“Our work provides an improved model for predicting the transport potential of small particles (covering the size range of viruses, bacteria, and larger microbes) in granular porous media.”

Researchers and practitioners in many fields of science and engineering need to predict the removal and transport of colloidal and microbial particles in porous media. Extensive research is currently carried out in several of these fields—for instance, transport of microbial pathogens in subsurface environments. Our equation is simple to use and, unlike previous approaches, it includes all the mechanisms involved in the transport and removal of particles.

Our paper presents a new equation for predicting particle filtration efficiency in saturated porous media. This model is useful to scientists and engineers working in a wide range of fields, from design of water treatment processes to predictions of contaminant transport in subsurface environments.

Our work provides an improved model for predicting the transport potential of small particles (covering the size range of viruses, bacteria, and larger microbes) in granular porous media. The model is relevant in many different applications where it is necessary to predict or calculate particle removal and travel distances. For example, the model can be used to predict how far microbial pathogens can travel in the natural subsurface environment.

We identified the limitations of previous particle transport models early on and were excited about the opportunity to present a more complete and theoretically sound correlation. The development of the correlation equation became a part of Nathalie Tufenkji’s Ph.D. dissertation work at Yale University.