The impact of physical processes on pollutant transport in Hangzhou Bay

A Lagrangian tracer model is set up for Hangzhou Bay based on Coupled Hydrodynamical Ecological model for Regional Shelf Sea (COHERENS). The study area is divided into eight subdomains to identify the dominant physical processes, and the studied periods are March (the dry season) and July (the wet season). The model performance has been first verified by sea-surface elevation and tidal current observations at several stations. Eight tracer experiments are designed and Lagrangian particle tracking is simulated to examine the impact of physical processes (tide, wind and river runoff) on the transport of passive tracer released within the surface layer. Numerical simulations and analysis indicate that: (1) wind does not change the tracer distribution after 30 days except for those released from the south area of the bay during the wet season; (2) the tide and the Qiantang River runoff are important for particle transport in the head area of the bay; (3) the Changjiang River runoff affects the tracer transport at the mouth of the bay, and its impact is smaller in the dry season than in the wet season. Supported by the Natural Science Foundation of China (No.40576080); National High Technology Research and Development Program of China (863 Program, No. 2007AA12Z182)     

Are artificial neural network techniques relevant for the estimation of longitudinal dispersion coefficient in rivers? / Les techniques de réseaux de neurones artificiels sont-elles pertinentes pour estimer le coefficient de dispersion longitudinale en rivières?

Abstract

Abstract Accurate application of the longitudinal dispersion model requires that specially designed experimental studies are performed in the river reach under consideration. Such studies are usually very expensive, so in order to quantify the longitudinal dispersion coefficient, as an alternative approach, various researchers have proposed numerous empirical formulae based on hydraulic and morphometric characteristics. The results are presented of the application of artificial neural networks as a parameter estimation technique. Five different cases were considered with the network trained for different arrangements of input nodes, such as channel depth, channel width, cross-sectionally averaged water velocity, shear velocity and sinuosity index. In the case where the sinuosity index is included as an input node, the results turned out to be better than those presented by other authors.     

感潮河流准动态水质回荡模型的研究

根据感潮河流的水流特性,研制了准动态水质回荡模型,并利用相似的皮尔逊-Ⅲ型分布曲线对其进行求解,提出了模型参数的计算方法。该模型适用于可降解有机污染物浓度的分布变化分析,经黄浦江干流氨氮浓度资料验证,成果比较满意。     

基于均匀混合假设的天然河道水质模拟方法

扩散质进入窄浅型河道后,通常采用有限差分法求解一维对流分散方程进行水质模拟,计算相对复杂。为简化计算,提出了根据河道断面特征等水力特性,将河道划分为若干单元,忽略不灵敏因子分散项对单元间扩散质交换的影响,并引入单元均匀混合假定,提出了基于均匀混合假设的天然河道水质模拟方法,建立相应的水质数学模型。算例表明,该模型运算稳定,与有限差分法模拟精度相当,但可大大简化并节省计算工作量。     

淮南市区浅层地下水污染机制研究

该文将重点阐述淮南市区浅层地下水的主要污染源及其分布形状、主要污染物及其性状特征,分析了不同来源的污染物对市区浅层地下水的污染途径.     

Kinematic wave solutions for pollutant transport over an infiltrating plane with finite‐period mixing and mixing zone

Kinematic wave solutions are derived for transport of a conservative non‐point‐source pollutant during a rainfall‐runoff event over an infiltrating plane for two cases: (i) finite‐period mixing and (ii) soil‐mixing zone. Rainfall is assumed to be steady, uniform and finite in duration, and it is assumed to have zero concentration of pollutants. Infiltration is assumed constant in time and space. Prior to the start of rainfall, the pollutant is distributed uniformly over the plane. In the first case, when rainfall occurs, the mixing of pollutant in the runoff water occurs in a finite period of time. In the second case, the chemical concentration is assumed to be a linearly decreasing function of rainfall intensity and overland flow. The solute concentration and discharge are found to depend on the flow characteristics as well as the solute concentration parameters. The characteristics of solute concentration and discharge graphs seem to be similar to those reported in the literature and observed in laboratory experiments. Copyright © 2002 John Wiley & Sons, Ltd.     

Sorption and desorption behavior of residual antidepressants and caffeine in freshwater sediment and sewage sludge

The use of antidepressants is widespread in modern times. Thus, they present a potential risk for ecosystems due to occurrence in domestic sewage containing unaltered metabolites and structures, even after the treatment plants have processed the sewage. The current research investigated the sorption and desorption of antidepressants(citalopram, venlafaxine, fluoxetine, sertraline, and amitriptyline) and caffeine from freshwater sediment and sewage sludge. The samples of freshwater sediment were ...     

2011年11月苏州一次灰霾天气过程分析

2011年11月10-14日苏州地区发生了一次严重灰霾天气过程,利用气象观测资料、探空资料及大气成分站监测资料对苏州三个站点的受污染情况进行了综合分析。结果表明：灰霾期间地面受弱气压场控制,风力较小,且有接地逆温的持续存在,大气水平和垂直输送都很弱,导致大量污染物在近地面堆积,能见度恶化;三站中昆山站灰霾持续时间最长,共计104时次,影响程度最重,重度灰霾占总数的39 %,中度和重度灰霾超过灰霾总数的一半;灰霾时各粒径颗粒物浓度均维持在较高水平,细粒子在可吸入颗粒物中占有较大比重,说明细粒子对灰霾贡献作用大,14日凌晨昆山及太仓出现大雾天气时细粒子比重甚至超过了灰霾时,而相对湿度峰值只有94 %,因此将该段天气定性为雾霾共存或者湿性霾更妥;秸秆焚烧污染期间,BC浓度明显上升,其绝对浓度要高出正常情况的3倍左右;通过CO/SO₂及PM₁₀/SO₂对比发现昆山站受秸秆焚烧污染程度要严重的多,因此推测昆山本地郊区可能也存在零星秸秆露天焚烧点。     

利用WRF-Chem模拟研究京津冀地区夏季大气污染物的分布和演变

应用WRF—Chem（Weather Research and Forecasting Model with Chemistry）模式模拟研究了2007年8月京津冀地区近地面O3、NO2、PM2.5浓度的时空变化特征,将模拟结果与观测数据进行详细对比,结果表明,模式可以较好地模拟O3、PM2.5,浓度的空间分布和时间变化特征,成功再现了8月33和PM2.5的几次积累增加过程,其中O,的模拟值与观测值的相关系数为0．69～0．86,PM2.5的相关系数为0．44～0．49,但模式对NO2的模拟相对较差,相关系数为0．27～0．43。北京、天津地区为O3月均低值区,月均体积浓度约30×10^-9,渤海及京津冀以西地区O3月平均体积浓度可达60×10^-9;PM2,呈现南高北低的分布特征,变化范围为120～240μg／m3。14时月平均03体积浓度在北京、天津地区低于周边地区,约为60×10^-9;而PM2.5质量浓度在环渤海地区和河北南部较高,为100～120μg/m^3。8月17日北京出现一次典型的高浓度O,污染事件,14时北京地区温度达到33℃,O3体积浓度为80×10^-9～110×10^-9。在局地排放、化学反应和外来输送的共同作用下,渤海西岸和北岸PM2.5的质量浓度超过120μg／m3,其中二次气溶胶质量浓度为50～100μg／m3,一次排放人为气溶胶质量浓度为10～20μg／m3,海盐质量浓度为1～7μg／m3,二次气溶胶是该地区PM2.5的主要贡献者。