Air Pollution Modeling and its Application XX (original) (raw)
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Air Pollution Modeling and Its Application XVII
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Air Pollution Modeling and Its Application XIII
Springer eBooks, 2000
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The Current State And The Future Directions In Air Quality Modeling
1996
In this paper the present "state\ of air quality modeling (as viewed by the authors) is presented. The focus of the paper will be on the "current\ state-of-a airs. Due to limitation of space (and the focus of this Dagstuhl Seminar) the discussion will focus on only a few aspects of air quality modeling: i.e., chemical integration, sensitivity analisys and computational framework.
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Air pollution predictions for environmental impact assessments usually use Gaussian plume/puff models driven by observationally-based meteorological inputs. An alternative approach is to use prognostic meteorological and air pollution models, which have many advantages over the Gaussian approach and are now becoming a viable tool for performing year-long simulations. Continuing rapid increases in computing power are bringing this approach to the PC. This report provides a comprehensive technical description of the newly enhanced prognostic model called The Air Pollution Model (TAPM).
Science of The Total Environment, 2008
The high levels of air pollutants over the North-Western Mediterranean (NWM) exceed the thresholds set in current air quality regulations. They demand a detailed diagnosis of those areas where the exceedances of thresholds related to human health are found. In this sense, there is a need for modelling studies for the specific area of the NWM that take into account the annual cycle to address the diagnosis of air pollution. A new approach to the modelling of air quality in the NWM has been adopted by combining the WRF-EMICAT-CMAQ-DREAM modelling system to diagnose the current status of the levels of photochemical air pollution (focusing on ozone, O 3 ; nitrogen dioxide, NO 2 ; carbon monoxide, CO; and particulate matter, PM10) in the area during an annual cycle (year 2004). The complexity of the area of study requires the application of high spatial and temporal resolution (2 km and 1 h). The annual simulations need to cover the complex different meteorological situations and types of episodes of air pollution in the area of study. The outputs of the modelling system are evaluated against observations from 52 meteorological and 59 air quality stations belonging to the Environmental Department of the Catalonia Government (Spain), which involve a dense and accurate spatial distribution of stations in the territory (32,215 km 2 ). The results indicate a good behaviour of the model in both coastal and inland areas of the NWM, with a slight trend to the overestimation of tropospheric O 3 concentrations and the underestimation of other photochemical pollutants (NO 2 , CO and PM10). The modelling diagnosis indicates that the main air quality-related problems in the NWM are the exceedances of the 1-hr O 3 information threshold set in the Directive 2002/3/EC (180 μg m − 3 ) as a consequence of the transport of O 3 precursors downwind the Barcelona Greater Area (BGA); and the exceedances of the annual value for the protection of human health for NO 2 and PM10 (40 μg m − 3 , Directive 1999/30/EC), both in the BGA, as a consequence of the high traffic-related emissions. ava i l a b l e a t w w w. s c i e n c e d i r e c t . c o m w w w. e l s ev i e r. c o m / l o c a t e / s c i t o t e n v
W17: AIR QUALITY MODELLING: STATE-OF-THE-ART
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.
Comparative Study of Air Quality Models
In mega cities and urban areas, industrial growth and vehicular emissions have caused severe concern of ambient air pollution. Situation is alarming; it can increase in near future to cope up with population expansion. Air quality models have been using for assessing impact of emission sources to ambient air pollution as well as for planning emission controls. These models use meteorology and emission inventory to trace the dispersion path of a pollutant to estimate the impact at the receptor. US-EPA's AERMOD has an improved approach for characterizing boundary layer parameters and vertical profile of atmosphere as compared to other dispersion models. The application of Gaussian Plume Model (GPM) requires knowledge of several parameters, i.e. atmospheric turbulence, emission release rate, wind speed, dispersion coefficients, effective stack height, mixing height etc. In most of the cases of Indian scenario, meteorological data is not available. Under such conditions, it is propo...