Each year, 8.1 million people die worldwide due to air pollution, where nanoparticles are so small that they evade the defenses of the human body.
In response, a team from the University of Warwick, England, developed a mathematical tool capable of accurately predicting how these particles move in the air.
This advancement is key because it could change the foundations for studying atmospheric pollution and protecting public health.
The research, led by Duncan Lockerby from the School of Engineering at the University of Warwick and published in Journal of Fluid Mechanics Rapids, presents an innovative mathematical model.
This estimates the trajectory and behavior of nanoparticles of any shape in the air.
The applications of the model that measures air pollution
The model, already available as code for Matlab, can be applied in laboratories and industries worldwide.
Its practical impact is varied: it allows anticipating the dispersion of pollutants in cities, the movement of ashes, fire smoke, and the behavior of nanoparticle-based medicines.
The method also provides new insights into systems that monitor air quality.
Additionally, the University of Warwick opened a laboratory that will allow experimentation with particles of different shapes under controlled conditions.
The researchers suggested using the model in environmental studies, the development of safe technologies, and the creation of clean air regulations.
However, they clarified that the method still needs to be tested for particles with more extreme shapes and for cases where many particles interact.
Lockerby emphasized that the results “represent a significant advancement for both environmental health and aerosol science.”
Why particle shapes matter
Millions of nanoparticles float daily in the air: soot, dust, pollen, microplastics, and viruses.
Their tiny size allows them to reach deep areas of the lungs and access the bloodstream.
Until now, scientific calculations assumed that all particles were spheres, because this makes mathematical models simpler.
But this view excludes almost all the diversity of shapes present in real life, where particles have edges, surfaces, and irregular geometries.
These simplifications prevent accurately predicting how the pollutants that most concern public health are distributed and accumulated.
“The motivation was simple: if we can accurately predict how particles of any shape move, we can significantly improve air pollution models,” stated Lockerby.
The century-old formula adapted to measure air pollution
The model is based on the mathematical formula created in 1910 by physicist John Cunningham, known as the “Cunningham correction factor”.
This equation allows calculating how air resistance affects tiny particles.
Robert Millikan, Nobel laureate in Physics, adapted this equation for spheres but left out other shapes.
Lockerby’s team revisited the original concept and expanded it to work for any geometry.
The model uses a “correction tensor,” a type of mathematical formula that allows calculating the forces and resistance faced by particles of all shapes, without relying on prior experimental data or lengthy and costly simulations.
The team verified the solidity of the method by comparing the results with laboratory data.
With spherical particles, the margin of error was less than 4%. Lockerby noted that “it provides the first framework to accurately predict how non-spherical particles travel through the air.”
Thus, this development comes at a critical time when air pollution remains one of the main concerns of global public health, according to 2021 UN data.
