W17: Air Quality Modelling

organised by Roberto San José and Alexander Baklanov


Title: Air Quality Modelling: State-Of-The-Art

Authors: R. San Jose, A. Baklanov, R.S. Sokhi, K. Karatzas and J.L. Perez

Abstract: Air quality modeling is an area with a significant progress and interest during the last two decades. It covers all aspects related to pollution dispersion and impact on different ecosystems. It is very much related to the meteorological field since the atmosphere is governed by the general laws derived by the Navier-Stokes equation system. Progress in computer capabilities during the last decades has impulse substantially the research on air quality modeling in a parallel way. Air pollution modeling covers a very complex and interdisciplinary area where we include remote sensing – land use impact -, initial and boundary conditions, data assimilation techniques, chemical schemes, comparison between measured and modeled data, computer efficiency, parallel computing in air quality modeling, long-range transport impact on local air pollution, new satellite data assimilation techniques, real-time and forecasting air quality modeling and sensitivity analysis. This contribution focuses on providing a general overview of the state-of-the-art on air quality modeling, from the point of view of the “user community”, i.e. policy makers, urban planners, environmental managers, etc.. It also tries to bring to the discussion key questions concerning the air quality modeling success in usage, such as, where are greatest uncertainties in emission inventories, how well do air quality models simulate urban aerosols, what are the next generation developments in models to answer new scientific questions, etc.

Title: Air Pollution in Japan: the Inverted U-Shaped Relation

Authors: Toshitaka Fukiharu

Abstract: In 1995 Grossman and Krueger, utilizing the data collected worldwide, discovered the inverted U-shaped relation between the per-capita GDP and air pollution level. It may be explained that when a society is poor it endures the rising pollution level to become rich, while when it has become rich, it prefers less pollution as it becomes richer, due to the "income effect". Theoretically, this economic argument assumes that the preference relation of the society members towards environment is invariant, as the society becomes rich. To explain the inverted U-shaped relation, however, an alternative explanation is also possible: although for each country's cross-sectional data the positive relation holds between the per-capita GDP and pollution level, when the data collected worldwide, where the pollution level is the average of the above country data, the locus may exhibit the inverted U-shape. The worldwide result might be regarded as the one of time-series data, in which each country's preference relation towards environment is different depending on the stage of economic growth. First, it is shown by mathematical modeling that the above two explanations can depict the inverted U-shape. Next, it is examined if the inverted U-shaped relation holds for specific years, utilizing Japanese cross-sectional data for 1990 and 2000. In this section three types of pollution are dealt with: SOX, NOX, and SPM. The inverted U-shaped relation does exist for SOX case in 2000. It is the case, however, solely for SOX case in 2000. Even for this SOX case in 2000, statistically, it is also possible to assert that the positive relation exists. For all the other cases on NOX and SPM, only the positive relation exists, while the inverted U-shaped relation is statistically denied. Thus, the explanation in terms of the shift of preference relation towards more pollution-intolerant is more persuasive in Japan.

Title: Spatial estimations of air pollution in street canyons by LIDAR measurements

Authors: Lubos Matejicek, Jana Konradova

Abstract: Air pollution of urban areas can be explored by direct monitoring, mathematical modeling and physical simulation in the wind tunnels. Complex analysis requires using of all mentioned approaches together. To integrate the data inputs and outputs, which include spatio-temporal interactions, the Geographic Information System (GIS) is used for database management and spatial analysis. The geodatabase is primarily developed to support spatial interpolations of data from LIDAR measurements in the street canyons. The LIDAR measurements provide the information about the distribution of pollutants in the points along the beam trajectories. As the examples, the sets of O3 and NO2 spatial measurements are performed in the area of Prague street canyons. To estimate the levels of concentrations in the neighbor points, deterministic methods (IDW, spline) and geostatistical methods (kriging, cross-correlation) are used in the frame of the GIS projects. The interpolations provide the distribution of pollutant concentrations in the vertical planes, which are used for better understanding of air pollution in the street canyons. In addition to the interpolated pollutant concentrations in the 3D space, the attached GIS layers represent digital terrain models with buildings and vegetation, aerial and satellite images, surrounding sources of pollution and other thematic map layers. The integration of all mentioned data enables to extend our knowledge of the pollutants distribution and consecutively the influence on living environment. The developed projects can be included into more complex approaches, which can help local and state authorities to improve their decision-making management and to carry out risk assessment analysis. Besides the spatial data integration, numerical models are included into the project to predict the transport of pollutants. The data sharing with other modeling systems can be used through the geodatabase.