方法和基于BP神经网络的污染物浓度评估模型,得到PM10浓度与气象条件的对应关系.结果表明,随着日降水量的增大,PM10浓度减小;风速与PM10浓度呈明显的负相关,随着风速的增大,PM10浓度明显减小;气象因素与PM10浓度之间呈非线性关系,大气能见度对PM10和相对湿度的变化极为敏感.随着PM10浓度的增大,大气能见度迅速降低,相对湿度越高,大气能见度则越低;近几年杭州市气象条件不利于大气污染物的扩散和清洗,是杭州城市环境空气质量上升缓慢的主要原因之一.     

采用数值风洞模型对热电厂烟塔合一大气污染扩散的研究

随着城市的快速建设,城市建筑的高度和体量不断增加,同时大气污染源的排放方式和排放状态也与从前发生了很大的变化,特别是热电厂采用烟塔合一排放方式的出现,对常规应用的稳态远距离以统计学为基础理论的高斯大气预测方法提出了挑战。目前国内外广泛使用的大气污染物预测模式——德国模式在烟塔合一排放方式的预测上存在着许多关键性问题,如大风下洗条件下,冷却塔附近空腔区的大小和范围、空腔区污染物最高地面浓度等无法给出准确的预测结果。为准确预测烟塔合一排放方式的大气污染物扩散情况,采用一种新的大气污染物扩散的预测模式——数值风洞模型进行模拟预测研究,预测结果表明,在烟塔合一排放方式下,大气污染物最高地面浓度随风速增加而增加,同时在冷却塔下风向存在负压区,污染物在该区域高浓度聚集。且在夏季6.0m/s风速下,冷却塔下风向最高地面浓度出现峰值,属于最不利的气象条件。数值风洞模型可利用图形化手段实现对空腔区产生、变化、破碎至再生成的全过程描述,从而建立了一种大气污染预测的重要手段。     

露天堆场防风抑尘网遮蔽效果的数值模拟

应用Fluent6.3标准k-ε方程对露天堆场周围空气流场进行数值模拟;计算来流风速6 m/s工况下,孔隙率为0、0.2、0.3、0.4、0.6、1时,抑尘网及料堆前后不同断面处风速的垂直分布及不同高度空气压力系数分布。结果表明,抑尘网网前1倍网高范围内,风速廓线受抑尘网影响显著,风速较无网工况最大降幅62.9%,且风速降幅随孔隙率增大而减小;抑尘网和料堆间区域,风速沿垂直高度非单调一致变化,30 m以下风速较无网工况小,30 m以上较无网工况大;堆后2倍堆高范围内,12 m高度以下处于回流区,风速较无网工况时大,12 m以上处于主流区,风速较无网工况时小;堆后3倍堆高距离外,各孔隙率风速廓线与无网工况一致。压力系数分布显示:网前3倍网高(66 m)至堆后3倍堆高(51 m)间压力系数变化显著,尤其在抑尘网处压力系数梯度大;孔隙率小于0.3时,迎风面负压最大,孔隙率大于0.4时,冠顶负压最大,至孔隙率为0.6时,料堆高度压力系数分布与无网工况一致。综合风速衰减和压力系数分布,孔隙率为0.2~0.4时,抑尘网遮蔽效果最佳。     

Wind tunnel study of air entrainment into two-dimensional dense gas plumes at the Chemical Hazards Research Center

Experiments in a neutrally stable wind tunnel boundary layer were made for two-dimensional (quasi-line) sources of carbon dioxide dispersing over two types of uniformly spaced (billboard) surface roughness elements. Velocity and concentration measurements were made with each surface roughness over a wide range of source Richardson number by varying carbon dioxide release rate and wind speed. Concentration measurements were made with a FID gas analyzer using an ethane tracer in the source gas, and velocity measurements were made with independent LDV and HWA systems. For each surface roughness, this paper describes the wind tunnel boundary layer and presents alongwind and vertical concentration profiles in the gas plume. Vertical velocity and concentration profiles were measured at selected downwind distances, and the profiles were integrated to confirm the consistency of the measurements with the mass of carbon dioxide released. The data are intended for development of improved vertical turbulent entrainment correlations for use in dense gas dispersion models applied to hazardous chemical consequence analyses.     

