T型街道内空气流动与污染物扩散特性研究

为研究T型街道峡谷内空气流动与污染物扩散传质的特性,利用数值模拟研究来流风向角(θ)的变化(θ为45°、90°和135°)对T型街道交叉路口内空气流动与机动车尾气污染物扩散传递的影响,并与风洞实验测量数据进行验证。3种湍流模型中,可实现k—ε模型计算的速度相对偏差小于8%,与风洞实验结果一致性最好。结果表明,来流风向角的变化,会造成从街道顶部或侧面进入街道内的气流方向及通量发生改变,从而显著影响T型街道交叉口内及其附近的流动结构和污染物浓度分布。污染物容易在建筑尾流区等流动不畅的区域产生聚集,造成污染浓度偏高。当θ=135°时,T型街道内通风条件最好,街道内行人呼吸高度和建筑临街立面附近污染物浓度水平均相对较低。由于流动结构的改善,T型街道峡谷内的污染水平低于一般街道峡谷。     

道路路障对街道峡谷内污染物扩散的影响

采用数值模拟,研究不同风向角α(α=0°、45°、90°)及道路屏障位置(中间单路障和两侧双路障)对街道峡谷内机动车尾气污染物扩散的影响。数值模拟采用标准κ-ε湍流模型且Sc_t选择0.3时,计算结果与风洞实验结果较好吻合。结果表明,2种路障布置方式可有效降低人行道内污染物浓度,特别是,当α=45°时,污染物浓度最多可降低46.23%。同时,风向角α对街道峡谷内污染物扩散影响较大。当α=90°时,空气流通不良使得污染程度最为严重,且污染集中在背风侧近地面。单路障比双路障布置对污染物扩散影响更大,前者使污染物主要集中在街道中心背风侧,其他位置浓度明显降低;双路障时仅在一定范围内改善人行道内空气品质,但对街道整体污染物分布影响不大。     

三维街道峡谷机动车尾气时空扩散模拟研究

针对信号控制路段,采用非稳态κ-ε湍流模型、组分输运方程进行非定常三维街道峡谷数值模拟,研究了三维街道峡谷内动态交通流下机动车污染物CO的时空扩散过程,并对比了含信号、不含信号的定常模拟结果.结果表明,(1)受信号控制及峡谷内流场影响,峡谷内污染物浓度呈现显著的时空不均匀性;(2)各路段背风面浓度值要大于迎风面,且背风面和迎风面浓度峰值均位于峡谷中部的人行横道区;(3)信号周期内人行横道区污染物浓度始终远高于峡谷内其他区域.在距离背风面建筑1 m的人行横道处污染物浓度可达24.15 mg/m3,超过国家空气质量二级标准141.50％;(4)受信号控制影响,含信号控制街道峡谷污染物浓度高于不含信号控制路段,人行横道背风面污染物浓度是不含信号控制人行横道的3.5倍.     

孤立与非孤立城市街道峡谷内污染物扩散

通过求解二维不可压N-S方程、k-ε方程及污染物对流扩散方程,模拟了孤立街道峡谷与非孤立街道峡谷内的流场及交通污染物浓度场.计算结果与风洞试验结果总体趋势一致.非孤立街道峡谷内污染物壁面浓度要大于孤立街道峡谷内的壁面浓度.通过计算街道峡谷建筑屋顶高度处的垂直方向污染物通量,说明了湍流扩散是污染物扩散出街道峡谷的主要原因,其污染物通量总为正,而平均流通量可以为负.非孤立街道峡谷由于平均流流动和湍流流动的总扩散通量减少,造成污染物在街道峡谷内集聚,从而理论上解释了非孤立街道峡谷与孤立街道峡谷污染扩散的差别.     

成都市轻型车尾气污染物排放趋势预测

机动车尾气污染物已成为影响城市大气环境质量的主要因素之一,预测未来机动车尾气污染物排放状况可以为城市机动车尾气污染防治提供有力的依据.依据成都市的经济发展趋势,设定了不同阶段的轻型车尾气污染物排放标准,并利用建立的尾气污染物排放趋势预测模型分析了该市轻型车尾气中颗粒物、NOx、总碳氢化合物、CO的排放量和变化趋势,并提出了相应的尾气污染物减排对策.     

