浅水海湾排污扩散器初始稀释度的计算

流速和水深是影响浅水型海湾扩散器初始稀释能力的主要环境因素,其长时间序列的实测资料在现实中通常很难得到,而平面二维水动力模型的引入可为初始稀释度的计算提供必要和准确的水动力要素。通过建立二维水动力模型模拟受纳海域的流场,利用实测水文资料进行模型的率定和验证,模拟设计水文条件下附近水域的流场,然后提取排污口处的水深、流速和流向的时间序列,再利用近区模型计算任一时刻的初始稀释度,最后进行累积频率分析得到设计保证率下的初始稀释度。将该方法应用于杭州湾某排污扩散器初始稀释能力的评估,研究表明,利用远区模型为扩散器近区模拟提供环境水文要素,弥补了实际工程计算中缺乏实测水文资料的不足,并大大提高了近区模拟的计算精度。     

锦州湾潮间带底质重金属对海水的污染

本文从两方面论述了底质重金属对海水污染问题:(1)从五里河口经潮间带至海湾剖面线上,沉积物中铅、锌、镉地球化学相的分布规律及垂直方向的变化,并把沉积物间隙水重金属形态与沉积物重金属地球化学相联系起来分析铅、锌、镉被释放出来污染上覆海水的可能性;(2)阐述了间隙水水文地质条件,推导了水动力扩散数学模型,用实测资料求出水动力扩散系数 D_L=3.72×10~(-2)cm~2/sec,求得扩散迁移通量:J_(pb)=0.0421mg/m~2·h,Jzn=0.7787mg/m~2·h,Jcd=0.799mg/m~2·h,得出锦州湾潮间带是不可忽视的海水“二次污染源”的结论。     

基于活性炭的多孔介质水动力弥散系数测定

溶质在多孔介质运移过程中,水动力弥散系数不仅反映多孔介质的介质特性,同时也是描述溶质浓度随时空变化规律的重要参数。以颗粒状活性炭为研究对象,建立了水动力条件下的对流弥散方程进行溶质运移过程描述,并采用土柱扩散实验对其水动力弥散系数进行了测定。结果表明,借用反函数变化思路,可快速准确测定多孔介质的水动力弥散系数D;同时,变流速条件下D不为常量,且分子扩散的影响可忽略,其与渗流速度v之间满足D=9.328v1.796函数关系。由此建立的数学模型求解和D-v函数关系可为描述溶质在多孔介质中运移规律的研究提供一定的参考。     

基于MIKE21的万宝湖二维水环境数值模拟

以大庆市万宝湖为研究区域,应用MIKE21软件,建立万宝湖水动力和水质二维耦合模型,以实测资料为依据,进行模型参数的率定和验证。结合模拟结果,分析了万宝湖的水动力条件变化特征及其对于水环境中各种污染物迁移转化机制的影响。结果表明,万宝湖各主要污染物在靠近湖岸和排口附近浓度较大,并由湖岸向湖心呈梯度递减,形成岸边污染带,各污染物在不同的排口浓度分布具有差异性。最后,针对万宝湖的污染状况和污染物分布特点提出了相应的治理建议。     

海湾围垦工程作用下的动力沉积响应

通过采用平面二维有限元数学模型模拟计算乐清湾边滩围垦前后的潮流变化分布 ,在此基础上 ,预测围垦工程建设后导致泥沙冲淤变化。据此说明海湾围垦工程作用下的动力沉积响应。结果表明 ,海湾围垦工程对流场及泥沙冲淤的影响局限于工程区临近水域。在围区两侧 ,工程前后流速减小 ,使水流挟沙力降低 ,导致泥沙局部淤积 ;在围堤的转角外侧 ,将存在流速略有增大的区域 ,而在此的海床冲刷状况并不明显     

