城市街区流场和污染物扩散的数值模拟研究

利用天气预报(WRF)模式提供边界条件和初始条件驱动Fluent模式,模拟了榆中县城市区域的大气流动和污染物扩散。WRF模式在一定误差要求下对研究区域的基本气象要素的模拟准确率均在70%以上,较为准确地模拟气象要素实况,为Fluent模式提供了可靠的初始条件和边界条件;Fluent模式充分刻画了复杂城市下垫面的建筑物对污染物扩散的影响,较好地反映了不同区域污染物浓度差异;通过WRF-Fluent耦合模式的模拟,显示有建筑群存在的城市环境中,流场相对于环境风产生显著改变,进而反映建筑群中污染物的复杂扩散形态。结果表明,WRF-Fluent耦合模式作为一种研究城市建筑密集区域的大气流动状态和污染物扩散过程的方法是可行的。     

海岸地区基于AERMOD的热力内边界层对大气污染物扩散影响的模拟研究

海岸地区热力内边界层(TIBL)对大气污染物扩散具有重要影响。选取杭州湾地区某区域为模拟区,采用一个TIBL高度的简单计算模式模拟模拟区的TIBL高度,将其耦合到空气质量模式AERMOD中,并对AERMOD的相关模块和参数进行了相应的修改,再分别利用原AERMOD和改进后的AERMOD,模拟了不同污染源情景下的大气污染物地面浓度分布。结果表明,在多数情况下,由于TIBL对于大气污染物扩散空间的限制,大气污染物的地面最大浓度有所升高,地面浓度的高值区范围也有所增加,具体影响特征取决于污染源与TIBL的相对高度以及污染源距离海岸的相对位置。     

大气面源模式具体应用探讨

大多数工业发达国家,均以法律形式规定地面大气环境质量标准,并根据当地气象等自然条件,通过大气扩散模式来确定大气污染物排放标准。所用的模式是对高斯模式进行必要     

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。     

基于元胞自动机的大气扩散模型及GIS可视化

基于对目前常用大气扩散模型以及大气扩散特性的分析,采用通过局部转移规则实现宏观涌现的复杂系统建模工具-元胞自动机来建立时空动态的大气扩散模型。结合MATLAB的矩阵运算能力和GIS的栅格数据处理能力进行模型的实现与可视化。仿真结果表明,所建立的模型不仅能动态模拟大气污染的高斯扩散等常用扩散模式,通过合理的模型参数设定也可动态模拟非常规扩散模式,如模拟时段内风向风速发生多次变化或者模拟区域存在湍流等条件下的扩散过程,得到准确的污染物时空动态分布,可望为大气污染防治提供决策支持。     

基于Fluent城市大气污染物扩散数值模拟

城市大气污染问题已经引起广泛的关注,其中对城市中大气污染物的迁移扩散过程还需进一步研究。为了探究城市复杂地形下大气污染物扩散预测的新模式,采用计算流体力学方法,建立了数值预测模型,构造出水平均匀的大气边界层模拟风场;进一步对建筑物影响下的大气污染物扩散过程进行了模拟,并与实验结果进行了对比。结果表明:数值模拟结果与实验结果基本吻合,计算流体力学方法可用于城市复杂地形下大气污染问题的研究工作;模拟结果与湍流模型的选取和湍流施密特数的设置有密切关系;采用SST k-ω湍流模型对此类问题较适宜,随着湍流施密特数的增大,扩散范围逐渐增大。     

建筑物对高架点源大气污染物扩散影响的模拟研究

运用数值方法对城市中高架点源排放大气污染物的扩散规律进行了模拟研究,在计算区域内建立了三维数学模型,并将拉格朗日法描述的颗粒轨道模型耦合到风场。本研究计算了地面风速为3 m/s时的大气流场,并模拟研究了该风场条件下气体污染物的扩散和固体颗粒污染物的运动轨迹。通过分析模拟结果,给出了高架点源中排放的气体污染物的扩散区域和固体颗粒污染物运动轨迹的变化规律。     

大气污染环境医学模式的初步探讨

数学模式在环境科学研究中有着广泛的应用。例如,表示污染物扩散转移变化规律的物理模式;表示污染物在生物体内累积消长规律的生物模式;还有化学模式等。本文探讨大气     

杭州市风、逆温的气候特征与大气污染

影响大气污染物扩散和稀释的主要因素有两方面。1.气象的动力因子——风和湍流。两者对污染物在大气中的扩散与稀释起决定作用。大气湍流是气流作无规则运动。风包括风向、风速。风向决定污染物迁移方向,风速大     

狭长交叉山谷中污染物浓度预测分析

为更准确地预测狭长交叉山谷中大气污染物浓度,利用高斯山谷扩散模式和美国Earth Technology Incorporat-ed公司研究的中尺度空气质量扩散模型CALPUFF对某山谷工业园区所在的狭长山谷中大气污染物浓度进行了计算。计算中,CALPUFF模型考虑了山谷中地表地形的变化,融入了诊断风场模块CALMET。...     