A model for the maximum credible hourly impact on any ground receptor from point sources with thermal plume rise

A pollutant dispersion model is developed, allowing fast evaluation of the maximum credible 1-h average concentration on any given ground-level receptor, along with the corresponding critical meteorological conditions (wind speed and stability class) for stacks with buoyant plumes in urban or rural areas. Site-specific meteorological data are not required, as the computed concentrations are maximized against all credible combinations of wind speed, stability class, and mixing height. The analysis is based on the dispersion relations of Pasquill-Gifford and Briggs for rural and urban settings, respectively, the buoyancy induced dispersion correlation of Pasquill, the wind profile exponent values suggested by Irwin, the buoyant plume rise relations of Briggs, as well as the Benkley and Schulman's model for the minimum mixing heights. The model is particularly suited for air pollution management studies, as it allows fast screening of the maximum impact on any selected receptor and evaluation of the ways to have this impact reduced. It is also suited for regulatory purposes, as it can be used to define the minimum stack size requirements for a given source as a function of the exit gas volume and temperature, the pollutant emission rates and their hourly concentration standards, as well as the source location relative to sensitive receptors.     

An Atmospheric Diffusion Model for Metropolitan Areas

An urban diffusion model, which does not require the use of an electronic computer, is presented. The main simplifying assumptions are that continuous pollutant sources are uniformly distributed over the urban area and vertical diffusion occurs until the effluent from each line source reaches the top of the mixing layer, after which the effluent is uniformly distributed through the mixing layer. After the appropriate vertical diffusion coefficient is specified, the calculated concentration is a function of source strength, linear dimension of the metropolis, mixing depth, and wind speed. The calculated concentration is interpreted either as a representative maximum concentration or, through integration, as the average concentration over the metropolitan area. When a representative pollutant concentration is known, the model may be used to determine the apparent “uniform” source strength.     

Use of the Kit Fox field data to analyze dense gas dispersion modeling issues

The 1995 Kit Fox dense gas field data set consists of 52 trials where short-duration CO₂ gas releases were made at ground level over a rough surface during neutral to stable conditions. The experiments were intended to demonstrate the effects on dense gas clouds of relatively large roughnesses typical of industrial process plants. Fast response concentration observations were made by 80 samplers located on four downwind lines (25, 50, 100, and 225 m), including profile observations on three towers on each of the closest three arcs. Detailed meteorological measurements were made on several towers within and outside of the roughness arrays. The data analysis emphasized the variation of maximum concentration with surface roughness, the dependence of cloud advection speed on cloud depth, the variation of the three components of dispersion with ambient turbulence, and the dependence of vertical entrainment rate on ambient friction velocity and cloud Richardson number. The Kit Fox data were used to evaluate a specific dense gas dispersion model (HEGADAS 3+), with emphasis on whether it would be able to account for the increased roughness. The model was able to satisfactorily simulate the observed concentrations, with a mean bias of about 5% and with about 90% of the predictions within a factor of two of the observations.     

A new Lagrangian particle model for the simulation of dense gas dispersion

A Lagrangian stochastic model (MicroSpray), able to simulate the airborne dispersion in complex terrain and in presence of obstacles, was modified to simulate the dispersion of dense gas clouds. This is accomplished by taking into account the following processes: negative buoyancy, gravity spreading and the particle's reflection at the bottom computational boundary. Elevated and ground level sources, continuous and instantaneous emissions, time varying sources, plumes with initial momentum (horizontal, vertical or oblique in any direction), plumes without initial momentum are considered. MicroSpray is part of the model system MSS, which also includes the diagnostic MicroSwift model for the reconstruction of the 3-D wind field in presence of obstacles and orography. To evaluate the MSS ability to simulate the dispersion of heavy gases, its simulation performances are compared in detail to two field experiments (Thorney Island and Kit Fox) and to a chlorine railway accident (Macdona). Then, a comprehensive analysis considering several experiments of the Modelers Data Archive is presented. The statistical analysis on the overall available data reveals that the performance of the new MicroSpray version for dense gas releases is generally reliable. For instance, the agreement between concentration predictions and observations is within a factor of two in the 72% up to 99% of the occurrences for the case studies considered. The values of other performance measures, such as correlation coefficient, geometric mean bias and geometric variance, mostly set in the ranges indicated as good-model performances in the specialized literature.     