未确知信息对河流型水源保护区划分的影响

基于未确知数学理论,考虑河流环境系统信息的未确知性,定义二维水质模型主要参数为未确知参数,建立未确知二维水质模型,递推计算出保护区划分的合理长度及对应的污染物浓度取值区间及可信度分布,并对未确知二维水质模型中各参数的影响做了比较分析。结果表明,利用未确知二维水质模型,以COD为污染物计算的晋江干流水源二级保护区水域长度为6 220m,该长度能在0.934 0的主观可信度上保证水质安全,而基于确定性水质模型,利用各参数均值计算的保护区长度5 350 m存在95.22%的水质超标风险率。未确知二维水质模型各参数影响分析表明,模型应用的未确知参数及各参数变异性对模型计算结果有较大关系,未确知参数考虑越多,保护区划分长度越长;参数变异系数越小,其对计算结果影响越小。     

沿江区域开发对滩涂湿地的水环境影响

以长江口区域开发为例,通过建立平面二维数学模型,预测开发区产生的废水,经污水处理厂处理达标排入长江后,对长江口（北支）湿地自然保护区的水环境影响。预测结果表明,尾水正常排放时,对保护区的影响不大,这为区域开发的环境管理,提供了科学的依据。     

响应面法优化超临界水氧化处理农药废水

在间歇式超临界水氧化系统中对草甘膦农药废水进行降解实验。选取温度、反应时间、过氧量3个量为因素量,总有机碳(TOC)去除率为响应量进行中心组合设计（CCD）。在实验的基础上,利用响应面分析法（RSM）对实验结果进行分析及参数优化：建立了TOC去除率与各个因素关系的二次多项式数学模型;分析了各个因素单独的及相互作用对TOC去除率的影响;优化结果表明,在温度483℃、反应时间29.2 min、过氧量148.4%的条件下,达到了最佳效果,此时TOC的去除率为100%。     

有限单元法及其在河流污染计算中的应用

介绍了应用有限单元法预测计算河道较平直，水流稳定河流中污染物浓度分布的二维平面数学模型，该模型具有应用方便，计算迅捷等优点，计算中无须先知道排放口污染物掺混浓度，能直观地反映有多个排放口的河流中的污染物浓度分布的情况。     

河口建闸对楠溪江河口段纳污能力的影响研究

在调查楠溪江河口地区现状水环境和污染源分布的基础上,利用Mike21软件建立楠溪江河口的一维水动力及水质模型,据此分析90%保证率枯水年最枯月平均流量条件下,建闸对楠溪江河口段纳污能力的影响,以期为当地政府部门提供决策依据。     

Dynamics of cyanobacterial bloom formation during short-term hydrodynamic fluctuation in a large shallow, eutrophic, and wind-exposed Lake Taihu, China

Short-term hydrodynamic fluctuations caused by extreme weather events are expected to increase worldwide because of global climate change, and such fluctuations can strongly influence cyanobacterial blooms. In this study, the cyanobacterial bloom disappearance and reappearance in Lake Taihu, China, in response to short-term hydrodynamic fluctuations, was investigated by field sampling, long-term ecological records, high-frequency sensors and MODIS satellite images. The horizontal drift caused by the dominant easterly wind during the phytoplankton growth season was mainly responsible for cyanobacterial biomass accumulation in the western and northern regions of the lake and subsequent bloom formation over relatively long time scales. The cyanobacterial bloom changed slowly under calm or gentle wind conditions. In contrast, the short-term bloom events within a day were mainly caused by entrainment and disentrainment of cyanobacterial colonies by wind-induced hydrodynamics. Observation of a westerly event in Lake Taihu revealed that when the 30 min mean wind speed (flow speed) exceeded the threshold value of 6 m/s (5.7 cm/s), cyanobacteria in colonies were entrained by the wind-induced hydrodynamics. Subsequently, the vertical migration of cyanobacterial colonies was controlled by hydrodynamics, resulting in thorough mixing of algal biomass throughout the water depth and the eventual disappearance of surface blooms. Moreover, the intense mixing can also increase the chance for forming larger and more cyanobacterial colonies, namely, aggregation. Subsequently, when the hydrodynamics became weak, the cyanobacterial colonies continuously float upward without effective buoyancy regulation, and cause cyanobacterial bloom explosive expansion after the westerly. Furthermore, the results of this study indicate that the strong wind happening frequently during April and October can be an important cause of the formation and expansion of cyanobacterial blooms in Lake Taihu.     

