Application of the AERMOD Model to Evaluate the Health Benefits Due to Air Pollution from the Public Transport Sector in Ha Noi, Viet Nam

Fine particulate matter (PM2.5) mainly originates from combustion emissions on-road transportation. Exposure to PM2.5 could be considered one of the primary causes of diseases such as heart attack, stroke, lung cancer, and chronic respiratory, which made it one of the most important co-benefits when evaluating the impact of GHG mitigation measures. This study quantifies the co-benefit of Ha Noi’s modal shift from private to public means of transport, which are reduced air pollution and extended life expectancy, combining AERMOD model and benefit transfer method. Analytical results show that shifting from motorbike to electric train could be the most beneficial option in term of health co-benefit, compared to the usage of standard buses and BRTs.

Space Observations and Global Climatic Data Reanalysis in AERMOD Modeling Package to Enhance the Industrial Air Pollution and Health Risk Assessment

We try to enhance the AERMOD industrial pollution dispersion model with remote sensing observations and climatic models based on them. In this paper, we focus on surface parameters (albedo, roughness, Bowen ratio) and land use classification on which they depend. We model maximum hourly concentrations and the resulting acute health risk and assess the effect on them produced by using remote sensing data for local areas around industrial plants instead of global standard AERMOD parameters. We consider five real multi-source plants for the effect of classification and two of them for the effect of surface parameters. The effect on the critical pollutant is measured in three ways: a) as difference between the yearly maxima of hourly concentrations of a critical pollutant (“absolute”);b) the same limited to daytime workhours and 95% quantile instead of absolute maximum (“regulatory”);c) as maximum hourly difference over a year (“instant”). The measure of effect is divided either by the reference concentration of the pollutant, which yields the impact on health risk, or by the concentration obtained with AERMOD standards, which yields relative measure of impact. For a), the impact of roughness dominates, that of albedo is small and that of the Bowen ratio is almost zero. For b), the impact of roughness is less prominent, and that of albedo and Bowen ratio is noticeable. For c), the impact is considerable for all three parameters. The effect of land use classification is considerable in all three cases a) - c). We provide the figures for different measures of remote sensing data effect and discuss the perspective of using remote sensing data in regulatory context.

AERMOD模型在大气环境影响评价中的应用——以某水泥窑处置固废危废项目为例

以某水泥窑处置固废危废项目为例,应用AERMOD模型,以PM10、PM2.5、TSP和二噁英为模拟因子,定量分析该水泥窑处置固废危废项目对区域大气环境质量的影响程度和对周围敏感点居民的健康风险。研究结果表明:PM10、PM2.5、TSP和二噁英的日均浓度模拟值占标率均小于1,均满足相应的环境质量标准限值要求;该项目周围所有敏感点的HI均远远小于EPA推出的可接受风险水平(HI<1),且LCR低于EPA推出的可接受风险水平(LCR<1×10^(-6)),即该项目生产过程排放的二噁英对周围敏感点的居民既不会造成致癌风险,也不会引起慢性健康风险。

Application of the AERMOD modeling system for environmental impact assessment of NO_2 emissions from a cement complex

We applied the model of American Meteorological Society-Environmental Protection Agency Regulatory Model（AERMOD） as a tool for the analysis of nitrogen dioxide（NO2） emissions from a cement complex as a part of the environmental impact assessment.The dispersion of NO2 from four cement plants within the selected cement complex were investigated both by measurement and AERMOD simulation in dry and wet seasons.Simulated values of NO2 emissions were compared with those obtained during a 7-day continuous measurement campaign at 12 receptors.It was predicted that NO2 concentration peaks were found more within 1 to 5 km,where the measurement and simulation were in good agreement,than at the receptors 5 km further away from the reference point.The QuantileQuantile plots of NO2 concentrations in dry season were mostly fitted to the middle line compared to those in wet season.This can be attributed to high NO2 wet deposition.The results show that for both the measurement and the simulation using the AERMOD,NO2 concentrations do not exceed the NO2 concentration limit set by the National Ambient Air Quality Standards（NAAQS） of Thailand.This indicates that NO2 emissions from the cement complex have no significant impact on nearby communities.It can be concluded that the AERMOD can provide useful information to identify high pollution impact areas for the EIA guidelines.

