A dispersion model for traffic produced turbulence in a two-way traffic scenario

Low wind speed conditions are often associated with poor air quality in urban areas, especially near roadways. Predictions of pollutant concentration under such conditions, i.e. low wind-speeds and near road locations, are, however, complicated by the role of traffic produced turbulence (TPT) on pollutant mixing and dilution. Existing dispersion models consider the effect of TPT on pollutant concentrations near roadways, accounting for parameters such as vehicle intensity, vehicle speeds, etc, but do not explicitly account for the contribution of two-way traffic interaction on the pollutant dispersion parameter. The turbulent kinetic energy (TKE) resulting from a two-way traffic condition will be higher than that with a one-way traffic pattern. Here, we obtain a simple formulation for TKE under a two-way traffic pattern from the balance of production and dissipation of turbulence. Considering the vorticity generated by the two-way traffic and determining the equivalent drag coefficient, an expression for TKE due to the two-way traffic interaction was obtained for three different traffic density regimes: light, intermediate, and heavy. The model predictions are validated by comparison with published data from a field study. An improved parameterization of the TPT considering the two-way traffic interaction effect is seen to significantly improve predictions of near roadway pollutant concentrations.     

A CFD-based wind solver for an urban fast response transport and dispersion model

In many cities, ambient air quality is deteriorating leading to concerns about the health of city inhabitants. In urban areas with narrow streets surrounded by clusters of tall buildings, called street canyons, air pollution from traffic emissions and other sources may accumulate resulting in high pollutant concentrations. For various situations, including the evacuation of populated areas in the event of an accidental or deliberate release of chemical, biological and radiological agents, it is important that models should be developed that produce urban flow fields quickly. Various computational techniques have been used to calculate these flow fields, but these techniques are often computationally intensive. Most fast response models currently in use are at a disadvantage in these cases as they are unable to correlate highly heterogeneous urban structures with the diagnostic parameterizations on which they are based. In this paper, a novel variant of the popular projection method for solving the Navier–Stokes equations has been developed and applied to produce fast and reasonably accurate parallel computational fluid dynamics (CFD) solutions for flow in complex urban areas. This model, called QUIC-CFD represents an intermediate balance between fast (on the order of minutes for a several block problem) and reasonably accurate solutions. This paper details the solution procedure and validates this model for various simple and complex urban geometries.     

A Bayesian hierarchical model for assessing the impact of human activity on nitrogen dioxide concentrations in Europe

Ambient concentrations of many pollutants are associated with emissions due to human activity, such as road transport and other combustion sources. In this paper we consider air pollution as a multi-level phenomenon on a continental scale within a Bayesian hierarchical model. We examine different scales of variation in pollution concentrations ranging from large scale transboundary effects to more localised effects which are directly related to human activity. Specifically, in the first stage of the model, we isolate underlying patterns in pollution concentrations due to global factors such as underlying climate and topography, which are modelled together with spatial structure. At this stage measurements from monitoring sites located within rural areas are used which, as far as possible, are chosen to reflect background concentrations. Having isolated these global effects, in the second stage we assess the effects of human activity on pollution in urban areas. The proposed model was applied to concentrations of nitrogen dioxide measured throughout the EU for which significant increases are found to be associated with human activity in urban areas. The approach proposed here provides valuable information that could be used in performing health impact assessments and to inform policy.     

Analysis and prediction of the influence of energy utilization on air quality in Beijing

This work evaluates the influence of energy consumption on the future air quality in Beijing, using 2000 as the base year and 2008 as the target year. It establishes the emission inventory of primary PM₁₀, SO₂ and NO_x related to energy utilization in eight areas of Beijing. The air quality model was adopted to simulate the temporal and spatial distribution of each pollutant concentration in the eight urban areas. Their emission, concentration distribution, and sectoral share responsibility rate were analyzed, and air quality in 2008 was predicted. The industrial sector contributed above 40% of primary PM₁₀ and SO₂ resulting from energy consumption, while vehicles accounted for about 65% of NO_x. According to the current policy and development trend, air quality in the eight urban areas could become better in 2008 when the average concentrations of primary PM₁₀, SO₂ and NO₂ related to energy utilization at each monitored site are predicted to be about 25, 50 and 51 μg/m³, respectively.     

