Air Pollution Modelling and Control
Summary
Air pollution modelling employs mathematical representations of emissions, atmospheric transport, chemical transformation and removal processes to predict pollutant concentrations across scales from street canyons to continental plumes. Models range from simple Gaussian dispersion formulas—used for near-source impact assessments—to three-dimensional chemical transport models (CTMs) that resolve gas-phase and aerosol chemistry, deposition and meteorological feedbacks. By assimilating emission inventories, meteorological fields and observational data, these tools support air quality forecasting, scenario testing and policy evaluation. Control strategies informed by modelling include targeted emission reductions in transport and industry, fuel-switching programmes, optimiser placement of monitoring networks, and design of end-of-pipe abatement such as scrubbers and filters. Integrated modelling underpins regulatory decisions, informs public health advisories and guides local measures—such as low-emission zones or temporary curtailment of biomass burning—to protect urban populations and sensitive ecosystems.
Research from Nature Portfolio
Recent work has demonstrated the global diversity of trace metals in fine particulate matter and its implications for air quality and health. A globally coordinated network of surface PM2.5 samplers coupled with chemical transport simulations revealed that anthropogenic activities drive spatial variations in airborne metals, with concentrations of lead, arsenic and chromium enriched by hundreds to thousands of per cent above crustal levels in urban and industrial hotspots. These measurements have been crucial for refining emission inventories and improving aerosol-chemistry modules in CTMs.
In an urban biofuel transition study, real-world fleet shifts between ethanol and gasoline use were shown to alter morning-commute ultrafine particle concentrations by roughly one-third in a major megacity. High-resolution observations and econometric analysis provided empirical evidence that fuel composition influences sub-100 nm particle counts more markedly than conventional PM2.5 metrics, highlighting the need to consider ultrafine dynamics in vehicle-emission models and control policies.
Air Pollution Modelling and Control publication trend
The graph below shows the total number of articles in air pollution modelling and control across all publications each year (not limited to Nature Index journals).
Technical terms
PM2.5: Particulate matter with aerodynamic diameter less than 2.5 micrometres, capable of deep lung penetration and linked to adverse health effects.
Chemical transport model (CTM): A numerical framework that simulates emissions, advection, diffusion, chemical transformation and deposition of atmospheric pollutants over multiple scales.
Emission inventory: A comprehensive dataset quantifying pollutant release rates from various sources, used as input for dispersion and CTM analyses.
Source apportionment: Analytical techniques to determine the contributions of distinct emission sources to observed pollutant concentrations.
Back-trajectory modelling: A method that traces air parcels backward in time to identify potential source regions of observed pollutants.
Ultrafine particles: Aerosol particles with diameters below 100 nanometres, often regulated separately due to distinct health impacts.
References
- Large global variations in measured airborne metal concentrations driven by anthropogenic sources. Scientific Reports (2020).
- Reduced ultrafine particle levels in São Paulo’s atmosphere during shifts from gasoline to ethanol use. Nature Communications (2017).
- Brazilian Atmospheric Inventories – BRAIN: a comprehensive database of air quality in Brazil. Earth System Science Data (2024).
- PM2.5 source allocation in European cities: A SHERPA modelling study. Atmospheric Environment (2018).
- Evaluating public exposure to airborne particulates from major incident fires: A back trajectory plume modelling approach. Journal of Hazardous Materials (2025).
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