Application of WRF Model for Vehicular Pollution Modelling Using AERMOD

Vehicular pollution is becoming significant in urban areas because of increasing population. This is at ground level, so it gives high population exposure. In this study, Chembur, which is the most polluted area in Mumbai city due to industrial and vehicular sources, is selected for vehicular pollution modeling using AMS/EPA Regulatory Model (AERMOD). Meteorological parameters, land use surface characteristics and source emission data are collected as required by AERMOD. The results of modelling depend upon reliability of input data and meteorological data has a vital role in the performance of the model. Generally, temporally and spatially interpolated meteorological data is used in modeling. This is generally collected from nearby meteorological station but this causes inaccuracy of the results. In this paper, the Weather Research and Forecasting (WRF) model has been used to generate onsite data on nine meteorological parameters. The modeling of six roads of Chembur has been performed using above meteorological data. This approach gives good results of traffic modeling. The results of AERMOD are compared with observed air quality which has contribution from all sources in the region and relative contribution of vehicular sources identified.

基于AERMOD模型的大气环境影响评价对项目的优化建议--以福建省某拟建生活垃圾焚烧发电项目为例

运用AERMOD模型预测不同地表类型、烟囱高度、烟气流速、排烟温度对大气环境影响变化规律,以期能为项目选址、设计提供优化建议。结果表明:(1)不同土地利用类型的各污染物网格点最大贡献浓度占标率依次为针叶林<落叶林<城市外围<农作物<草地;(2)烟气出口流速对大气污染物扩散影响很小(变幅<1%),烟囱高度、排烟温度对大气污染物扩散影响较大;(3)拟建项目推荐方案为选址在周边内3km为针叶林,烟囱高度为90m,烟气流速取10~20m/s,排烟温度在130~150℃之间。

AERMOD模型和CULPUFF模型预测结果对比分析

烟团气流在遇到山体碰撞后会部分反弹,部分顺着山体向上扩散、向下扩散,烟团中沉降性强的污染因子会在碰撞处部分下沉,沉降性差或者不沉降的污染因子随着反弹的气流继续扩散。在2018年版大气导则推荐的进一步预测模型中,CULPUFF模型考虑了复杂地形烟团的迂回扩散;AERMOD模型不考虑迂回扩散,预测时烟团遇到山体阻隔在碰撞点全部向下沉,局部出现最大落地浓度富集现象,从而导致山体碰撞点处的浓度为最大落地浓度。因此,在复杂地形条件下,采用CULPUFF模型预测的结果比采用AERMOD模型预测的最大落地浓度结果小,扩散的范围大,结果更接近真实情况,项目的大气环境可行性更强。因此,在2018年版大气导则的要求下,复杂地形建议采用CULPUFF模型进行预测。

Assessing the Impact of Fugitive Dust Emissions from Cement Silos at Cluster of Concrete Batching Facilities Using Air Dispersion Modeling

This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM10) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM10 released from the cement silos into the air. Simulations were carried out for PM10 emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM10 emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m3, and the highest daily emission value is 0.6 μg/m3;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m3. The highest daily emission average value was 1250.09 μg/m3;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM10 pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.

美国AERMOD模型与中国大气导则推荐模型点源比较

介绍了美国AERMOD模型和中国大气导则推荐模型一般浓度公式,通过大气稳定度和扩散参数的确定、复杂地形处理和对流条件下污染物扩散等原理方面的比较认为,AERMOD模型优于大气导则推荐模型.以美国环境保护局(USEPA)2个试验场Clifty Creek(平坦地形)和Lovett(复杂地形)的数据资料为比较数据,分别用AERMOD模型和大气导则推荐模型计算SO2小时质量浓度,在Pasquill 6类稳定度下用相对偏差(FB)、预测值与观测值的比率(RHCR)及图形法(Q-Q图)等进行模型比较,结果表明:在RHCR和FB中,AERMOD模型除个别值外,其他均好于大气导则推荐模型;而大气导则推荐模型存在接近或大于模型可靠性界限0.67(0.66和0.74),说明其可靠性比AERMOD模型差;图形法比较中,强不稳定和不稳定下AERMOD模型明显好于大气导则推荐模型,而大气导则推荐模型预测值明显偏低,其他稳定度下结果相差不大.研究认为:在平坦地形和复杂地形条件下,AERMOD模型点源预测值均优于大气导则推荐模型,并从原理上进行了解释.

