Typical building arrangements for urban air pollution modelling

Typical building arrangements along urban roads and their parameters were determined for three cities in the south-western part of Germany. Some examples of the dispersion of vehicle emissions within idealized street canyons show how different building parameters influence the concentration of air pollutants.     

A comparison study of three urban air pollution models

The predictions of three urban air pollution models with varying degrees of mathematical and computational complexities are compared against the hourly SO₂ ground-level concentrations observed on 10 winter nights of the RAPS experiment in St. Louis. The emphasis in this study is on the prediction of urban area source concentrations. Statistics for the paired comparison of predictions of each model with the observations are presented. The RAM and the ATDL model with stable diffusion coefficients overestimated the observed night-time concentrations. The results show that the performance of the ATDL model with near-neutral diffusion coefficients is comparable to the more sophisticated 3-D grid numerical model.     

Source contributions to the mutagenicity of urban particulate air pollution

Using organic compounds as tracers, a chemical mass balance model was employed to investigate the relationship between the mutagenicity of the urban organic aerosol sources and the mutagenicity of the atmospheric samples. The fine particle organic mass concentration present in the 1993 annual average Los Angeles-area composite sample was apportioned among eight emission source types. The largest source contributions to fine particulate organic compound mass concentration were identified as smoke from meat cooking, diesel-powered vehicle exhaust, wood smoke, and paved road dust. However, the largest source contributions to the mutagenicity of the atmospheric sample were natural gas combustion and diesel-powered vehicles. In both the human cell and bacterial assay systems, the combined mutagenicity of the composite of primary source effluents predicted to be present in the atmosphere was statistically indistinguishable from the mutagenicity of the actual atmospheric sample composite. Known primary emissions sources appear to be capable of emitting mutagenic organic matter to the urban atmosphere in amounts sufficient to account for the observed mutagenicity of the ambient samples. The error bounds on this analysis, however, are wide enough to admit to the possible importance of additional mutagenic organics that are formed by atmospheric reaction (e.g., 2-nitrofluoranthene has been identified as an important human cell mutagen in the atmospheric composite studied here, accounting for approximately 1% of the total sample mutagenic potency).     

Numerical simulation of air pollution in urban areas: model performance

The numerical model developed in the first part of this investigation is applied to assess the behavior of sulfur dioxide and sulfate concentration distributions in an urban area using the St Louis Regional Air Pollution Study (RAPS) data. Statistical techniques chosen to determine the accuracy and uncertainty associated with the numerical model results include paired analysis and resampling analysis. The results of the numerical model are also compared with those of RAM, a Gaussian plume model. Finally, the behavior of point and area emission sources in an urban area is assessed to provide an insight into the complex interrelationships between the emissions and meteorological conditions which determine the distribution of ground level concentrations.     

Spatially differentiated and source-specific population exposure to ambient urban air pollution

Models assessing exposure to air pollution often focus on macro-scale estimates of exposure to all types of sources for a particular pollutant across an urban study area. While results based on these models may aid policy makers in identifying larger areas of elevated exposure risk, they often do not differentiate the proportion of population exposure attributable to different polluting sources (e.g. traffic or industrial). In this paper, we introduce a population exposure modeling system that integrates air dispersion modeling, Geographic Information Systems (GIS), and population exposure techniques to spatially characterize a source-specific exposure to ambient air pollution for an entire urban population at a fine geographical scale. By area, total population exposure in Dallas County in 2000 was more attributable to vehicle polluting sources than industrial polluting sources at all levels of exposure. Population exposure was moderately correlated with vehicle sources (r = 0.440, p < 0.001) and weakly with industrial sources (r = 0.069, p = 0.004). Population density was strongly correlated with total exposure (r = 0.896, p < 0.001) but was not significantly correlated with individual or combined sources. The results of this study indicate that air quality assessments must incorporate more than industrial or vehicle polluting sources-based population exposure values alone, but should consider multiple sources. The population exposure modeling system proposed in this study shows promise for use by municipal authorities, policy makers, and epidemiologists in evaluating and controlling the quality of the air in the process of urban planning and mitigation measures.     

Numerical simulation of air pollution in urban areas: Model development

A three-dimensional, grid-based numerical air pollution model for the estimation of air pollutant concentrations in an urban area is developed. Based on the continuity equation, the modeling system incorporates the combined influences of advective transport, turbulent diffusion, chemical transformation, source emissions and surface removal of air contaminants. Recent developments in plume rise and plume penetration processes, objective wind field analysis procedures and numerical solution techniques incorporated into the model are described.     

Analysis of the air pollution climate at a central urban background site

Measurements of air pollutants from a background site in central London are analysed. These comprise hourly data for CO, NO, NO₂, O₃, SO₂ and PM₁₀ from 1996 to 2008 and particle number count from 2001 to 2008. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and autocorrelation and cross-correlation functions. CO, NO and NO₂ show a typical traffic-associated pattern with two daily peaks and lesser concentrations at the weekend. Particle number count and PM₁₀ show a similar cycle, but with smaller amplitude. Ozone has an annual cycle with a maximum in May, influenced by the spring maximum in background ozone, but the diurnal and weekly cycles are dominated by losses through reaction with nitric oxide. Particle number count shows a minimum corresponding with maximum air temperatures in August, whereas the CO, NO NO₂ and SO₂ show a minimum in June/July. There is a lower particle count to NO_x ratio at the background site compared to a central London kerbside site (Marylebone Road) and a seasonal pattern in particle count to NO_x and PM₁₀ ratios consistent with loss of nanoparticles by evaporation during atmospheric transport. Sulphur dioxide peaks in the morning in summer, but at midday in winter consistent with emissions from elevated sources mixing down from aloft as the diurnal mixed layer deepens. Implications for epidemiological studies of air quality and health are discussed. Sulphur dioxide, carbon monoxide, nitric oxide and nitrogen dioxide show clear downward trends over the measurement period, PM₁₀ declines initially before levels stabilised, and ozone concentrations increased.     