应用GIS模拟城市大气污染物浓度分布

从点源大气污染扩散模型出发,借助GIS的栅格与数据库运算功能,结合自已设计的推算流程,对兰州市大气污染物SO2的空间分布情况进行了模拟。经检验,该方法能够较准确的反映出兰州大气污染物的空间分布特征,较应用实测值进行插值的方法简便,具有较好的应用前景。     

Impacts of methanol fuel on vehicular emissions: A review

● Methanol effectively reduces CO, HC, CO₂, PM, and PN emissions of gasoline vehicles. ● Elemental composition of methanol directly affects the reduction of emissions. ● Several physicochemical properties of methanol help reduce vehicle emissions. The transport sector is a significant energy consumer and a major contributor to urban air pollution. At present, the substitution of cleaner fuel is one feasible way to deal with the growing energy demand and environmental pollution. Methanol has been recognized as a good alternative to gasoline due to its good combustion performance. In the past decades, many studies have investigated exhaust emissions using methanol-gasoline blends. However, the conclusions derived from different studies vary significantly, and the explanations for the effects of methanol blending on exhaust emissions are also inconsistent. This review summarizes the characteristics of CO, HC, NO_x, CO₂, and particulate emissions from methanol-gasoline blended fuels and pure methanol fuel. CO, HC, CO₂, particle mass (PM), and particle number (PN) emissions decrease when methanol-blended fuel is used in place of gasoline fuel. NO_x emission either decreases or increases depending on the test conditions, i.e., methanol content. Furthermore, this review synthesizes the mechanisms by which methanol-blended fuel influences pollutant emissions. This review provides insight into the pollutant emissions from methanol-blended fuel, which will aid policymakers in making energy strategy decisions that take urban air pollution, climate change, and energy security into account.     

基于PLS1的哈尔滨市PM2.5与空气污染物相关性分析

以往对PM2.5的研究多集中在气象因子或单一空气污染物对PM2.5质量浓度变化的影响,未考虑多种空气污染物对PM2.5质量浓度的协同作用。通过哈尔滨市环保局发布的2014年1月份（共31 d）市区内主要空气污染物SO2、NO2、PM10、CO、O3、PM2.5的质量浓度数据,运用相关性分析、PLS1和通径分析方法,研究哈尔滨市区内主要空气污染物对PM2.5质量浓度变化的直接影响、通过其他空气污染物的间接影响及污染物之间的协同作用。结果表明,SO2、NO2、PM10、CO 与 PM2.5质量浓度显著性相关,O3与 PM2.5质量浓度相关性不显著,SO2、NO2、PM10、CO 之间存在严重的复相关性。依据相关性分析结果,建立了SO2、NO2、PM10、CO对PM2.5质量浓度的PSL1模型,模型的拟合优度r2为0.852,模型拟合良好。对所建立的模型进行通径分析,结果显示,SO2、NO2、PM10、CO对PM2.5质量浓度变化的直接作用分别为0.005、-0.142、-0.140、1.191,CO对PM2.5质量浓度变化的直接影响作用最大。SO2、NO2、PM10通过CO对PM2.5质量浓度变化的间接作用分别为0.706、1.011、1.118均大于它们对PM2.5质量浓度变化的直接作用。SO2、NO2、PM10、CO对PM2.5质量浓度变化的总决定系数为85.9%。CO是主要空气污染物中影响PM2.5质量浓度变化的主要因素,降低冬季煤炭供暖期CO的排放量,有利于提高空气环境质量,降低对人体的健康危害。     

Understand the local and regional contributions on air pollution from the view of human health impacts

• PM_2.5-related deaths were estimated to be 227 thousand in BTH & surrounding regions. • Local emissions contribute more to PM_2.5-related deaths than PM_2.5 concentration. • Local controls are underestimated if only considering its impacts on concentrations. • Rural residents suffer larger impacts of regional transport than urban residents. • Reducing regional transport benefits in mitigating environmental inequality. The source-receptor matrix of PM_2.5 concentration from local and regional sources in the Beijing-Tianjin-Hebei (BTH) and surrounding provinces has been created in previous studies. However, because the spatial distribution of concentration does not necessarily match with that of the population, such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM_2.5-related health impacts. To demonstrate that, we study the source-receptor matrix of the PM_2.5-related deaths instead, with inclusion of the spatial correlations between the concentrations and the population. The advanced source apportionment numerical model combined with the integrated exposure–response functions is used for BTH and surrounding regions in 2017. We observed that the relative contribution to PM_2.5-related deaths of local emissions was 0.75% to 20.77% larger than that of PM_2.5 concentrations. Such results address the importance of local emissions control for reducing health impacts of PM_2.5 particularly for local residents. Contribution of regional transport to PM_2.5-related deaths in rural area was 22% larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population. This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots. An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM_2.5 pollution thus mitigating the associated environmental inequality.     

Multiscale Plume Transport from the Collapse of the World Trade Center on September 11, 2001

The collapse of the world trade center (WTC) produced enhanced levels of airborne contaminants in New York City and nearby areas on September 11, 2001 through December, 2001. This catastrophic event revealed the vulnerability of the urban environment, and the inability of many existing air monitoring systems to operate efficiently in a crisis. The contaminants released circulated within the street canyons, but were also lifted above the urban canopy and transported over large distances, reflecting the fact that pollutant transport affects multiple scales, from single buildings through city blocks to mesoscales. In this study, ground-and space-based observations were combined with numerical weather forecast fields to initialize fine-scale numerical simulations. The effort is aimed at reconstructing pollutant dispersion from the WTC in New York City to surrounding areas, to provide means for eventually evaluating its effect on population and environment. Atmospheric dynamics were calculated with the multi-grid Regional Atmospheric Modeling System (RAMS), covering scales from 250 m to 300 km and contaminant transport was studied using the Hybrid Particle and Concentration Transport (HYPACT) model that accepts RAMS meteorological output. The RAMS/HYPACT results were tested against PM2.5 observations from the roofs of public schools in New York City (NYC), Landsat images, and Multi-angle Imaging SpectroRadiometer (MISR) retrievals. Calculations accurately reproduced locations and timing of PM2.5 peak aerosol concentrations, as well as plume directionality. By comparing calculated and observed concentrations, the effective magnitude of the aerosol source was estimated. The simulated pollutant distributions are being used to characterize levels of human exposure and associated environmental health impacts.     

A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions

Several reaction schemes, based on the conserved scalar theory, are implemented within a stochastic Lagrangian micromixing model to simulate the dispersion of reactive scalars in turbulent flows. In particular, the formulation of the reaction-dominated limit (RDL) reaction scheme is here extended to improve the model performance under non-homogeneous conditions (NHRDL scheme). The validation of the stochastic model is obtained by comparison with the available measurements of reactive pollutant concentrations in a grid-generated turbulent flow. This test case describes the dispersion of two atmospheric reactant species (NO and O₃) and their reaction product (NO₂) in an unbounded turbulent flow. Model inter-comparisons are also assessed, by considering the results of state-of-the-art models for pollutant dispersion. The present validation shows that RDL reaction scheme provides a systematic overestimation (relative error of ca. 85% around the centreline) in computing the local reactant consumption/production rate, whereas the NHRDL scheme drastically reduces this gap (relative error lower than 5% around the centreline). In terms of NO₂ production (or reactant consumption), neglecting concentration fluctuations determines overestimations of the product mean of around 100% and a NO₂ local production of one order of magnitude higher than the reference simulation. In terms of standard deviations, the concentration fluctuations of both the passive and reactive scalars are generally of the same order of magnitude or up to 1 or 2 orders of magnitudes higher than the corresponding ensemble mean values, except for the background reactant close to the plume edges. The study highlights the importance of modelling pollutant reactions depending on the instantaneous instead of the mean concentrations of the reactants, thus quantifying the role of the turbulent fluctuations of concentration, in terms of scalar statistics (mean, standard deviation, intensity of fluctuations, skewness and kurtosis of concentration, segregation coefficient, simulated reaction rate). This stochastic particle method represents an efficient numerical technique to solve the convection–diffusion equation for reactive scalars and involves several application fields: micro-scale air quality (urban and street-canyon scales), accidental releases, impact of odours, water quality and fluid flow industrial processes (e.g. combustion).     

Development of a rotorcraft dust-emission parameterization using a CFD model

Flights of rotorcraft over the desert floor can result in significant entrainment of particulate matter into the atmospheric boundary layer. Continuous or widespread operation can lead to local and regional impacts on visibility and air quality. To account for this pollutant source in air quality models, a parameterization scheme is needed that addresses the complex vertical distribution of dust ejected from the rotorcraft wake into the atmospheric surface layer. A method to parameterize the wind and turbulence fields and shear stress at the ground is proposed here utilizing computational fluid dynamics and a parameterized rotor model. Measurements taken from a full scale experiment of rotorcraft flight near the surface are compared to the simulation results in a qualitative manner. The simulation is shown to adequately predict the forward detachment length of the induced ground jet compared to the measured detachment lengths. However, the simulated ground vortex widths and vorticity deviate substantially from the measured values under a range of flight speeds. Results show that the method may be applicable for air quality modeling assuming slow airspeeds of the rotorcraft, with advance ratios of 0.005–0.02.     

Comparison of atmospheric modelling systems simulating the flow,turbulence and dispersion at the microscale within obstacles

Three different modelling techniques to simulate the pollutant dispersion in the atmosphere at the microscale and in presence of obstacles are evaluated and compared. The Eulerian and Lagrangian approaches are discussed, using RAMS6.0 and MicroSpray models respectively. Both prognostic and diagnostic modelling systems are considered for the meteorology as input to the Lagrangian model, their differences and performances are investigated. An experiment from the Mock Urban Setting Test field campaign observed dataset, measured within an idealized urban roughness, is used as reference for the comparison. A case in neutral conditions was chosen among the available ones. The predicted mean flow, turbulence and concentration fields are analysed on the basis of the observed data. The performances of the different modelling approaches are compared and their specific characteristics are addressed. Given the same flow and turbulence input fields, the quality of the Lagrangian particle model is found to be overall comparable to the full-Eulerian approach. The diagnostic approach for the meteorology shows a worse agreement with observations than the prognostic approach but still providing, in a much shorter simulation time, fields that are suitable and reliable for driving the dispersion model.     

Spatiotemporal multimedia emission inventory for polycyclic aromatic hydrocarbons near petroleum production plants in China based on a 10′ × 10′ grid

A spatiotemporal model was developed to investigate emissions of polycyclic aromatic hydrocarbons (PAHs) in Daqing, a Chinese city with large petroleum industry plants. The model was based on land-use types determined on a 10′?×?10′ grid. A geographic information system and regression analyses were used to characterise spatial and temporal variations in PAH emissions into multiple environmental media. The simulated results were validated using previously published experimental data, and the model was found to function well. PAH emissions to the atmosphere, soil, and surface water between 1998 and 2013 were estimated. The results indicated that PAH emissions to the atmosphere increased but PAH emissions to the soil and surface water decreased over the study period. PAH emissions to the atmosphere were markedly higher in winter than in summer. PAH emissions were concentrated in urban areas and areas near petroleum production plants, indicating that PAH emissions were closely related to industrial activities. The results will support research into the migration and transformation of PAHs and human health and ecological risk assessments. The results may also be useful for developing policies for controlling PAH pollution and managing risks associated with PAHs.     

南京城市土壤重金属含量及空间分布特征

研究了南京城市土壤重金属含量、来源及空间分布特征。结果表明,南京城市土壤中V、Mn、Co、Ni、Cr污染不明显,但受到了不同程度的Cu、Pb、Zn、Sb、Hg、Cd污染,其中Hg污染比较严重。V、Mn、Co、Ni、Cr含量之间均呈极显著正相父;Cu、Pb、Zn、Sb、Hg、Cd含量之间也均呈极显著正相关。南京城市土壤V、Mn、Co、Ni、Cr主要继承了原土物质;Hg、Cd、Pb主要来源于城市燃煤、机动车尾气及工厂排放粉尘;Sb主要来源于机动车尾气和工厂排放粉尘。南京城市土壤Hg、Cd、Pb、Sb含量空间分布规律非常相似,均表现为外围向市中心有逐渐增加的趋势,并且在新街口—鼓楼、梅山硫铁矿形成异常高值的岛状、环状区域。     