Modeling studies of ammonia dispersion and dry deposition at some hog farms in North Carolina

A modeling study was conducted on dispersion and dry deposition of ammonia taking one hog farm as a unit. The ammonia emissions used in this study were measured under our OPEN (Odor, Pathogens, and Emissions of Nitrogen) project over a waste lagoon and from hog barns. Meteorological data were also collected at the farm site. The actual layout of barns and lagoons on the farms was used to simulate dry deposition downwind of the farm. Dry deposition velocity, dispersion, and dry deposition of ammonia were studied over different seasons and under different stability conditions using the short-range dispersion/air quality model, AERMOD. Dry deposition velocities were highest under near-neutral conditions and lowest under stable conditions. The highest deposition at short range occurred under nighttime stable conditions and the lowest occurred during daytime unstable conditions. Significant differences in deposition over crop and grass surfaces were observed under stable conditions.     

A Gaussian puff model with optimal interpolation for air pollution modelling assessment

A Gaussian plume model was modified to simulate the dispersion of non-reactive air pollutants under non-homogeneous wind conditions through a multi-puff approach. It was applied to the city of Lisbon and evaluated by comparison with measured sulphur dioxide data, showing a reasonable skill to estimate the transport and dispersion of pollutants under complex wind field and different atmospheric conditions. The modelling results were integrated with observed data, based on correlation functions determined from historical values, to obtain the improved analytical results by using optimal interpolation. A significant improvement over the predictions by the Gaussian puff model alone was achieved.     

Dry Removal of Gaseous Fluorine Pollutants

The conservation equations governing buoyant plume rise are solved for the case of non-uniform wind conditions. A power law is selected to represent the actual wind profile. Analytical solutions are presented both for uniformly stable and neutral atmospheric conditions. These solutions are shown to be of the same form as those obtained in the simpler uniform case but with the plume rise now depending explicitly on the wind speed shear. A sensitivity analysis of the effects on plume rise of typical variation in wind shear and entrainment reveals that the two quantities have an almost equal effect therefore justifying the use of the present model. To simplify computations a “uniform wind” is introduced such that when used in conjunction with Briggs' equations the results become consistent with those of the present theory.     

Influence of dissolved humic substances on the mass transfer of organic compounds across the air-water interface

The effect of dissolved humic substances (DHS) on the rate of water-gas exchange of two volatile organic compounds was studied under various conditions of agitation intensity, solution pH and ionic strength. Mass-transfer coefficients were determined from the rate of depletion of model compounds from an apparatus containing a stirred aqueous solution with continuous purging of the headspace above the solution (dynamic system). Under these conditions, the overall transfer rate is controlled by the mass-transfer resistance on the water side of the water-gas interface. The experimental results show that the presence of DHS hinders the transport of the organic molecules from the water into the gas phase under all investigated conditions. Mass-transfer coefficients were significantly reduced even by low, environmentally relevant concentrations of DHS. The retardation effect increased with increasing DHS concentration. The magnitude of the retardation effect on water-gas exchange was compared for Suwannee River fulvic and humic acids, a commercially available leonardite humic acid and two synthetic surfactants. The observed results are in accordance with the concept of hydrodynamic effects. Surface pressure forces due to surface film formation change the hydrodynamic characteristics of water motion at the water-air interface and thus impede surface renewal.     

