Atmospheric Transport and Source Characterization of Air Pollutants

Atmospheric transport and source characterisation of air pollutants address how airborne substances move through the atmosphere and how their origins and pathways are identified. Pollutants such as fine particulate matter (PM₂.₅ and PM₁₀), ozone precursors and trace metals can be emitted locally or at great distances, then undergo chemical transformation, vertical mixing and deposition. Understanding these processes requires integration of field observations, remote sensing and trajectory or chemical transport models. Back-trajectory analyses reveal the pathways of air masses, while receptor-based approaches—such as the potential source contribution function—quantify contributions from upwind zones. Insights into boundary-layer dynamics, regional recirculation and long-range transport inform mitigation strategies and regulatory policies. Recent advances have combined high-resolution numerical models with intensive measurement campaigns to refine estimates of transboundary fluxes, assess the influence of meteorological variability and distinguish primary emissions from secondary formation. This body of work underpins coordinated actions to improve air quality and public health on local, national and international scales.

Research from Nature Portfolio

Recent studies have elucidated the interplay between local emissions and regional transport in urban particulate pollution and demonstrated precision control strategies. One investigation introduced a dynamic framework to characterise the rising phase of PM₂.₅ pollution episodes by quantifying the concentration growth rate (PMRR) and linking it to wind speed, direction and upwind regional levels. This work highlighted that high PMRR events in megacities often coincide with enhanced regional contributions, whereas in some locales local sources dominate. A separate study developed a precision air pollution control approach that couples trajectory-receptor modelling with three-dimensional atmospheric simulations to pinpoint emission origins and optimise controls. Applied to severe haze events, this method reduced peak PM₂.₅ by over 60 % while requiring substantially fewer emission restrictions than blanket measures, demonstrating economic and environmental efficiency.

Atmospheric Transport and Source Characterization of Air Pollutants publication trend

The graph below shows the total number of articles in atmospheric transport and source characterization of air pollutants across all publications each year (not limited to Nature Index journals).

Technical terms

Particulate matter (PM₂.₅, PM₁₀): Airborne solid or liquid particles with aerodynamic diameters less than 2.5 µm or 10 µm, respectively, which affect health and visibility.

Back-trajectory modelling: A technique using wind and pressure data to trace the path of an air parcel backward in time to identify potential source regions.

Potential Source Contribution Function (PSCF): A receptor-based statistical method that links pollutant concentrations at a receptor site to the probability of emission sources in upwind grid cells.

Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model: A widely used computational tool for simulating air parcel trajectories and dispersion of pollutants.

Secondary inorganic aerosols (SIA): Fine particles such as sulfate, nitrate and ammonium formed in the atmosphere through chemical reactions of gaseous precursors.

References

1. Understanding the Rising Phase of the PM2.5 Concentration Evolution in Large China Cities. Scientific Reports (2017).
2. Mitigation of severe urban haze pollution by a precision air pollution control approach. Scientific Reports (2018).
3. The effect of cross-regional transport on ozone and particulate matter pollution in China: A review of methodology and current knowledge. The Science of The Total Environment (2024).
4. Transport Pathways and Potential Source Region Contributions of PM2.5 in Weifang: Seasonal Variations. Applied Sciences (2020).
5. Comparative Analysis of Three Methods for HYSPLIT Atmospheric Trajectories Clustering. Atmosphere (2021).