A GIS-based approach to spatio-temporal analysis of environmental pollution in urban areas: A case study of Prague's environment extended by LIDAR data

Environmental pollution of urban areas is one of key factors that state authorities and local agencies have to consider in the decision-making process. To find a compromise among many criteria, spatial analysis extended by geostatistical methods and dynamic models has to be carried out. In this case, spatial analysis includes processing of a wide range of air, water and soil pollution data and possibly noise assessment and waste management data. Other spatial inputs consist of data from remote sensing and GPS field measurements. Integration and spatial data management are carried out within the framework of a geographic information system (GIS). From a modeling point of view, GIS is used mainly for the preprocessing and postprocessing of data to be displayed in digital map layers and visualized in 3D scenes. Moreover, for preprocessing and postprocessing, deterministic and geostatistical methods (IDW, ordinary kriging) are used for spatial interpolation; geoprocessing and raster algebra are used in multi-criteria evaluation and risk assessment methods. GIS is also used as a platform for spatio-temporal analyses or for building relationships between the GIS database and stand-alone modeling tools. A case study is presented illustrating the application of spatial analysis to the urban areas of Prague. This involved incorporating environmental data from monitoring networks and field measurements into digital map layers. Extra data inputs were used to represent the 3D concentration fields of air pollutants (ozone, NO₂) measured by differential absorption LIDAR. ArcGIS was used to provide spatial data management and analysis, extended by modeling tools developed internally in the ArcObjects environment and external modules developed with MapObjects. Ordinary kriging methods were employed to predict ozone concentrations in selected 3D locations together with estimates of variability. Higher ozone concentrations were found above crossroads with their heavy traffic than above the surrounding areas. Ozone concentrations also varied with height above the digital elevation model. Processed data, spatial analysis and models are integrated within the framework of the GIS project, providing an approach that state and local authorities can use to address environmental protection issues.     

杭州城市热岛空间分布及时域-频域多尺度变化特征

利用杭州20个自动气象站逐时数据计算2006年四季各站平均热岛强度,用薄盘样条函数法研究杭州城市热岛的空间变化,发现:夏秋季时较强,而春冬季强度较弱;总体趋势是杭州市丰体城区最大,向外辐散,逐渐减弱.利用2006年2月～2007年2月逐时气象数据,结合Morlet小波变换方法分析了杭州热岛周期变化特征,发现:其在频域上具有多尺度的周期振荡,尺度主要是24 h(日)、168 h(周)和1 490 h(2月).以日为周期的热岛强度与局地气候系统、地面长波辐射、近地层热量交换、人为热的日周期变化有关;而以周为周期的热岛强度变化成因主要与人类活动及城市大气污染物排放的"周末效应"有显著的关系;以2个月为周期的变化特征与一些较大尺度的自然变化相关.结果表明,杭州城市热岛时空变化是天气系统、地面长波辐射、下垫面、大气污染、人为热、人类活动、近地层热量交换等共同作用的结果.     

The effect of outdoor air pollutants and greenness on allergic rhinitis incidence rates: a cross-sectional study in Seoul,Korea

Air pollution poses a serious threat to human health in Asia. This study analyzes the association of air pollutants and greenness with incidence rates of allergic rhinitis in Seoul at the administrative district level to gain insight into district-level urban policies to improve public health. A spatial regression model is constructed to investigate the correlation between allergic rhinitis incidence rates and five air pollutants measured at 128 air pollution monitoring stations around Seoul: sulfur dioxide (SO₂), particulate matter less than 10 μm (PM₁₀), ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The allergic rhinitis incidence data are derived from the National Health Insurance Service’s database that includes the number of allergic rhinitis-related clinic visits by the patients over 20 years of age and living in Seoul. A kriging geostatistical interpolation was used to estimate average air pollution level of 423 administrative districts. To assess pollen concentrations that can affect allergic rhinitis, the average normalized difference vegetation index (NDVI) is measured based on the urban greenness. The model, controlling for built environment and socio-economic attributes, identifies the possibility of a weak association between allergic rhinitis incidence rates and carbon monoxide levels. The NDVI value is negatively correlated with allergic rhinitis incidence rates, implying a complicated aspect in relation to the effect of urban greenness.     

