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利用合肥市臭氧和VOCs连续观测数据分析了合肥市臭氧及其前体物污染特征,并使用NAQPMS模型研究了合肥市不同季节臭氧来源情况。结果表明:O3已经成为影响合肥市环境质量的主要污染因子,O3高值区主要集中在5—6月和9月。合肥市大气VOCs中烷烃含量最丰富,其次是烯烃、芳香烃和炔烃;主要物种为乙烷、丙烷、乙炔、正戊烷、乙烯、环戊烷、异戊烷、正丁烷、异丁烷和甲苯。合肥市O3生成主要受VOCs控制,其中,烯烃是合肥市O3生成贡献最大的关键活性组分,乙烯的OFP贡献率居首位。合肥市不同季节O3来源差异较大,其中,本地排放是主要来源,夏季占比为50%,其余季节占比为30%~45%,O3存在跨省长距离输送特征,主导风向的变化是造成合肥市臭氧来源季节性变化的重要因素。  相似文献   

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以2种典型的污染排放源(点污染源和线污染源)为基础,提出排污窗口的概念,通过参数转换分解源强对污染扩散进行研究。首先在高斯污染扩散模型的基础上,对非持续性污染源强建模,然后以某烟囱的周期性排污分析,检验排污窗口设置的合理性。对于单双号限行的窗口性质的污染排放研究中,首先对交通流建立线污染扩散模型,然后融合元胞自动机(9元胞互影响)模拟区域多角度污染的扩散平衡,最后对"单双号限行"下北京市不同区域空气质量指标进行分析与仿真。分析结果表明,合理的排污窗口能够减轻污染程度及对人们日常生活的影响。  相似文献   

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通过资料分析和数值模拟开展了2015年8月1日—10日台风“苏迪罗”对珠三角地区臭氧(O3)污染影响的机理研究。结果表明,2015年8月5—8日,在台风接近登陆点的过程中,台风外围天气导致了高温、高辐射和静小风等气象条件,促进了光化学反应的进行和污染物的局地积累。同时,高温、高辐射等气象条件加剧了植被源区生物源挥发性有机物(BVOCs)的排放。采用化学传输模式模拟发现,植被BVOCs对O3污染的贡献最高可达24×10-9。结合拉格朗日粒子扩散模式(LPDM)探索了影响珠三角地区的主导气团,发现珠三角城市地区和高BVOCs源区存在交互传输的现象。污染期间,高BVOCs源区的一次排放产物(BVOCs)和二次产物(O3)经区域输送加剧了珠三角地区O3的污染。此外,研究发现台风外围条件下珠三角内陆盛行的偏北风与海陆热力差异引起的海风在沿海地区辐合,造成污染物局地积累,加剧并延长了O3污染。研究有利于加强对O3污染机理的认识,进而更好地采取针对性措施,有助于减小O3污染带来的危害。  相似文献   

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The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.  相似文献   

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An accurate prediction of the transport-reaction behaviour of atmospheric chemical species is required to fully understand the impact on the environment of pollution emissions. Elevated levels of secondary pollutants such as ozone in the lower atmosphere can be harmful to the health of both plants and animals, and can cause damage to property present in the urban environment. Detailed models of pollution mechanisms must therefore be developed through comparisons with field measurements to aid the selection of effective abatement policies. Such models must satisfy accuracy requirements both in terms of the number of species represented, and the spatial resolution of species profiles. Computational expense often compels current models to sacrifice detail in one of these areas. This paper attempts to address the latter point by presenting an atmospheric transport-reaction modelling strategy based upon a finite volume discretisation of the atmospheric dispersion equation. The source terms within this equation are provided by an appropriate reduced chemical scheme modelling the major species in the boundary layer. Reaction and transport discretisations are solved efficiently via a splitting technique applied at the level of the non-linear equations. The solution grid is generated using time dependant adaptive techniques, which provide a finer grid around regions of high spatial error in order to adequately resolve species concentration profiles. The techniques discussed are applied in two dimensions employing emissions from both point and area sources. Preliminary results show that the application of adaptive gridding techniques to atmospheric dynamics modelling can provide more accurately resolved species concentration profiles, accompanied by a reduced CPU time invested in solution. Such a model will provide the basis for high resolution studies of the multiple scale interactions between spatially inhomogeneous source patterns in urban and regional environments.  相似文献   

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随着社会经济的快速发展,我国臭氧污染日益严重,因此,研发出能定量评估气象条件对臭氧污染影响程度的诊断指数,成为提高和改善气象服务质量的重要任务之一。利用中国大陆地区2018年温度、总云量、风速、风向、相对湿度等气象场数据与臭氧浓度数据,研究臭氧污染敏感气象条件,统计各气象因子分布在不同数值区间时发生臭氧污染事件的相对频率(即分指数),按照分指数最大值和最小值的差值大小进行排序,筛选出10个与臭氧污染密切相关的气象因子,将10个气象因子的分指数进行累加,即得出臭氧综合指数。随后,对各地构建臭氧综合指数时采用的气象要素进行统计,得到出现频率最高的3个气象要素,并参考这些气象要素构建了臭氧潜势指数。分别以臭氧潜势指数和臭氧综合指数对北京市2019年臭氧日最大浓度建立拟合预报模型,结果表明:两类指数的拟合预报值与实测值有着相似的变化趋势;利用臭氧综合指数计算得到的预报值与实测值的相关系数为0.76,优于利用臭氧潜势指数计算得到的预报值与实测值的相关系数(0.64)。  相似文献   

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2020年12月底,以生态旅游业为主的重庆市渝东南地区出现了一次较为罕见的PM2.5污染过程,持续时间长且污染程度重。以渝东南地区武隆区为例,应用污染特征雷达图、后向轨迹模型及潜在源污染贡献估算等方法分析了本次PM2.5污染的特征及来源,结果表明:(1)在污染前期主要受扬尘、燃煤和机动车等污染排放影响,污染源直接排放贡献较大;中、后期污染受二次颗粒物影响显著,扬尘影响也较为明显。(2)污染期间的气流轨迹均为短距离输送,轨迹主要来自东北方向(65%)。(3)除自身污染排放贡献外,渝东北地区和主城都市区是武隆区PM2.5污染的主要潜在源区,对武隆区传输贡献占比超50%。  相似文献   

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PM(2.5) and VOCs (benzene, toluene, m-p-o-xylenes) concentrations were measured in an urban and a suburban site in Athens, Greece, during the period between April and November 2004. This period, which is considered to be the warmer period in Greece, is characterized by the development of sea-breeze over the Attica Basin. Additionally strong Northern, North-eastern winds called "The Etesians", predominate during the summer months (July-August), acting positively to the dispersion of pollutants. In this campaign, 24 days with sea-breeze development were observed, 15 days with northern winds, 6 days with southern winds while the rest of the days presented no specific wind profile. Maximum concentrations of PM(2.5), VOCs and nitrogen oxides, were detected during the days with sea-breeze, while minimum concentrations during the days with northern winds. Ozone was the only pollutant that appeared to have higher concentrations in the background site and not in the city centre, where benzene presented strong negative correlation with ozone, indicating the photochemical reaction of hydrocarbons that lead to the ozone formation. The BTX ratios were similar for both sites and wind profiles, indicating common sources for those pollutants. T/B ratio ranged in low levels, between 3-5 for site A and 2-5 for site B, suggesting vehicles emissions as the main sources of volatile compounds. Finally, the strong correlations of PM(2.5) and benzene concentrations, between the two sampling sites, indicate that both the city centre and the background site, are affected by the same sources, under common meteorological conditions (sea-breeze, northern winds).  相似文献   

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