Air pollution in cities

Air quality in cities is the result of a complex interaction between natural and anthropogenic environmental conditions. Air pollution in cities is a serious environmental problem – especially in the developing countries. The air pollution path of the urban atmosphere consists of emission and transmission of air pollutants resulting in the ambient air pollution. Each part of the path is influenced by different factors. Emissions from motor traffic are a very important source group throughout the world. During transmission, air pollutants are dispersed, diluted and subjected to photochemical reactions. Ambient air pollution shows temporal and spatial variability. As an example of the temporal variability of urban air pollutants caused by motor traffic, typical average annual, weekly and diurnal cycles of NO, NO₂, O₃ and O_x are presented for an official urban air-quality station in Stuttgart, southern Germany. They are supplemented by weekly and diurnal cycles of selected percentile values of NO, NO₂, and O₃. Time series of these air pollutants give information on their trends. Results are discussed with regard to air pollution conditions in other cities. Possibilities for the assessment of air pollution in cities are shown. In addition, a qualitative overview of the air quality of the world's megacities is given.     

Air pollution forecast in cities by an air pollution index highly correlated with meteorological variables

There are many different air pollution indexes which represent the global urban air pollution situation. The daily index studied here is also highly correlated with meteorological variables and this index is capable of identifying those variables that significantly affect the air pollution. The index is connected with attention levels of NO₂, CO and O₃ concentrations. The attention levels are fixed by a law proposed by the Italian Ministries of Health and Environment. The relation of that index with some meteorological variables is analysed by the linear multiple partial correlation statistical method. Florence, Milan and Vicence were selected to show the correlation among the air pollution index and the daily thermic excursion, the previous day's air pollution index and the wind speed. During the January–March period the correlation coefficient reaches 0.85 at Milan. The deterministic methods of forecasting air pollution concentrations show very high evaluation errors and are applied on limited areas around the observation stations, as opposed to the whole urban areas. The global air pollution, instead of the concentrations at specific observation stations, allows the evaluation of the level of the sanitary risk regarding the whole urban population.     

Air pollution modelling in Erzurum city

Various techniques have been applied to air pollution modelling. In this study, a model was developed by applying a continuity equation to the air control volume over Erzurum city centre. Model parameters were calculated by regression analysis, using SO2 and particle concentrations taken in 1989-1990 and 1990-1991 winter seasons. Multiple correlation coefficients, R2, for all analyses were of the same order of 97%. According to this model, daily polluting concentrations are not only influenced by daily meterological parameters but also by the values of previous days. The proposed model allows estimation of daily polluting concentrations by means of meteorological data.     

Air pollution in a convective boundary layer

Detailed profiles of the concentration and the concentration flux for pollutants released continuously from a point source near the ground are presented. Although there are no observational data of the concentration flux and the covariance of temperature and concentration, the distributions of concentration and eddy diffusivity derived from this study are in good agreement with those of laboratory experiments. This study also shows that the covariance of temperature and concentration is important in producing a countergradient concentration flux in a convective boundary layer.     

Air pollution and mortality: A history

Mortality is the most important health effect of ambient air pollution and has been studied the longest. The earliest evidence relates to fog episodes but with the development of more precise methods of investigation it is still possible to discern short-term temporal associations with daily mortality at the historically low levels of air pollution that now exist in most developed countries. Another early observation was that mortality was higher in more polluted areas. This has been confirmed by modern cohort studies that account for other potential explanations for such associations. There does not appear to be a threshold of effect within the ambient range of concentrations. Advances in the understanding of air pollution and mortality have been driven by the combined development of methods and biomedical concepts. The most influential methodological developments have been in time-series techniques and the establishment of large cohort studies, both of which are underpinned by advances in data processing and statistical analysis. On the biomedical side two important developments can be identified. One has been the application of the concept of multifactorial disease causation to explaining how air pollution may affect mortality at low levels and why thresholds are not obvious at the population level. The other has been an increasing understanding of how air pollution may plausibly have pathophysiological effects that are remote from the lung interface with ambient air. Together, these advances have had a profound influence on policies to protect public health. Throughout the history of air pollution epidemiology, mortality studies have been central and this will continue because of the widespread availability of mortality data on a large population scale and the weight that mortality carries in estimating impacts for policy development.     

Air pollution and inversion features in Istanbul

Air pollution in the Istanbul metropolitan area arises from three significant sources: industrial and residential fossil fuels and road traffic. In winter this combination pushes air pollution to levels that are dangerous to humans and to plant life. As far as fossil fuels are concerned, total suspended particulates (TSP) and sulphur dioxide are the chief pollutants. In order to investigate the problem, five-year winter-season monthly pollution concentration records are used, starting from 1989. Classical statistical methods, such as frequency distribution functions, are examined and found to have exponential (SO₂), logarithmic normal (TSP) and Weibull (inversion height) distributions. A simple concept of 'pollutant polygon' is presented in order to make detailed interpretations of the relationship between the monthly averages of SO₂ and TSP. These levels were affected by the weak dispersion conditions in the lower atmosphere over the city.     

Air pollution dispersion within urban street canyons

A semi-empirical mathematical model, Urban Street Model (USM), is proposed to efficiently estimate the dispersion of vehicular air pollution in cities. This model describes urban building arrangements by combining building density, building heights and the permeability of building arrangements relative to wind flow. To estimate the level of air pollution in the city of Krasnoyarsk (in Eastern Siberia), the spatial distribution of pollutant concentrations off roadways is calculated using Markov's processes in USM. The USM-predicted numerical results were compared with field measurements and with results obtained from other frequently used models, CALINE-4 and OSPM. USM consistently yielded the best results. OSPM usually overestimated pollutant concentration values. CALINE-4 consistently underestimated these values. For OSPM, the maximum differences were 160% and for CALINE-4 about 400%. Permeability and building density are necessary parameters for accurately modeling urban air pollution and influencing regulatory requirements for building planning.     

Air pollution models as descriptors of cause-effect relationships

The problem of air pollution modeling is treated beginning from a philosophical standpoint, in which a model is viewed as a ‘universal statement’ and a complementary set of ‘singular statements’ from which specific cause-effect relationships are deduced; proceeding to the formulation of a specific model from fundamental physical principles. In the course of the analyses, a number of basic issues are examined. These include the types of information that an air pollution model is capable of providing (it is shown that specific events are not predictable, only the set of possible events can be described); the problem of model ‘validation’ (even with a perfect model and error-free input data and observations, discrepancies will exist between predicted and observed quantities); the character and representation of long-range dispersion (the conventional concepts of transport and diffusion become ill-defined when applied within the context of longrange dispersion models); and other topics relevant to the use of models in decision making processes.