计算流体力学模拟街道峡谷特征和风向对细颗粒物污染扩散的影响

街道峡谷结构和风向会对街道峡谷内的污染物浓度和扩散特征带来一定影响。利用计算流体力学(CFD)软件,针对街道峡谷高宽比、建筑物间隔(建筑物间空隙与街道总长度的比值)和风向对街道峡谷内细颗粒物扩散的影响进行数值模拟。模拟结果表明,建筑物间隔为20%,风向为北风,风速为3m/s,街道峡谷高宽比分别为1∶2、1∶1和2∶1时,街道中心线距地面1.5m高度细颗粒物最大质量浓度分别位于-19.3、-88.0、-19.3m(以与街道中心点的距离计,正值表示在街道中心点以东,负值表示在街道中心点以西,下同)位置,为37.5、46.4、28.4μg/m3。街道峡谷高宽比为1∶1,风向为北风,风速为3m/s,建筑物间隔分别为0、20%和40%时,街道中心线距地面1.5m高度的细颗粒物最大质量浓度分别位于148.0、-92.3、-186.7m位置,为88.1、31.6、33.7μg/m3。街道峡谷高宽比为1∶1,建筑物间隔为20%,风速为3m/s,且分别处于西风、北风和西南风时,街道中心线距地面1.5m高度的细颗粒物最大质量浓度分别位于165.3、58.0、1.5m位置,为10.6、11.2、16.0μg/m3。可见,CFD模拟近地面污染物扩散时应考虑街道峡谷结构和风向的影响。     

机动车污染排放模型研究综述

过去几十年,为了掌握机动车污染排放的规律和特征,向决策者提供科学有效的机动车污染控制措施,研究者们致力于研究机动车污染物排放的物化原理和影响机动车污染的主要因素,并据此建立多种尺度的机动车排放模型,以模拟城市区域或者街道的污染物排放.为了分析机动车的瞬态排放特征,目前的机动车排放模型研究正逐渐从宏观向微观发展,排放测试方法注重获取逐秒的排放数据,排放模型模拟的时间尺度和空间尺度逐步趋向微观.此外,机动车模型研究正趋向与交通模型进行耦合,从而揭示机动车在实际道路交通流中的排放特征.从机动车排放的主要影响因素、机动车排放测试、机动车排放因子模型及机动车排放清单等4个方面综述了国内外机动车排放研究现状和发展动向,对比并评价各种机动车排放模型方法的优缺点和适用范围,对我国的机动车排放模型发展方向进行了展望.     

重庆市机动车尾气对大气环境的影响分析及减缓措施

在对重庆市机动车保有量、主城区交通状况进行深入调查的基础上，对机动车尾气排放对大气环境的影响进行了细致的分析与评估。阐述了机动车尾气是造成重庆市大气污染的重要因素。同时结合国内外一些先进的预防、控制和处理汽车尾气污染的方法，及近年来的观察、研究和试验，提出了合理减缓、控制机动车尾气污染的措施，以防止机动车尾气污染进一步蔓延。     

机动车尾气扩散模型研究进展

机动车尾气扩散模型作为一种重要的工具被用于评估城市空气质量、为污染控制战略以及交通规划决策制定提供支持。对国内外机动车尾气扩散模式进行了回顾,结合各种模式的特征,将其分为综合扩散模式、开阔道路线源扩散模式、交叉口道路扩散模式以及街道峡谷扩散模式,分别对模式的优缺点以及其适用性进行了分析,针对我国道路交通特征,提出了模型本土化所需解决的问题和未来的研究趋势。     

广州市机动车排放污染三维仿真模拟研究

基于三维的对流一扩散方程,采用50 m× 50 m× 20 m的高分辨率网格对广州市机动车排放污染扩散的宏观分布状况进行了数值模拟研究,应用有限体积法数值求解上述方程.模拟过程综合考虑了广州市的路网结构、交通流和路网线源排放强度等因素,进行了均匀风速的简单气象条件试算.结果表明,机动车排放污染物浓度随交通流量而变化,随高度增加而下降,上风向污染物浓度大于下风向,模拟结果与实际污染情况具有较好的一致性.     

