Modelling

The document serves as a training module on air quality modelling, detailing the use of dispersion models to estimate pollutant concentrations and the application of receptor models for source apportionment. It emphasizes the critical role of meteorological data—including wind, turbulence, and mixing height—and describes various modelling approaches from simple box models to complex Eulerian grids. Additionally, it highlights Nuclear Analytical Techniques (NATs) such as Neutron Activation Analysis (NAA) and Ion Beam Analysis (IBA) for identifying particulate matter sources in Asian cities.

• Air quality simulation models (AQSM) are numerical tools used to estimate pollutant concentrations in space and time, helping managers determine the relative contributions of mobile and stationary sources and the emission reductions needed to meet air quality standards.
• Dispersion models serve as a cost-effective complement to monitoring, capable of estimating spatial distributions, forecasting pollution episodes, and assessing the impact of planned facilities where monitoring is too expensive or methodologies do not exist.
• Atmospheric stability and temperature inversions significantly affect pollutant dispersion; for example, 'stagnant inversions' trap pollutants near the ground, while 'fumigation' occurs when morning heating mixes trapped pollutants down to ground level.
• The document distinguishes between different types of dispersion models: Box models are the simplest but often unrealistic; Gaussian models are used for point sources like stacks; Puff models (e.g., CALPUFF) handle non-steady-state effects; and Eulerian models (e.g., UAM) are best for complex photochemical oxidant problems.
• Source apportionment (SA) uses two main approaches: source-oriented, which uses emission inventories and chemical transport models (CTMs), and receptor-oriented, which uses statistical procedures like Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) to infer sources from ambient samples.
• Nuclear Analytical Techniques (NATs)—specifically Neutron Activation Analysis (NAA), X-ray fluorescence (XRF), and Ion Beam Analysis (IBA)—allow for the non-destructive, simultaneous analysis of many elements in particulate matter to identify pollution sources.
• Case studies in Asia demonstrate the utility of NATs for source identification: in Beijing, NAA identified soil and refuse incineration as sources; in Vietnam, NAA linked Zn to vehicular emissions; and in Metro Manila, biomass burning was identified as a major contributor to fine particulate matter (PM2.5).

APA

Haq, G., & Schwela, D. (2008). Modelling. Stockholm Environment Institute. https://www.sei.org/mediamanager/documents/Publications/Atmospheric/Cleanair/download/Module3-MODELLING-AirQualityManagement.pdf

Chicago

Haq, Gary, and Dieter Schwela. Modelling. Stockholm Environment Institute, 2008. https://www.sei.org/mediamanager/documents/Publications/Atmospheric/Cleanair/download/Module3-MODELLING-AirQualityManagement.pdf.

Wikipedia

{{cite report |last1=Haq |first1=Gary |last2=Schwela |first2=Dieter |title=Modelling |publisher=Stockholm Environment Institute |date=2008 |url=https://www.sei.org/mediamanager/documents/Publications/Atmospheric/Cleanair/download/Module3-MODELLING-AirQualityManagement.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{haq2008modelling, author = {Haq, Gary and Schwela, Dieter}, title = {{Modelling}}, institution = {Stockholm Environment Institute}, year = {2008}, url = {https://www.sei.org/mediamanager/documents/Publications/Atmospheric/Cleanair/download/Module3-MODELLING-AirQualityManagement.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }