Atmospheric Chemistry and Air Quality Modeling

Atmospheric chemistry and air quality modeling integrates the physical transport of gases and particles with the chemical transformation and removal processes that determine pollutant concentrations from local to global scales. Models couple meteorological fields—such as wind, humidity and temperature—with emission inventories that quantify sources from industry, transport, vegetation and natural phenomena. Within these frameworks, photochemical reactions drive the formation of secondary pollutants, while deposition processes return species to the surface. Advances in numerical schemes and computational power have enabled nested simulations spanning regional, urban and street-scale domains, permitting detailed assessment of health impacts, ecosystem exposure and policy interventions. Such models underpin regulatory decisions on emission controls, inform early-warning systems for pollution episodes and support nature-based solutions, including urban greening, to mitigate heat stress and pollutant exposure. Ongoing challenges include reducing uncertainties in emissions, boundary conditions and process parametrisations, particularly for aerosol–cloud interactions and secondary organic aerosol formation. The integration of ensemble forecasting techniques and data assimilation from satellite and ground-based sensors promises more reliable air quality forecasts and real-time assessments. Ultimately, the field strives to couple chemistry–climate interactions to predict feedbacks under a changing environment, ensuring that modelling remains a central pillar in protecting human health and guiding sustainable development worldwide.

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Atmospheric Chemistry and Air Quality Modeling publication trend

The graph below shows the total number of articles in atmospheric chemistry and air quality modeling across all publications each year (not limited to Nature Index journals).

Technical terms

Chemical transport model: A numerical tool that couples atmospheric dynamics with chemical reactions and pollutant emissions to simulate air quality.

Planetary boundary layer: The lowest part of the atmosphere directly influenced by surface heating, turbulence and friction, critical for pollutant dispersion.

Secondary organic aerosol (SOA): Fine particulate matter formed by the oxidation of volatile organic compounds, contributing to haze and health risks.

Emissions inventory: A comprehensive dataset quantifying pollutant sources by sector, geography and chemical species for model inputs.

Ensemble forecasting: The use of multiple model runs, varying inputs or schemes, to characterise uncertainties and improve confidence in air quality predictions.

References

1. Meteorological, chemical and biological evaluation of the coupled chemistry-climate WRF-Chem model from regional to urban scale. An impact-oriented application for human health. Environmental Research (2024).
2. Air quality modelling in the summer over the eastern Mediterranean using WRF-Chem: chemistry and aerosol mechanism intercomparison. Atmospheric Chemistry and Physics (2018).
3. Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1. Geoscientific Model Development (2019).