Economic impacts of urban air pollution: valuation for Mumbai, India

Urban air pollution is on the rise in many cities of the world. There are associated health impacts that affect urban residents, especially the poor. By doing economic valuation, it is possible to draw the attention of citizens, policy-makers and, of course, researchers to the extent of damage and the value of it. In this paper, such a valuation is done using time-series data for the suburb of Mumbai called Chembur and cross-sectional data for several wards. We value mortality and morbidity from air pollution using the above data. It is shown that the pollution in Mumbai can lead to high health costs. In general the average cost amounts 0.26% of income due to highly subsidised treatment and poverty. However, 5% of patients who suffer severe attacks may pay as much as much as 19% of their income. Workdays lost are of equal importance to health expenditures. Distributional aspects of the damage are such that children and senior citizens are affected most.     

Intercomparison of nocturnal mixing height estimate methods for urban air pollution modelling

One of the most important meteorological input parameters for three-dimensional photochemical air pollution models is the mixing height h, which has a strong influence on the shape and intensity of the vertical diffusivity K_z and, as a consequence, on ground-level air concentrations of primary and secondary pollutants. A number of indirect algorithms for the estimate of h in nocturnal, stable conditions, when the mixing is dominated by mechanical turbulence, are reviewed and compared with mixing heights derived from wind (SODAR) and temperature (RASS) profiles measured in the Milan urban area during spring and summer 1996. Mixing heights derived from temperature soundings correlate positively with those derived from wind soundings only when a stable layer is superimposed to a quasi-adiabatic layer, while the correlation is very weak in the presence of a ground-based inversion. In general, indirect algorithms perform very poorly if compared with RASS-based estimates, and reasonably well if compared with SODAR-based estimates. Among the others, Benkley and Schulman (1979, Journal of Applied Meteorology 18, 772–780) method, which makes use of wind speed observed at 10 m height, and Nieuwstadt (1984, Boundary-Layer Meteorology 30, 31–55), which makes use of friction velocity and Monin–Obukhov length, give the best results.     

Recent trends in sulphur dioxide air pollution in the Sheffield urban region

A study has been made of changes in the levels of SO₂ in the Sheffield region from 1968 to 1975. There was a marked decrease in the levels since 1970 during both winter and summer seasons. Although a series of mild winters could have contributed to the reduction in SO₂ the dominant influence appears to be the substantial increase in the use of sulphur-free fuels (natural gas and purified coke-oven gas) in industry; emissions from a local power station appear to bear no clear relationship to the SO₂ trend changes. The lower SO₂ levels have allowed the identification of comparatively high levels which may have resulted from the import of pollutants from more distant sources.     

重庆主城区大气重污染形势的激光雷达探测与分析

2013年1月12日-26日,利用大气超级站ALS300型激光雷达对重庆主城区大气进行了连续探测,分析了重污染形势期间的大气扩散条件及大气颗粒物时空分布等探测结果。分析表明,大气层结持续稳定,扩散条件差使得大气颗粒物浓度居高不下,大气能见度持续恶化;大气重污染期间PBL高度较低,平均为320～350m;大气颗粒物污染带处于100～400m高度范围;全国范围内异常的大气环流形势和重庆主城区独特的地形、气候特征是造成持续大气重污染形势的原因。     

Rapid urban growth,land-use changes and air pollution in Santiago,Chile

This paper is a contribution to the understanding of the topoclimatic and environmental geography of the basin where Santiago — one of the most polluted Latin American city – is located. In the first part, land-use change is analysed looking at the climatic transformation caused by the rapid transit from natural semiarid surface to urban areas. In the second part, seasonal weather and daily cycles of slope winds and the available ventilation are described trying to relate those patterns with the spatial distribution of air pollution. A combination of meteorological, geographical and cultural factors explain extreme air pollution events: meteorologically, Santiago is under permanent subsidence inversion layers. Geographically, the city is located in a closed basin surrounded by mountains. Culturally, the urban area has the highest population concentration (40% of the national total), industries (near 70% of the total) and vehicles, which are the main sources of smog. The urban and suburban transport system is based on a large number of buses (diesel) and private cars, both experiencing a rapid growth from the past few years. The city and specially the transport system generates high emissions of pollutant, but the natural semiarid deforested soils and slopes are also important sources. The local wind system can explain the differential spatial distribution on the concentration of air pollutants in the city and its periphery. In winter (rain season) concentrations of particulate matter are higher at the centre and the SW part of the city. The andean piedmont area (E part of the city) shows minimum values, suggesting major ventilation effects of slope and valley winds. Ozone exceeds air quality standards in summer (dry season) at all sites in the centre and periphery. However, the O₃-concentrations are higher on preferred residential areas located at the piedmont area (E part of the city), suggesting air pollution transport effects. Currently, there is no consideration of these local climatic features in the process of urban planning.