Comparative study of measured and modelled number concentrations of nanoparticles in an urban street canyon

This study presents a comparison between measured and modelled particle number concentrations (PNCs) in the 10–300 nm size range at different heights in a canyon. The PNCs were modelled using a simple modelling approach (modified Box model, including vertical variation), an Operational Street Pollution Model (OSPM) and Computational Fluid Dynamics (CFD) code FLUENT. All models disregarded any particle dynamics. CFD simulations have been carried out in a simplified geometry of the selected street canyon. Four different sizes of emission sources have been used in the CFD simulations to assess the effect of source size on mean PNC distributions in the street canyon. The measured PNCs were between a factor of two and three of those from the three models, suggesting that if the model inputs are chosen carefully, even a simplified approach can predict the PNCs as well as more complex models. CFD simulations showed that selection of the source size was critical to determine PNC distributions. A source size scaling the vehicle dimensions was found to better represent the measured PNC profiles in the lowest part of the canyon. The OSPM and Box model produced similar shapes of PNC profile across the entire height of the canyon, showing a well-mixed region up to first ≈2 m and then decreasing PNCs with increased height. The CFD profiles do correctly reproduce the increase from road level to a height of ≈2 m; however, they do not predict the measured PNC decrease higher in the canyon. The PNC differences were largest between idealised (CFD and Box) and operational (OSPM) models at upper sampling heights; these were attributed to weaker exchange of air between street and roof-above in the upper part of the canyon in the CFD calculations. Possible reasons for these discrepancies are given.     

Modelling dispersion of traffic pollution in a deep street canyon: Application of CFD and operational models

In this study, numerical modelling of the flow and concentration fields has been undertaken for a deep street canyon in Naples (Italy), having aspect ratio (i.e. ratio of the building height H to the street width W) H/W = 5.7. Two different modelling techniques have been employed: computational fluid dynamics (CFD) and operational dispersion modelling. The CFD simulations have been carried out by using the RNG k–? turbulence model included in the commercial suite FLUENT, while operational modelling has been conducted by means of the WinOSPM model. Concentration fields obtained from model simulations have been compared with experimental data of CO concentrations measured at two vertical locations within the canyon. The CFD results are in good agreement with the experimental data, while poor agreement is observed for the WinOSPM results. This is because WinOSPM was originally developed and tested for street canyons with aspect ratio H/W ≌ 1. Large discrepancies in wind profiles simulated within the canyon are observed between CFD and OSPM models. Therefore, a modification of the wind profile within the canyon is introduced in WinOSPM for extending its applicability to deeper canyons, leading to an improved agreement between modelled and experimental data. Further development of the operational dispersion model is required in order to reproduce the distinct air circulation patterns within deep street canyons.     

Influence of trees on the dispersion of pollutants in an urban street canyon—Experimental investigation of the flow and concentration field

Flow field and concentration measurements have been performed in an idealized model of an urban street canyon with one row of trees arranged along the center axis. The model was set up in an atmospheric boundary layer wind tunnel and the approach flow was directed perpendicular to the street axis. A line source embedded in the bottom of the street was used to release tracer gas for the simulation of traffic exhaust emissions. Trees with spherical crowns were modeled and positioned inside the street canyon, varying crown diameter, crown permeability, trunk height and tree spacing. Traffic-induced turbulence was simulated by rotating belts with thin plates. Concentrations were measured at the facades of the street canyon. For small tree crowns, only little changes in concentration were measured, however, increasing crown diameters led to increasing concentrations at the leeward street canyon wall associated with a reduction of local concentrations at the windward wall. For some cases, a variation of trunk height led to a modification of the concentration pattern on the walls. Increasing the tree spacing resulted in a noticeable concentration decrease. When compared to the situation with standing (but emitting) traffic, the traffic-induced turbulence by two-way car movements always contributed to a more homogenous concentration field inside the street canyon yielding to reduced mean concentration levels.     

