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1.
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   

4.
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   

5.
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   

6.
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   

7.
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   

8.
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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Changes in urban surface areas and population growth have significantly affected the weather and environment. Emissions of nitrogen oxides are increasing in the Pearl River Delta region. Nitrogen compounds emitted by factories and motor vehicles are the major sources of nitric pollution. To study the impacts of urbanization and the relationship between pollutant diffusion and the atmospheric environment, the nonhydrostatic mesoscale forecast model MM5 (v3.73), which was developed by Penn State University and the National Center of Atmospheric Research, and a mass continuity equation for air pollutants, were used in this study. Two experiments were designed. One experiment (BE) applied horizontal grid resolutions of 27, 9, 3, and 1?km in four nested domains. The other experiment adopted new land-use data (in domain 4) directly retrieved from Landsat Thematic Mapper imagery to replace the 1980s data of the United States Geological Survey in BE. A 48-h simulation (from 0000?UTC on 21 October to 0000?UTC on 23 October 2008) was conducted, with the first 12?h being the spin-up time and the remaining 36?h being the effective simulation, so as to capture the diurnal features of the thermally induced winds associated with the land–sea breeze and urban heat island circulations. The different results obtained from the two tests for wind circulation and air pollution dispersion and transportation in the Pearl River Delta region were analyzed. The simulated results show that the both experiments can well simulate land–sea breeze circulation and remarkable land–sea breeze evolution, comparing with observation data. The height of the PBL had a significant diurnal cycle. The structure of the wind field can obviously impact the dispersion of the NO x in three dimensions. Nitrogen oxides mainly diffused along the dominant wind direction (east or southeast wind), therefore the majority of the pollutants accumulated in the northwest region of the fine domain in both simulation experiments. However, it induced the pollutants concentration in an irregular pattern due to the fine-resolution grid spaces and complicated inland wind field in the northwest area of the inner domain. Moreover, increasing the proportion of urban surface caused sensible heat flux increase, latent heat flux decrease and humility reducing relatively in the region of urban surface characteristics apparently. Urbanization will cause pollution accumulated severely over the urban surface.  相似文献   

11.
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   

12.
对南通市区2022年4月初因疫情防控采取全区域静态管理期间的空气质量进行分析,以气象参数、臭氧前体物VOCs和NOx作为分析对象。结果表明:此次污染过程的主导因素是高温、强辐射、低湿和偏南风的气象条件。南通市区处于VOCs控制区,高温、强辐射使得VOCs挥发性增强,浓度升高。偏南方向的苏通园区和能达公园VOCs浓度较高且升幅较大,源解析结果表明这2个点位涂料溶剂使用占比升幅更高,既容易受附近石化和储油库影响,也容易受偏南风向的污染输送影响。据初步统计,静态管理期间南通市区停工数量为80%左右,污染期间NO2浓度高值区主要分布在沿江一带,长江南岸的张家港和常熟地区存在多家高排放企业,在偏南风下,张家港和常熟的污染物极易输送至南通市区。基于空气质量模型WRF-CAMx的O3和PM2.5来源解析结果显示,静态管理期间外来输送明显,占比为68.7%~84.7%。污染期间的船舶排放和二次转化贡献也不容忽视。建议南通市应重点加强工业、油气挥发和涂料溶剂源减排,同时加强区域联防联控,以便进一步改善空气质量。  相似文献   

13.
利用WRF-Chem模式,对2013年11月29日至12月11日长江三角洲地区的严重空气污染事件进行数值模拟,研究长三角核心区不同污染物本地源和外来输送所占比重。分析长三角核心区排放源对本地不同污染物浓度的污染贡献。结果表明,在2013年12月的这一次污染事件中,颗粒物平均本地贡献与外来输送基本比重相当;而SO_2、CO、NH_3、NO_x这4种气体污染物则以本地贡献为主,本地贡献的差异与气体的化学反应活性有关,活性越强本地贡献比重越大。污染过程中12月7日至12月9日00:00为污染最严重的时段,污染物的本地贡献有明显上升。区域间输送的方向和强度与地面风向、风速有紧密的联系。在边界层高度范围内,大部分污染物越往高空本地排放源的贡献越弱,外来输送主导作用增强,而硝酸盐在地面、1 km和1.5 km的本地贡献差异远小于其他污染物。  相似文献   

14.
This paper presents two simple methods for the estimation of the instantaneous background air pollution level in a study area around an emitting point source. The methods allow estimation of concentrations non-inclusive of the contribution of the local emitting source. Hourly records of several monitoring stations located around the point source and results of the diagnostic Lagrangian particle dispersion model LADISMO are used in the calculations. A hypothetical case study is used to demonstrate the application of the two methods. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   

15.
This work develops a source-oriented approach to locate the influential pollution sources and estimate their contributions to pollutant concentrations observed at a receptor site. The domain containing possible influential pollution sources is divided into systematic grid cells, and the influential grid sources are determined based on the locations of the segment endpoints of air trajectories arriving at the receptors. The contribution of each grid source is initially calculated using a formula derived from a Lagrangian box model and including the effects of source emissions, atmospheric dilution, and chemical transformation and deposition. The formula is described in detail in this study. Finally, the average contribution of each grid source is determined based on numerous analyzed events. The proposed approach was used to locate influential pollution sources and determine their contributions to a rural monitoring station during periods of high SO2 pollution in southern Taiwan. The contributions of sources in various 2 km by 2 km grid cells, five districts, three source categories, 8 industrial areas, and a power plant were evaluated. The results show that the major influential sources were in the northwestern region of south Taiwan, and belonged to three district and point sources. Furthermore, two industrial areas close to the evaluated stations were also very significant, and contributed about 30% of the total pollution.  相似文献   