AERMOD模式系统理论

作为新一代法规性质的稳态大气扩散模式,AERMOD将最新的大气边界层和大气扩散理论应用到空气污染扩散模式中。AERMOD具有下述特点:(1)按空气湍流结构和尺度的概念,湍流扩散由参数化方程给出,稳定度用连续参数表示;(2)中等浮力通量对流条件采用非正态的PDF模式;(3)考虑了对流条件下浮力烟羽和混合层顶的相互作用;(4)AERMOD模式系统可以处理:地面源和高架源、平坦和复杂地形和城市边界层;(5)AERMAP提出了一个有效高度对流场的影响。示踪试验表明,AERMOD模拟的结果比较理想。

AERMOD在国内环境影响评价中的实例验证与应用

AERMOD是美国环保局推出的新一代空气质量模式系统,它由AERMET(气象数据预处理器)、AERMAP(地形数据预处理器)和AERMOD(大气扩散模型)3部分组成。结合宁波市北仑区域大气环境影响评价,对该模式系统进行模式验证,并应用于实际预测评价。验证结果表明,在采用适当的模型参数时,该系统预测值与实际监测值具有很好的一致性,SO2、NO2日均最高浓度预测准确率分别达到64.3%和85.7%。最后结合实际预测评价工作,提出AERMOD模式系统在国内环境影响评价工作中的优势及不足。

AERMOD模型模拟城市生活垃圾焚烧厂二噁英类物质扩散迁移

根据二噁英类物质在常温大气环境中的固相吸附态比例约为90%-100%的特性,提出以颗粒物TSP和PM10为载体模拟二噁英类物质扩散迁移过程,并采用AERMOD模型进行模拟.结果表明,100%和80%的气-固分配系数设置对二噁英类物质扩散迁移落地点浓度和距离影响不显著,颗粒物粒径分布系数影响较明显.二噁英类物质实测浓度值为0.23-1.66 pg I-TEQ/m3.以TSP为载体AERMOD模拟浓度值为0.13-1.81 pg I-TEQ/m3,以PM10为载体模拟浓度为0.15-1.68 pg I-TEQ/m3.两参数对模拟结果产生的平均总不确定性分别为24.31%和12.43%.AERMOD模型模拟值与实测值相对差比值为0.01-0.89,PM10模拟浓度值比TSP模拟浓度值更接近于实测值.

基于AERMOD及减排政策的昆明市工业区SO_2情景模拟

以昆明市工业区为试点,将2009年作为基准年,2015年作为情景年,利用Aermod模型系统以及相关数据对工业区内SO2环境浓度进行预测.模拟情景的建立基于"十二五"工业源减排规划.研究发现工业源减排措施将对区域SO2浓度有显著影响,降幅最高可达13%.2015年不同模拟时段的SO2等浓度下分布面积均较2009年有明显减小,高浓度地区个数变少,这种现象也出现在污染源非集中地区.研究结果表明利用模型预测可有效分析减排政策对工业区内环境质量状况的影响,有助于建立减排响应机制.

AERMOD空气扩散模型在沈阳的应用和验证

根据2003年1～12月沈阳逐日大气环境监测敷据、气象数据以及AERMOD模式系统建立并验证了空气扩散模型；同时，应用污染源排放清单管理工具软件建立了排放清单，其输出的数据格式满足AERMOD空气扩散模型的要求。验证结果表明：颗粒物的监测日平均值与模拟日平均值的相关性较好，81％的数值落在模拟值与监测值的2倍误差范围内，模拟值与监测值的相关系数为0．68；SO2有72％的数值落在模拟值与监测值的2倍误差范围内，模拟值与监测值的相关系数为0．64。

