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.     

Planning for the monitoring of pollutants from non‐stationary combustion sources†

The most important constituents of traffic exhaust are carbon monoxide, nitrogen oxides, volatile organic compounds, polycyclic hydrocarbons and lead. Satisfactory analytical methods are available for measuring these compounds, but the required expenditure in their application to air pollution studies is quite different. Due to correlations between the concentrations of several exhaust components in road air conclusions regarding the expected level of some substances can be drawn by measurement of another emitted compound. But the selection of indicator compounds must be made under the aspect of the source‐specific relationship of emitted substances. The temporal and spatial distribution of air pollutants in street air is affected by traffic emissions more than by meteorological conditions. “Fingerprints”; of typical organic gaseous components of traffic exhaust also were found in residential areas.     

The Modelling of Turbulence from Traffic in Urban Dispersion Models — Part II: Evaluation Against Laboratory and Full-Scale Concentration Measurements in Street Canyons

The paper addresses the problem of the parameterisation of traffic induced turbulent motion in urban dispersion models. Results from a variety of full-scale and wind-tunnel studies are analysed and interpreted within a modelling framework based on scaling considerations. The combined effects of traffic and wind induced dispersive motions are quantified for different traffic situations (variable traffic densities, vehicle velocities and vehicle types) and incorporated into the developed parameterisations. A new dispersive velocity scale is formulated and recommendations regarding its application in urban dispersion models are given. The necessity of accounting for traffic induced air motions in predictions of street-canyon pollution levels is demonstrated. Further research is needed to verify the empirical constants in the proposed parameterisations and to generalize the developed approach for a broader range of urban building configurations, meteorological conditions, and traffic situations.     

天津城市道路灰尘重金属污染特征

以天津城市道路灰尘重金属为研究对象,按照环线分布将天津市中心城区划分为内环以内、内环-中环、中环以外3个区域,总共设置93个采样点。对表层灰尘进行采样收集,预处理后测定样品的理化性质,采用原子吸收光谱仪测定道路灰尘中重金属Cd、Cr、Cu、Ni和Pb的含量,进而分析天津市道路灰尘重金属的含量水平,运用ArcGIS软件中的地统计分析方法内插得出其空间分布特征,通过Pearson相关分析和主成分分析判析重金属来源。研究结果表明：道路灰尘颗粒粒径表现为双峰,主峰对应粒径较小,且为非正态分布,大量小粒径颗粒的存在使重金属含量增高;市区和各环区有机质变异系数较大,道路灰尘中有机质的空间分布差异较大,因而人为因素影响广泛;市区道路灰尘中重金属 Cd、Cr、Cu、Ni 和 Pb的平均含量依次为0.99、121.41、100.62、43.35和61.48 mg·kg-1,分别为天津土壤环境背景值的11.00倍、1.44倍、3.49倍、1.30倍和2.93倍;Cd、Cr和Cu的空间分布差异较大,Ni和Pb的空间分布差异较小;Pearson相关分析表明Pb-有机质（P＜0.05）, Cu-Ni（P＜0.01）和Cr-Cu（P＜0.05）之间存在显著正相关关系,主成分分析人为因素的积累贡献率为33.050%,自然因素的积累贡献率为57.315%,因此得出重金属受人为因素影响较大,交通尾气排放和工业污染为天津道路灰尘重金属污染的重要来源,且以多因子复合影响为主。     

天津市环境空气中铅（Pb）的污染

本文统计分析了１９９４￣１９９６年天津市环境空气及交通环境中铅的浓度值，分析了天津市环境空气及交通环境中锅污染的程度、变化趋势、污染来源。由此说明天津市出现“尾气型”污染的迹象。为此，务必加大力度对机动车尾气排放的监测和管理，这对降低污染，改善天津市环境空气质量具有一定的现实意义。     

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.     

北京市地面街尘与径流中重金属的污染特征（Characteristics of Heavy Metals in Street Dusts and Urban Runoff in Beijing）

街尘作为城市各种污染物的载体和地表径流污染物的主要来源对水环境的影响日益受到关注.论文分析了北京市城区街尘与地表径流中重金属浓度和颗粒的粒径分布.结果表明:不同城市土地利用类型对街尘和径流中的重金属含量、颗粒粒径分布具有重要影响.在商业区、主要道路、住宅区、城中村4种土地利用类型中,街尘重金属浓度和地面单位面积重金属质量均以主要道路最高;径流重金属浓度由高到低顺序依次为:主要道路>城中村>居民区;主要道路和商业区街尘颗粒中细粒径占的比例较高,在全部土地利用类型的径流水样中颗粒物粒径分布差别不大;随着街尘中颗粒物粒径的减小,重金属浓度增加;街尘中小于149μm的颗粒物质量百分比和重金属浓度均较高,且在径流中这个粒径段的颗粒物含量也高,体积比达80%以上.建议在今后的城市街尘面源污染控制中应特别关注土地利用类型和街尘粒径的影响.     