16.
为推进城市空气质量精细化管理工作的实施,实现VOCs污染源精准排查,2019年3-4月,利用单光子电离飞行时间质谱对青岛市重点区域进行了VOCs走航观测。在排查到的污染源中,工业区的VOCs浓度较生活区整体偏高,且生活区、工业区夜间的VOCs浓度均较白天高。VOCs各类组分中,生活区白天苯系物、卤代烃、烯烃、烷烃的占比均在20%左右,夜间苯系物占比明显升高;工业区苯系物在白天和夜间的占比均最高,其他组分相对较小。浓度较高的前10位VOCs物种中,生活区白天烯烃物种占主导,夜间烷烃物种的比重明显增加;工业区苯系物、烯烃物种在白天和夜间的比重均较大,烷烃物种较小。生活区VOCs的污染源主要为机动车尾气排放和油品挥发,工业区主要为企业排放。烯烃和苯系物臭氧生成贡献较烷烃高,特别是丁烯、戊烯、己烯、甲苯、二甲苯/乙苯、三甲苯贡献显著,建议作为优控物种重点管控。  相似文献   

17.
A new index named Air Quality Balance Index (AQBI), which is able to characterise the amount of pollution level in a selected area, is proposed. This index is a function of the ratios between pollutant concentration values and their standards; it aims at identifying all situations in which there is a possible environmental risk even when several pollutants are below their limit values but air quality is reduced. AQBI is evaluated by using a high-resolution three-dimensional dispersion model: the air concentration for each substance is computed starting from detailed emissions sources: point, line and area emissions hourly modulated. This model is driven with accurate meteorological data from ground stations and remote sensing systems providing vertical profiles of temperature and wind; these data are integrated with wind and temperature profiles at higher altitudes obtained by a Local Area Model. The outputs of the dispersion model are compared with pollutant concentrations provided by measuring stations, in order to recalibrate emission data. A three-dimensional high resolution grid of AQBI data is evaluated for an industrial area close to Alessandria (Northern Italy), assessing air quality and environmental conditions. Performance of AQBI is compared with the Air Quality Index (AQI) developed by the U.S. Environmental Protection Agency. AQBI, computed taking into account all pollutants, is able to point out situations not evidenced by AQI, based on a preset limited number of substances; therefore, AQBI is a good tool for evaluating the air quality either in urban and in industrial areas. The AQBI values at ground level, in selected points, are in agreement with in situ observations.  相似文献   

18.
Among chemical industries, petroleum refineries have been identified as large emitters of a wide variety of pollutants. Benzene, toluene, ethylbenzene, and xylene (BTEX) form an important group of aromatic volatile organic compounds (VOCs) because of their role in the troposphere chemistry and the risk posed to human health. A very large crude oil refinery of the Baltic States (200,000 bbl/day) is situated in the northern, rural part of Lithuania, 10 km from the town of Ma?eikiai (Lithuania). The objectives of this study were: (1) to determine of atmospheric levels of BTEX in the region rural and urban parts at the vicinity of the crude oil refinery; and (2) to investigate the effect of meteorological parameters (wind speed, wind direction, temperature, pressure, humidity) on the concentrations measured. The averaged concentration of benzene varied from 2.12 ppbv in the rural areas to 2.75 ppbv in the urban areas where the traffic was determined to be a dominant source of BTEX emissions. Our study showed that concentration of benzene, as strictly regulated air pollutant by EU Directive 2008/50/EC, did not exceed the limit of 5 ppbv in the region in the vicinity of the crude oil refinery during the investigated period. No significant change in air quality in the vicinity of the oil refinery was discovered, however, an impact of the industry on the background air quality was detected. The T/B ratio (0.50-0.81) that was much lower than 2.0, identified other sources of pollution than traffic.  相似文献   

19.
深圳大运会期间一次光化学污染事件成因分析   总被引:1,自引:0,他引:1  
对深圳大运会期间8月20日发生的一次光化学污染过程进行分析。此次过程中,处于工业区的石岩大气成分站测得O3浓度小时平均最大值为213.4μɡ/m3,超过国家环境空气质量二级标准限值(200μɡ/m3),出现时间在当日13:00~14:00时。与处于城区的竹子林站和郊区的西涌站污染物浓度进行对比分析得知,此次光化学污染的主要特点是局地性较强,持续时间较短,影响范围小。同步的风速、风向、温度、相对湿度及紫外辐射等气象要素分析表明,此次光化学污染事件与气象条件关系非常紧密,当日天气晴朗、日照强烈、温度高、相对湿度适中,有利于光化学反应的发生,且不利的风向条件使得来自上风向城区的污染物易于累积。  相似文献   

20.
依据污染源调查资料,采用距离法对克孜勒苏河喀什市段污染物的入河量进行估算。结果表明:污水处理厂排放口是克孜勒苏河喀什市段最主要的污染源,COD、NH3-N、TN、TP的排放量占研究区域总量的61%~83%;其次是豆腐厂总排口,4项指标占研究区域总排放量的17%~37%,也是该河段的主要污染源。两者各指标排放量之和均超过区域总量的98%。不同类型的污染源中,生活源COD、NH3-N、TN、TP的贡献率分别是工业源的2、5、4和1.6倍。  相似文献   

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