An atmospheric dispersion model for the environmental impact assessment of thermal power plants in Japan--a method for evaluating topographical effects

An atmospheric dispersion model was developed for the environmental impact assessment of thermal power plants in Japan, and a method for evaluating topographical effects using this model was proposed. The atmospheric dispersion model consists of an airflow model with a turbulence closure model based on the algebraic Reynolds stress model and a Lagrangian particle dispersion model (LPDM). The evaluation of the maximum concentration of air pollutants such as SO2, NOx, and suspended particulate matter is usually considered of primary importance for environmental impact assessment. Three indices were therefore estimated by the atmospheric dispersion model: the ratios (alpha and beta, respectively) of the maximum concentration and the distance of the point of the maximum concentration from the source over topography to the respective values over a flat plane, and the relative concentration distribution [gamma(x)] along the ground surface projection of the plume axis normalized by the maximum concentration over a flat plane. The atmospheric dispersion model was applied to the topography around a power plant with a maximum elevation of more than 1,000 m. The values of alpha and beta evaluated by the atmospheric dispersion model varied between 1 and 3 and between 1 and 0.4, respectively, depending on the topographical features. These results and the calculated distributions of y(x) were highly similar to the results of the wind tunnel experiment. Therefore, when the slope of a hill or mountain is similar to the topography considered in this study, it is possible to evaluate topographical effects on exhaust gas dispersion with reasonable accuracy using the atmospheric dispersion model as well as wind tunnel experiments.     

Control of Asphaltic Concrete Plants in Los Angeles County

Characteristics of maximum short-term ground level concentrations from an elevated point source, namely, the effective plume height, the critical wind speed, the distance to the point of maximum concentration, and the maximum concentration, are derived from the gaussian plume model. Both phases of plume development—before and after it has reached its final height—are considered. The plume rise treatment includes both thermal buoyancy and momentum effects. Certain limitations on critical wind speed are discussed. The dispersion model whose basis is established in this paper should be especially useful in applications where on site meteorological data are unavailable.     

High-resolution simulation of volcanic sulfur dioxide dispersion over the Miyake Island

After severe eruptions of the volcano at Miyake Island in August 2000, a large amount of volcanic gas was released into the atmosphere. To simulate flows and dispersion of sulfur dioxide (SO₂) over Miyake Island, a set of numerical models was developed. The multi-nesting method was adopted to reflect a realistic meteorological field and to sufficiently resolve the flow over the island with a diameter of 8 km. The outermost model was the Regional Spectral Model (RSM) of the Japan Meteorological Agency (JMA) with a horizontal grid size of 10 km. Finer atmospheric structure was simulated with the nonhydrostatic model jointly developed by the Meteorological Research Institute and the Numerical Prediction Division of JMA (MRI/NPD-NHM) with grid intervals of 2 km, 400 m and 100 m. Realistic topography of the island was represented in the innermost model. The Lagrangian particle method was applied to the dispersion model, which is driven by the meteorological field of the 100 m grid MRI/NPD-NHM. The random walk procedure was used to represent the turbulent diffusion. The model was verified in four cases. Simulated SO₂ concentrations agreed well with observed concentrations at a monitoring station including temporal variation. Under a large synoptic change, however, accurate prediction became difficult. Further numerical experiments have been done to investigate characteristics of the flow and the distribution of SO₂. Steady inflows, classified according to the surface wind speed and direction, were assumed. Simulated SO₂ distribution on the ground apparently depends on the surface wind. Under relatively weak inflow, there is a large diurnal change in SO₂ distribution, affected by the thermally induced flow. SO₂ gas is widely spread downstream in the nighttime but hardly reaches the coastal area in the daytime. On the other hand, SO₂ gas steadily reached the downstream coast with little diurnal variation under the stronger inflow. Ground temperature, as well as the static stability of the inflow, also influences downstream wind, turbulent diffusivity and SO₂ distribution.