A laboratory model of wake-affected stack's emissions

The high demand for electric energy during winter months, which coincides with the most critical conditions from the point of view of atmospheric pollution, makes it necessary to exploit at their maximum capacity even the oldest and smallest power plants, where dispersion is usually inefficient and greatly influenced by the aerodynamic wake of the buildings. In this paper the results of a series of hydrodynamic simulations, concerning the emissions of two 70 MW units of an electric power plant are presented. It was, in fact, necessary to decide whether a certain height-increase of the stacks, within the limits imposed by the building structures, would be sufficient to reduce the elevated ground-level concentrations found in some critical wind conditions, or if new stacks, external to the power plant buildings, would be needed.     

Estimating dust emission from a sandbank on the downstream Jhuoshuei River under strong wind conditions

An empirical emission model based on experimental data was proposed. The total suspended particulates (TSP) emission model obtained by using stepwise multiple-regression analysis was significant (p<0.001); moreover, the relatively high value of R-squared (R²=0.85), which indicated that four parameters included in the model (air temperature, soil silt content, soil moisture content, and wind speed) accounted for the particulate emissions from a sandbank. The results of the multiple-regression analysis demonstrated that the TSP emission factors increased with increase in air temperature, soil silt content and wind speed, but were inversely affected by the soil moisture content. The model equation verified the experimental results and proved itself to be an important tool in predicting the dust emissions from a sandbank under strong wind conditions.     

Evaluation of a Gaussian and a Lagrangian model against a roadside data set,with emphasis on low wind speed conditions

The evaluation of the high percentiles of concentration distributions is required by most national air quality guidelines, as well as the EU directives. However, it is problematic to compute such high percentiles in stable, low wind speed or calm conditions. This study utilizes the results of a previous measurement campaign near a major road at Elimäki in southern Finland in 1995, a campaign specifically designed for model evaluation purposes. In this study, numerical simulations were performed with a Gaussian finite line source dispersion model CAR-FMI and a Lagrangian dispersion model GRAL, and model predictions were compared with the field measurements. In comparison with corresponding results presented previously in the literature, the agreement of measured and predicted data sets was good for both models considered, as measured using various statistical parameters. For instance, considering all NO_x data (N=587), the so-called index of agreement values varied from 0.76 to 0.87 and from 0.81 to 1.00 for the CAR-FMI and GRAL models, respectively. The CAR-FMI model tends to slightly overestimate the NO_x concentrations (fractional bias FB=+14%), while the GRAL model has a tendency to underestimate NO_x concentrations (FB=−16%). The GRAL model provides special treatment to account for enhanced horizontal dispersion in low wind speed conditions; while such adjustments have not been included in the CAR-FMI model. This type of Lagrangian model therefore predicts lower concentrations, in conditions of low wind speeds and stable stratification, in comparison with a standard Lagrangian model. In low wind speed conditions the meandering of the flow can be quite significant, leading to enhanced horizontal dispersion. We also analyzed the difference between the model predictions and measured data in terms of the wind speed and direction. The performance of the CAR-FMI model deteriorated as the wind direction approached a direction parallel to the road, and for the lowest wind speeds. However, the performance of the GRAL model varied less with wind speed and direction; the model simulated better the cases of low wind speed and those with the wind nearly parallel to the road.     

Evaluation of low wind modeling approaches for two tall-stack databases

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.

Implications: AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.     

Prediction of pesticide concentrations in the atmosphere using an atmospheric diffusion model (linear source plume model)

The foundational model to predict concentration of pesticides in the atmosphere outside of the sprayed area was developed using the results of measured concentration in the atmosphere, in reference to the atmospheric diffusion model utilized for the air pollution prediction model. The atmospheric diffusion model assumes that the applied area was a topographically flat farmland, that wind direction and wind speeds were constant, and the pesticide was constantly discharged from the emission line sources. Therefore the linear source plume model (LSPLM) was developed. The concentration in the atmosphere was predicted by assigning the property of the pesticides and various conditions of measurements of the model, and compared with the measured them, then the adaptability of the model was examined. As a result, the correlation between the measured value and the predicted value in paddy and forested areas was significant (P < 0.01) although deviations in the order of tens were observed, the measured value and the predicted value were generally in agreement.