The promise of Beijing: Evaluating the impact of the 2008 Olympic Games on air quality

To prepare for the 2008 Olympic Games, China adopted a number of radical measures to improve air quality. Using the officially reported air pollution index (API) from 2000 to 2009, we show that these measures improved the API of Beijing during and a little after the Games, but a significant proportion of the effect faded away by October 2009. For comparison, we also analyze an objective and indirect measure of air quality at a high spatial resolution – aerosol optimal depth (AOD), derived using the data from NASA satellites. The AOD analysis confirms the real but temporary improvement in air quality, it also shows a significant correlation between air quality improvement and the timing and location of plant closure and traffic control. These results suggest that it is possible to achieve real environmental improvement via stringent policy interventions, but for how long the effects of these interventions will last will largely depend on the continuation of the interventions.     

Does subway expansion improve air quality?

Major cities in China and many other fast-growing economies are expanding their subway systems in order to address worsening air pollution and traffic congestion. This paper quantifies the impact of subway expansion on air quality by leveraging fine-scale air quality data and the rapid build-out of 14 new subway lines and 252 stations in Beijing from 2008 to 2016. Our main empirical framework examines how the density of the subway network affects air quality across different locations in the city during this period. To address the potential endogenous location of subway stations, we construct an instrument based on historical subway planning, long before air pollution and traffic congestion were of concern. Our analysis shows that an increase in subway density by one standard deviation improves air quality by two percent and the result is robust to a variety of alternative specifications including the distance-based difference-in-differences method. The total discounted health benefit during a 20-year period from reduced mortality and morbidity as a result of 14 new subway lines amounts to $1.0–3.1 billion, or only 1.4–4.4 percent of the total construction and operating cost.     

Evaluation of numerical simulations of CO2 transport in a city block with field measurements

Studying urban air-transport phenomena is highly complex, because of the heterogenous flow patterns that can arise. The main reason for these is the variable topology of urban areas, however, there is a large number of influencing variables such as meteorological conditions (e.g., wind situation, temperature) and anthropogenic factors such as traffic emissions. During a one-year CO₂ measurement campaign in the city of Basel, Switzerland, steep CO₂ gradients were measured around a large building. The concentration differences showed a strong dependency on the local flow regimes. Analysis of the field data alone did not provide a complete explanation for the mechanisms underlying the observed phenomena. The key numerical parameters were defined and the influence of turbulent kinetic energy dependency on the time interval for the Reynolds decomposition was studied. A Reynolds-Average Navier-Stokes Computational Fluid Dynamics (CFD) approach was applied in the study area and the CO₂ concentrations were simulated for six significant meteorological situations and compared to the measured data. Two flow regimes dependent on the wind situation, which either enhanced or suppressed the concentration of CO₂ in the street canyon, were identified. The enhancement of CO₂ in the street canyon led to a large difference in CO₂ concentration between the backyard- and street-sides of a building forming the one wall of the canyon. The specific characteristics of the flow patterns led to the identification of the processes determining the observed differences in CO₂ concentrations. The combined analysis of measurement and modeling showed the importance of reliable field measurements and CFD simulations with a high spatial resolution to assess transport mechanisms in urban areas.     

The investigation of metal concentrations in street dust samples in Aqaba city,Jordan

The concentrations of metals (Fe, Zn, Cu, Cr, Pb, Cd, Ni, Mn and Co) in 140 street dust samples were collected from Aqaba city, Jordan. These samples were determined using flame atomic absorption spectrophotometry after digestion with aqua regia. The highest levels of metal concentrations were found in the samples from heavy traffic. While the lowest levels of metal ions were noted in the street dust samples from hospital and health centers and school gardens. The results of this study were compared with several cities around the world. The levels of the metal concentrations found were generally below the mean world-wide values of street dust samples. Metal values in urban street dust samples were several times higher than the control levels. The statistical analyses were applied to the data matrix to determine the analytical results and to identify the possible source of pollution in the studied area. Correlations between the metal concentrations of the street dust samples were obtained. Factor analysis showed that the area was mainly influenced by three sources, namely lithogenic, traffic, and industrial.     

Numerical simulations of the effect of building configurations and wind direction on fine particulate matters dispersion in a street canyon

To explore the effect of traffic emissions on air quality within street canyon, the wind flow and pollutant dispersion distribution in urban street canyons of different H/W, building gap and wind direction are studied and discussed by 3D computational fluid dynamics simulations. The largest PM_2.5 concentrations are 46.4, 37.5, 28.4 µg/m³ when x = ? 88, ? 19.3, ? 19.3 m in 1.5 m above the ground level and the ratio of H/W is 1:1, 1:2 and 2:1, respectively. The flow around the top of the building and clearance flow between the buildings in street canyon influence by different H/W, which affected the diffusion of fine particulate matters. The largest PM_2.5 concentrations are 88.1, 31.6 and 33.7 µg/m³ when x = 148.0, ? 92.3 and ? 186.7 m above the ground level of 1.5 m height and the building gap of 0, 20 and 40%, respectively. The air flows are cut by the clearance in the street canyons, and present the segmental characteristics. The largest PM_2.5 concentrations are 10.6, 11.2 and 16.0 µg/m³ when x = 165.3 m, x = 58.0 and 1.5 m above the ground level of 1.5 m height and wind direction of the parallel to the street, perpendicular to the street and southwest, respectively. Modelled PM_2.5 concentrations are basic agreement with measured PM_2.5 concentrations for southwest wind direction. These results can help analyze the difussion of PM_2.5 concentration in street canyons and urban planning.