A measurement campaign in a street canyon in Helsinki and comparison of results with predictions of the OSPM model

In 1997, a measuring campaign was conducted in a street canyon (Runeberg St.) in Helsinki. Hourly mean concentrations of CO, NO_x, NO₂ and O₃ were measured at street and roof levels, the latter in order to determine the urban background concentrations. The relevant hourly meteorological parameters were measured at roof level; these included wind speed and direction, temperature and solar radiation. Hourly street level measurements and on-site electronic traffic counts were conducted throughout the whole of 1997; roof level measurements were conducted for approximately two months, from 3 March to 30 April in 1997. CO and NO_x emissions from traffic were computed using measured hourly traffic volumes and evaluated emission factors. The Operational Street Pollution Model (OSPM) was used to calculate the street concentrations and the results were compared with the measurements. The overall agreement between measured and predicted concentrations was good for CO and NO_x (fractional bias were −4.2 and +4.5%, respectively), but the model overpredicted the measured NO₂ concentrations (fractional bias was +22%). The agreement between the measured and predicted values was also analysed in terms of its dependence on wind speed and direction; the latter analysis was performed separately for two categories of wind velocity. The model qualitatively reproduces the observed behaviour very well. The database, which contains all measured and predicted data, is available for further testing of other street canyon dispersion models. The dataset contains a larger proportion of low wind speed cases, compared with other available street canyon measurement datasets.     

Numerical modeling on air quality in an urban environment with changes of the aspect ratio and wind direction

Due to heavy traffic emissions within an urban environment, air quality during the last decade becomes worse year by year and hazard to public health. In the present work, numerical modeling of flow and dispersion of gaseous emissions from vehicle exhaust in a street canyon were investigated under changes of the aspect ratio and wind direction. The three-dimensional flow and dispersion of gaseous pollutants were modeled using a computational fluid dynamics (CFD) model which was numerically solved using Reynolds-averaged Navier–Stokes (RANS) equations. The diffusion flow field in the atmospheric boundary layer within the street canyon was studied for different aspect ratios (W/H?=?1/2, 3/4, and 1) and wind directions (θ?=?90°, 112.5°, 135°, and 157.5°). The numerical models were validated against wind tunnel results to optimize the turbulence model. The numerical results agreed well with the wind tunnel results. The simulation demonstrated that the minimum concentration at the human respiration height within the street canyon was on the windward side for aspect ratios W/H?=?1/2 and 1 and wind directions θ?=?112.5°, 135°, and 157.5°. The pollutant concentration level decreases as the wind direction and aspect ratio increase. The wind velocity and turbulence intensity increase as the aspect ratio and wind direction increase.     

基于人工神经网络的街道峡谷NOx浓度的数值模型研究

通过对反向传播人工神经网络的算法和网络结构的研究，发现拟牛顿算法训练速度较快，能够较好地接近误差目标值，同时建立了包括输入层、隐含层、输出层的人工神经网络三层拓扑结构。通过对街道峡谷人工神经网络的训练，模拟计算了街道峡谷NOx浓度分布值。结果显示，训练误差和测试误差比为1．11，训练样本的模拟值与实测值的相关系数为0．93，测试样本的模拟值与实测值的相关系数为0．87，模拟值与实测值的相关系数均高于显著水平为α=0．05与α=0．01所对应检验性表的相关系数临界值。该模型能够用于街道峡谷污染物浓度的模拟计算，具有较好的泛化能力。     

Influence of cetane improvers on the air quality in an urban street canyon

The concentration distributions of NO_x, PM, HC and CO in an urban street canyon have been estimated using a two-dimensional air quality numerical model based on the k– turbulent model and the atmospheric convection diffusion equation when various cetane improvers were used in diesel fuels. A wind vortex can be found within the street canyon, and the pollutants emitted from the bottom of the street canyon tend to follow the course of the wind field, moving circularly. The addition of cetane improvers can improve the air quality in a street canyon, all of the pollutants were found to decrease with increasing centane number.     

