Work

TURB-Smoke. A database of Lagrangian pollutants emitted from point sources in turbulent flows with a mean wind

Year: 2026

Type: data-paper

Abstract: Identifying the location and characteristics of pollution sources in turbulent flows is challenging, especially for environmental monitoring and emergency response, due to sparse, stochastic, and infrequent cue detection. Even in idealized settings, accurately modeling these phenomena remains highly complex, with realistic representations typically achievable only through experimental or simulation-based data. We introduce TURB-Smoke, a cutting-edge numerical dataset designed for investigating odor and contaminant dispersion in turbulent environments with and without mean wind. Generated via direct numerical simulations of the fully resolved three-dimensional Navier-Stokes equations, TURB-Smoke tracks hundreds of millions of Lagrangian particles released from five distinct point sources in fully developed turbulence, thus providing a reliable ground-truth framework for developing and evaluating source-tracking strategies using stationary sensors or mobile agents in realistic flows. Each particle's trajectory is continuously tracked on many characteristic turbulence timescales, recording both the position and the local flow velocity. Additionally, we provide coarse-grained concentration fields in 3D and in quasi-2D slabs containing the source, ideal for quickly testing and optimizing search algorithms under varying flow conditions.

Source: Scientific Data

DOI: 10.1038/s41597-026-06774-7

Authors: Luca Biferale, Fabio Bonaccorso, Niccolò Cocciaglia, Robin A. Heinonen, Lorenzo Piro

Institutions: University of Rome Tor Vergata, University of Genoa

Language: English

Topic: Wind and Air Flow Studies

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,490

Funders: European Commission, National Institutes of Health, H2020 European Research Council