AERMOD模式高空气象资料处理方法研究

文章针对《环境影响评价技术导则大气环境》(HJ2.2-2008)推荐的AERMOD模式所需要的高空气象格点数据格式,以模拟山东省2009年逐时高空风温场、湿度数据为例,建立WRF中尺度模式模拟系统,并对WRF模式输出的模拟结果进行分析处理,编制格式处理程序,处理成rao探空标准格式,最终形成了高空气象资料处理技术方法。

AERMOD大气扩散模型研究综述

AERMOD模型是美国环保局和美国气象学会联合开发的一种大气扩散模型,它采用了最新的大气边界层和大气扩散理论,替代ISC(Industrial Source Complex)模型成为美国的新一代法规模型,该模型已被列入我国环境影响评价技术导则--大气环境(HJ/T2.2-2008)推荐模型之一。国内外针对该模型开展了很多研究,主要集中在:AERMOD模型与其它大气扩散模型的对比研究和评价;AERMOD模型运行所需气象数据的模拟以及AERMOD模型在某些领域中的具体应用。AERMOD模型较我国旧版环境影响评价技术导则--大气环境(HJ/T2.2-93)推荐模型更能反映污染物的实际扩散规律,但由于目前该模型系统在国内的应用不算广泛,而且该模型本身也一直在不断完善当中,因此,为验证它的可靠性、合理性及实用性并确定其预报准确率,建议在该模型推广应用到一个新的地区或城市之前应当经过模型评估过程。

基于AERMOD模型评估公路交通源PM_(2.5)的浓度分布

PM2.5是公路机动车主要污染物之一,对沿线居民的呼吸健康有直接的危害,因此有必要在公路建设环境影响评价中增加对交通源PM2.5扩散浓度的评估。本文通过分析空气质量模型AERMOD、PM2.5排放清单测算模型MOVES以及建模数据需求,在交通量调查、气象数据预处理以及道路源PM2.5排放清单测算的基础上,应用AERMOD模型评估了我国某高速公路沿线PM2.5的浓度分布水平。结果表明:在研究路段沿线下风向距路肩400m范围内,均受到公路交通源PM2.5污染(PM2.5净浓度≥4μg/m3)的影响;AERMOD模型可以精细化地评估道路机动车PM2.5对空气质量的影响,为道路沿线PM2.5浓度分布评估提供了一套研究方法,其评估结果对道路规划环境影响评价具有重要的参考价值。

适用于固定工业源泄放的扩散模型-AERMOD

本文就适用于固定工业源泄放的扩散模型-AERMOD模型的特点及基本公式进行了介绍。AERMOD模型是高斯扩散模型,其应用范围相当广泛。AERMOD模型较显著的特点有:1)以行星边界层湍流结构及理论为基础;2)对地面源和高架源的情形都适用;3)对简单地形和复杂地形进行了一体化的处理。

水陆设置对AERMOD模型预测的影响研究

为了研究扇区中水、陆设置对AERMOD模型预测结果的影响,本文以海南滨海地区某建设项目为例,在保持气象条件、地形条件和污染源参数不变的情况下,通过改变扇区中水、陆位置,比较其利用AERMOD模型进行大气环境影响预测的差异。结果表明:水、陆位置交换对点源小时平均浓度最大值的预测结果影响不大,但其高浓度出现时间和分布位置以及对关心点的预测结果均发生了明显的改变,这是因为扇区中水、陆位置改变,导致风向产生变化,从而影响到扩散位置的改变——即高浓度分布区域发生变化,同时由于风向发生变化,导致地表热通量的改变,也改变了行星边界层参数,最终使得AERMOD模型预测结果不同。

基于AERMOD模型的污染源排气筒高度与SO_2落地浓度的关系研究

基于AERMOD大气扩散模型,利用许昌市2009年的气象资料、地形资料分析了污染源主导风向上SO2年均落地距离与落地浓度的关系及不同排气筒高度与污染源主导风向上SO2年均最大落地浓度和最大落地距离的关系。结果表明,在特定的气象条件和污染物排放量条件下,主导风向下风向的SO2落地浓度约是上风向的4.8倍;污染源排气筒高度越高,SO2年均最大落地浓度愈小,最大落地浓度点与污染源的距离越远,因此提高污染源排气筒高度能够在一定程度上降低SO2年均落地浓度,减小污染源对地面影响。