Three-dimensional modeling of air flow and pollutant dispersion in an urban street canyon with thermal effects

Effects of excess ground and building temperatures on airflow and dispersion of pollutants in an urban street canyon with an aspect ratio of 0.8 and a length-to-width ratio of 3 were investigated numerically. Three-dimensional governing equations of mass, momentum, energy, and species were modeled using the RNG k-epsilon turbulence model and Boussinesq approximation, which were solved using the finite volume method. Vehicle emissions were estimated from the measured traffic flow rates and modeled as banded line sources, with a street length and bandwidths equal to typical vehicle widths. Both measurements and simulations reveal that pollutant concentrations typically follow the traffic flow rate; they decline as the height increases and are higher on the leeward side than on the windward side. Three-dimensional simulations reveal that the vortex line, joining the centers of cross-sectional vortexes of the street canyon, meanders between street buildings and shifts toward the windward side when heating strength is increased. Thermal boundary layers are very thin. Entrainment of outside air increases, and pollutant concentration decreases with increasing heating condition. Also, traffic-produced turbulence enhances the turbulent kinetic energy and the mixing of temperature and admixtures in the canyon. Factors affecting the inaccuracy of the simulations are addressed.     

基于人工神经网络的街道峡谷NO_x浓度的数值模型研究

通过对反向传播人工神经网络的算法和网络结构的研究,发现拟牛顿算法训练速度较快,能够较好地接近误差目标值,同时建立了包括输入层、隐含层、输出层的人工神经网络三层拓扑结构。通过对街道峡谷人工神经网络的训练,模拟计算了街道峡谷NOx浓度分布值。结果显示,训练误差和测试误差比为1.11,训练样本的模拟值与实测值的相关系数为0.93,测试样本的模拟值与实测值的相关系数为0.87,模拟值与实测值的相关系数均高于显著水平为α=0.05与α=0.01所对应检验性表的相关系数临界值。该模型能够用于街道峡谷污染物浓度的模拟计算,具有较好的泛化能力。     

Simulation of wind-driven dispersion of fire pollutants in a street canyon using FDS

Air quality in urban areas attracts great attention due to increasing pollutant emissions and their negative effects on human health and environment. Numerous studies, such as those by Mouilleau and Champassith (J Loss Prevent Proc 22(3): 316–323, 2009), Xie et al. (J Hydrodyn 21(1): 108–117, 2009), and Yassin (Environ Sci Pollut Res 20(6): 3975–3988, 2013) focus on the air pollutant dispersion with no buoyancy effect or weak buoyancy effect. A few studies, such as those by Hu et al. (J Hazard Mater 166(1): 394–406, 2009; J Hazard Mater 192(3): 940–948, 2011; J Civ Eng Manag (2013)) focus on the fire-induced dispersion of pollutants with heat buoyancy release rate in the range from 0.5 to 20 MW. However, the air pollution source might very often be concentrated and intensive, as a consequence of the hazardous materials fire. Namely, transportation of fuel through urban areas occurs regularly, because it is often impossible to find alternative supply routes. It is accompanied with the risk of fire accident occurrences. Accident prevention strategies require analysis of the worst scenarios in which fire products jeopardize the exposed population and environment. The aim of this article is to analyze the impact of wind flow on air pollution and human vulnerability to fire products in a street canyon. For simulation of the gasoline tanker truck fire as a result of a multivehicle accident, computational fluid dynamics large eddy simulation method has been used. Numerical results show that the fire products flow vertically upward, without touching the walls of the buildings in the absence of wind. However, when the wind velocity reaches the critical value, the products touch the walls of the buildings on both sides of the street canyon. The concentrations of carbon monoxide and soot decrease, whereas carbon dioxide concentration increases with the rise of height above the street canyon ground level. The longitudinal concentration of the pollutants inside the street increases with the rise of the wind velocity at the roof level of the street canyon.