武汉市城区大气PM2．5的碳组分与源解析

大气细颗粒物（PM2．5）和碳组分（OC,EC）是影响大气能见度、气候变化以及人体健康的重要污染物,研究大气颗粒物及其中碳组分的污染特征及各类典型污染源对大气细颗粒物及碳组分的贡献,对于认识区域和城市大气污染状况,控制细颗粒物的污染,具有重要意义。2011年7月至2012年2月,利用大流量PM2．5采样器采集武汉市大气细颗粒物样品并对其碳组分进行测定。武汉市城区大气中PM215、OC和EC的质量浓度平均值分别为（127±48．7）、（19．4±10．5）和（2．9±1．48）μg·m-3。其PM2．5的浓度处于我国主要城市的中等偏高水平,而OC、EC的浓度则属中等偏下水平,但均高于国外城市。武汉市大气PM2,质量浓度的季节性变化呈现出秋季〉冬季〉夏季的趋势,是气象因素和污染源排放综合影响的结果。OC浓度和EC浓度具有较好的相关性（r2=0．69）,表明二者存在来源联系。OC／EC的比值为6．7,指示武汉市大气中OC和EC的来源受汽车尾气排放和生物质燃烧的共同影响。SOA的平均质量浓度值为12．5μg·m-3约占PM2．5平均质量浓度的9．8％,表明SOA对武汉市城区大气PM2．5具有重要贡献。结合PM2．5所含的水溶性离子、微量元素组成,利用正矩阵因子分析（PMF）模型对武汉市城区大气PM2．5来源进行解析,结果表明,其主要来源及贡献率分别为机动车源（27．1％）、二次硫酸盐和硝酸盐（26．8％）、工厂排放（26．4％）和生物质燃烧（19．6％）。     

A Multimedia Chemical Fate Model with Time-Dependent Air-Water Transfer Rates

A multimedia model for the temporal evolution of the concentration of chemical species in a water basin and its bottom sediment layer has been tested with time-dependent air-water transfer rates varying with the meteorological conditions over the basin. The multimedia model uses the chemical fugacity approach in a system of two ordinary differential equations for the chemical species partition in the two mentioned media, with transfer through the sediment-water and the air-water interfaces. The air-water transfer rates are estimated by a micrometeorological preprocessor. A scenario in which known concentrations in air of a soluble pollutant (benzene) induce water and sediment pollution is tested on both synthetic (MonteCarlo-simulated) and real series of meteorological data. It is found that the use of time-dependent transfer coefficients affects not only the relaxation time, but also the long term concentration of the pollutant in water and sediment, that differs between 10 and 40% in the examined cases when compared with the same multimedia model using average constant transfer rates as usual. This is shown to be due to the statistical correlations between meteorological parameters and air pollutant concentrations, which stresses the advantages of a time-dependent estimation of the transfer coefficients. Correction terms are proposed to take into account the correlation effects when a constant parameters multimedia model is used.     

A building-based data capture and data mining technique for air quality assessment

Recently, a building-based air quality model system which can predict air quality in front of individual buildings along both sides of a road has been developed. Using the Macau Peninsula as a case study, this paper shows the advantages of building-based model system in data capture and data mining. Compared with the traditional grid-based model systems with input/output spatial resolutions of 1–2 km, the building-based approach can extract the street configuration and traffic data building by building and therefore, can capture the complex spatial variation of traffic emission, urban geometry, and air pollution. The non-homogeneous distribution of air pollution in the Macau Peninsula was modeled in a high-spatial resolution of 319 receptors·km^-2. The spatial relationship among air quality, traffic flow, and urban geometry in the historic urban area is investigated. The study shows that the building-based approach may open an innovative methodology in data mining of urban spatial data for environmental assessment. The results are particularly useful to urban planners when they need to consider the influences of urban form on street environment.