     

On spline-based approaches to spatial linear regression for geostatistical data

For spatial linear regression, the traditional approach to capture spatial dependence is to use a parametric linear mixed-effects model. Spline surfaces can be used as an alternative to capture spatial variability, giving rise to a semiparametric method that does not require the specification of a parametric covariance structure. The spline component in such a semiparametric method, however, impacts the estimation of the regression coefficients. In this paper, we investigate such an impact in spatial linear regression with spline-based spatial effects. Statistical properties of the regression coefficient estimators are established under the model assumptions of the traditional spatial linear regression. Further, we examine the empirical properties of the regression coefficient estimators under spatial confounding via a simulation study. A data example in precision agriculture research regarding soybean yield in relation to field conditions is presented for illustration.     

Spatiotemporal modeling of irregularly spaced aerosol optical depth data

Many advancements have been introduced to tackle spatial and temporal structures in data. When the spatial and/or temporal domains are relatively large, assumptions must be made to account for the sheer size of the data. The large data size, coupled with realities that come with observational data, make it difficult for all of these assumptions to be met. In particular, air quality data are very sparse across geographic space and time, due to a limited air pollution monitoring network. These “missing” values make it difficult to incorporate most dimension reduction techniques developed for high-dimensional spatiotemporal data. This article examines aerosol optical depth (AOD), an indirect measure of radiative forcing, and air quality. The spatiotemporal distribution of AOD can be influenced by both natural (e.g., meteorological conditions) and anthropogenic factors (e.g., emission from industries and transport). After accounting for natural factors influencing AOD, we examine the spatiotemporal relationship in the remaining human influenced portion of AOD. The presented data cover a portion of India surrounding New Delhi from 2000–2006. The proposed method is demonstrated showing how it can handle the large spatiotemporal structure containing so much missing data for both meteorologic conditions and AOD over time and space.     

Understanding the major drivers for implementation of municipal sustainable policies in underground space

Because of the expanding population in our cities with its demands for more diversified services, we cannot afford a piecemeal type of urban underground growth. Utilization of the urban street system for buried utilities has a serious adverse effect on other street functions because of the continuing necessity to perform excavations for the repair of existing lines and the installation of new ones. The excavations not only are a serious cause of traffic delay and congestion but also create noise and aesthetic disturbances, and result in excessive street maintenance requirements and in shortened overall street life. Consider the enhancing effects in quietness on abutting properties and users of the street, and the benefits become very great. Unfortunately, the lack of data and the difficulty in quantifying the intangibles have made it impossible to arrive at a reasonably accurate figure of overall negative impact on the urban environment of street cuts. However, if drivers are sufficiently strong to merit the use of utility tunnels, then sustainable municipal policies improving living quality will be implemented.     

城市街道汽车污染的多元回归分析

本文以沈阳市为对象，详细论述了城市街道分类、监测点位布置、汽车污染系统调查及污染规律分析。根据现有实测数据，重点进行了汽车污染的多元回归分析，并提出了城市街道汽车污染的防治途径。     

Upstream Turbulence Effect on Pollution Dispersion

Experiments have been carried out to investigate turbulence at and above roof-level in an urban environment, and to predict the behaviour of street pollution from experiments using dye dispersion, for different roughness conditions and bed geometries. The flow in the boundary layer above an idealised urban environment has been simulated in a laboratory water flume. Comparisons have been made for the same model street canyon with and without the presence of upstream roughness. In the tests reported here, model street canyons were aligned perpendicular to the flow direction, and velocity measurements made within and above the model street canyons using a laser Doppler velocimeter (LDV). Flow visualisation techniques have also been used to confirm the gross flow features from streak images. Turbulence generated from the upstream roughness has a significant effect on the turbulence production and dispersion behaviour of the dye simulating pollution in street canyons.     

Influences of traffic on Pb,Cu and Zn concentrations in roadside soils of an urban park in Dublin,Ireland

Soils in the vicinity of roads are recipients of contaminants from traffic emissions. In order to obtain a better understanding of the impacts of traffic on soils, a total of 225 surface soil samples were collected from an urban park (Phoenix Park, Dublin, Ireland) in a grid system. Metal (Pb, Cu and Zn) concentrations were determined using a portable X-ray fluorescence analyzer. Strong spatial variations for the concentrations of Pb, Cu and Zn were observed. The spatial distribution maps created using geographical information system techniques revealed elevated metal concentrations close to the main traffic route in the park. The relationships between the accumulation of Pb, Cu and Zn in the roadside soils and the distance from the road were well fitted with an exponential model. Elevated metal concentrations from traffic pollution extended to a distance of approximately 40 m from the roadside. The results of this study provide useful information for the management of urban parks particularly in relation to policies aimed at reducing the impact of traffic related pollution on soils.