Review of developments in air quality modelling and air quality dispersion models

Abstract

Air dispersion models are mathematical tools used for simulating the physical and chemical processes governing the diffusion and transformation of pollutants in the atmosphere. The simplest dispersion models are steady-state Gaussian plume models. They are based on mathematical approximation of the plume behaviour and follow some basic assumptions that may not always present a realistic scenario. Despite having these limitations, they provide reasonable results when used aptly. More recently, advanced dispersion models are being developed, which are based on a more refined approach of simulating the dispersion phenomenon following the properties of the atmosphere rather than relying on general mathematical approximation. This has expanded the field of modelling to tackle difficult situations such as complex terrain and long-distance transport. In this review paper, the developments in air quality modelling, with emphasis on dispersion modelling, are presented. Further, a few models are selected representing different categories in dispersion modelling, which are Gaussian models – American Meteorological Society/Environmental Protection Agency Regulatory Model, Caline4, Airviro Gauss, Complex Terrain Dispersion Model and Fugitive Dust Model; Eulerian models – California Grid Model, Flexible Air Quality Regional Model and Panache; Lagrangian models – Graz Lagrangian Model, Flexible Particle Dispersion Model, Austal2000 and Hybrid Single Particle Lagrangian Integrated Trajectory Model; and advanced dispersion models – UK–Atmospheric Dispersion Modelling System 5, The Air Pollution Model and Calpuff. A comparison has been done based on certain characteristic features obtained from various publications.

Learning Calibration Functions on the Fly: Hybrid Batch Online Stacking Ensembles for the Calibration of Low-Cost Air Quality Sensor Networks in the Presence of Concept Drift

“…Modeling of the atmospheric chemical composition has advanced steadily over the past number of years [1,2] with the aim of producing actionable Air Quality (AQ) information. Data about AQ are routinely collected from official (ground-based) monitoring stations.…”

The Effect of COVID-19 Pandemic on Emitted PM2.5 in Urban Road Networks: Using Loop Data and Kriging Method for Passenger Cars in the Central Part of the City of Lodz

“…Third, due to the delays that might be occurred in the data collection process, temporal records are associated with lags which add more complexity to the vehicular pollution emission analysis (Shi et al, 2018;Rossi et al, 2020). Nevertheless, regarding the fact that models provide helpful tools to estimate pollution concentration and dispersion (Holnicki et al, 2016;Khan and Hassan, 2020), vehicular emissions have been computed in various studies (Jenkins et al, 1970;Clougherty et al, 2008;Elangasinghe et al, 2014;Perez-Martinez and Miranda, 2015;Pan et al, 2016;Shi et al, 2018;Qu et al, 2019). These studies calculated the vehicular emissions by focusing on the flow data collected for a subset of links (e.g., a certain road or highway) in a network.…”

Modeling Urban Atmospheric Lead Dispersion from a Mining Tailings Basin in Bahia, Brazil

“…Atmospheric dispersion models are useful tools for predicting air quality and identifying areas and/or time periods of pollutant concentrations above established legal limits (Borges, Teixeira & Ribeiro 2021;Costa & Costa 2021). Such models consider transport processes including the mechanisms of suspension, advection, dispersion, deposition, resuspension and/or accumulation (Khan & Hassan 2021). Contaminants can be removed from the atmosphere by dry deposition processes through the action of gravity, and also by wet deposition consisting of the absorption of pollutants by raindrops and consequent removal by precipitation to the soil.…”

“…These models can be used to identify and study standard scenarios as well as for site assessment and simulation of predictions, thus supporting solutions to problems of air pollution. The atmospheric dispersion of suspended particulates is related to local turbulence and deposition, including downward movement due to precipitation and sedimentation (Khan & Hassan 2021;Leelossy et al 2018). According to Seinfels and Pandis (2006), the deposition process consists of three distinct steps being (1) aerodynamic transport to a very thin layer of stagnant air adjacent to the surface, (2) Brownian transport in this very thin layer, and (3) adherence at the surface.…”

“…Such models have been applied for investigating health impacts of air pollution (Andreão et al 2020), longrange transport (Duarte et al 2021) and scenarios for the reduction of contaminant emissions (Teixeira et al 2020;Zhang et al 2021). For more comprehensive reviews see Giovannini et al (2020), Khan and Hassan (2021), or Leelossy et al (2018).…”