Fuel reformulation in the Metropolitan Area of Mexico City

Two models frequently used to simulate the dispersion of pollutants in the atmosphere have been compared. This is necessary because only a well-tested and well-calibrated simulation model can be a good representation of the reality of the dispersion of pollutants. The models evaluated (HYSPLIT_4 with its four variants and MEDIA) were run using as input parameters the same meteorological dataset (for 23-26 October 1994) from the French model ARPEGE. The following statistical criteria were compared: the space and time evolution of the pollutant cloud; the variation of statistical parameters in time and space; and the differences between the simulated and measured values of concentration in time for six different stations. The results emphasise the characteristics of the two models and their abilities in the framework of the air quality monitoring.     

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.     

Evaluation of traffic-producing turbulence schemes within Operational Street Pollution Models using roadside measurements

Low wind scenarios are associated with the worst air pollution episodes in urban street canyons. Under these conditions, operational dispersion models often over-predict pollutant concentration. Traffic-producing turbulence (TPT) becomes dominant in mixing and diluting traffic-related pollutants under low wind speed conditions. Determining the TPT effect on the flow and dispersion patterns within urban street canyons is crucial for the development of detailed operational dispersion models for assessing urban air quality. Several spatially averaged TPT formulations have been recently proposed in the literature. However, only a few attempts have been made so far to incorporate different TPT schemes into operational dispersion models and evaluate their performance using measurements.In this paper, several TPT schemes presented in literature were evaluated. Two TPT schemes were implemented in the well-validated Windows version of the Danish Operational Street Pollution Model (WinOSPM). Both formulations were evaluated using six independent datasets of roadside CO concentrations collected in European cities. Statistical and sensitivity analyses were undertaken to test the performance of the different formulations. The results showed that the overall model performance was significantly sensitive to the TPT schemes adopted. The model performance improved when a detailed characterisation of the TPT, depending on the density of road traffic, was used.     

Derivation of exemption formulas for air quality regulatory applications

The regulatory agencies and the industries have the responsibility for assessing the environmental impact from the release of air pollutants, and for protecting environment and public health. The simple exemption formula is often used as a criterion for the purpose of screening air pollutants. That is, the exemption formula is used for air quality review and to determine whether a facility applying for and described in a new, modified, or revised air quality plan is exempted from further air quality review. The Bureau of Ocean Energy Management’s (BOEM) air quality regulations are used to regulate air emissions and air pollutants released from the oil and gas facilities in the Gulf of Mexico. If a facility is not exempt after completing the air quality review, a refined air quality modeling will be required to regulate the air pollutants. However, at present, the scientific basis for BOEM’s exemption formula is not available to the author. Therefore, the purpose of this paper is to provide the theoretical framework and justification for the use of BOEM’s exemption formula. In this paper, several exemption formulas have been derived from the Gaussian and non-Gaussian dispersion models; the Gaussian dispersion model is a special case of non-Gaussian dispersion model. The dispersion parameters obtained from the tracer experiments in the Gulf of Mexico are used in the dispersion models. In this paper, the dispersion parameters used in the dispersion models are also derived from the Monin-Obukhov similarity theory. In particular, it has been shown that the total amount of emissions from the facility for each air pollutant calculated using BOEM’s exemption formula is conservative.

Implications:?The operation of offshore oil and gas facilities under BOEM’s jurisdiction is required to comply with the BOEM’s regulations. BOEM’s air quality regulations are used to regulate air emissions and air pollutants released from the oil and gas facilities in the Gulf of Mexico. The exemption formulas have been used by BOEM and other regulatory agencies as a screening tool to regulate air emissions emitted from the oil and gas and other industries. Because of the BOEM’s regulatory responsibility, it is important to establish the scientific basis and provide the justification for the exemption formulas. The methodology developed here could also be adopted and used by other regulatory agencies.     

Quantification of ventilation on distribution of gaseous pollutants emitted from stored swine manure

Abstract

This paper describes the quantification of the effects of ventilation on distribution of gaseous pollutants as a result of mass transfer from stored manure to ventilation air in a swine confinement building. A multiple airflow regions model is developed and used to simulate the dynamics of gaseous pollutants in any airspace within a ventilated slotted‐inlet enclosure. The model predictions compared favorably with the measured results adapted from a literature research at ventilation rates between 443 and 932 m³/hr (deviations of 5.1 ‐ 14.68%) for carbon dioxide and ammonia concentrations. A comparison between predictions and measured carbon dioxide concentrations derived from an environmental chamber test found deviations ranged from 3.1 ‐ 5.6% at ventilation rates between 281 and 995 m³/hr. The results suggest that the model can be experimentally applied between ventilation rates of 443 and 995 m³/hr. The model also capable of predicting air exchange rate required to maintain acceptable levels of gaseous pollutants in swine confinement buildings based on gas emission rates.     

A methodology to estimate odors around landfill sites: the use of methane as an odor index and its utility in landfill siting

The estimation of odor production and dispersion from landfill sites is a very complicated task because of the different chemical species that exist in biogas. To site a new landfill, it is necessary to know the distance that odors can travel around the landfill under atmospheric conditions that increase the concentration of pollutants. Although CH4 is an odorless gas, it can be used as an index to determine the dispersion of low-reactivity odorous species around a landfill site. Methane production rates, estimated by biogas production models, were used by an air dispersion model to determine the spatial distribution of CH4 around landfill sites. By utilizing dispersion models under extreme atmospheric conditions, a maximum CH4 concentration around the landfills was determined. Based on the ratio between CH4 and odorous chemical species, the spatial distribution of the concentration of an odorous species was determined for those species with low reactivity in the atmosphere. For odorous species with high reactivity in the atmosphere, a dispersion-reaction model must be used. In this way, the acceptable distance between new landfills and residential areas can be determined. The proposed methodology could be used as a design tool for those who are interested in landfill siting.     

Analysis of air quality observations with the aid of the source-receptor relationship approach

In this study, an attempt was made to analyze time series of air quality measurements (O3, SO2, SO4(2-), NOx) conducted at a remote place in the eastern Mediterranean (Finokalia at Crete Island in 1999) to obtain concrete information on potential contributions from emission sources. For the definition of a source-receptor relationship, advanced meteorological and dispersion models appropriate to identify "areas of influence" have been used. The model tools used are the Regional Atmospheric Modeling System and the Lagrangian-type particle dispersion model (forward and backward in time), with capabilities to derive influence functions and definition of "areas of influence." When high levels of pollutants have been measured at the remote location of Finokalia, particles are released from this location (receptor) and traced backward in time. The influence function derived from particle distributions characterizes dispersion conditions in the atmosphere and also provides information on potential contributions from emission sources within the modeling domain to this high concentration. As was shown in the simulation results, the experimental site of Finokalia in Crete is influenced during the selected case studies, primarily by pollutants emitted from the urban conglomerate of Athens. Secondarily, it is influenced by polluted air masses arriving from Italy and/or the Black Sea Region. For some specific cases, air pollutants monitored at Finokalia were possibly related to war activities in the West Balkan Region (Kosovo).     

Measurement and three-dimensional modeling of airflow and pollutant dispersion in an undersea traffic tunnel

Airflow and pollutant dispersion in a cross-harbor traffic tunnel were experimentally and numerically studied. Concentrations of the gaseous pollutants CO, NOx, and total hydrocarbons (THC) at three axial locations in the tunnel, together with traffic flow rate, traffic speed, and types of vehicle were measured. Three-dimensional (3D) turbulent flow and dispersion of air pollutants in the tunnel were modeled and solved numerically using the finite volume method. Traffic emissions were modeled accordingly as banded line sources along the tunnel floor. The results reveal that cross-sectional concentrations are nonuniformly distributed and that concentrations rise with downstream distance. The piston effect of vehicles alone can provide 9-23% dilution of air pollutants in the tunnel, compounded to a 23-74% dilution effect according to the ventilation condition.     

Assessment of traffic-related air pollution in two street canyons in Paris: implications for exposure studies

The small-scale spatial variability of air pollution observed in urban areas has created concern about the representativeness of measurements used in exposure studies. It is suspected that limit values for traffic-related pollutants may be exceeded near busy streets, although respected at urban background sites. In order to assess spatial concentration gradients and identify weather conditions that might induce air pollution episodes in urban areas, different sampling and modelling techniques were studied.Two intensive monitoring campaigns were carried out in typical street canyons in Paris during winter and summer. Steep cross-road and vertical concentration gradients were observed within the canyons, in addition to large differences between roadside and background levels. Low winds and winds parallel to the street axis were identified as the worst dispersion conditions. The correlation between the measured compounds gave an insight into their sources and fate. An empirical relationship between CO and benzene was established. Two relatively simple mathematical models and an algorithm describing vertical pollutant dispersion were used. The combination of monitoring and modelling techniques proposed in this study can be seen as a reliable and cost-effective method for assessing air quality in urban micro-environments. These findings may have important implications in designing monitoring studies to support investigation on the health effects of traffic-related air pollution.     

Daily mortality in the Philadelphia metropolitan area and size-classified particulate matter

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO4(2-), and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM2.5 and coarse particles, SO4(2-) and non-SO4(2-) portions of total suspended particulate [TSP] and PM10), measured on the day of death and the previous day. We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O3. Using joint regressions on peak O3 with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O3 seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.