Simultaneous sPIV and PLIF characterization of diverse airborne odor plumes

Many animals must navigate airborne odor plumes for successful foraging, mating, and habitat selection, but such navigation presents a challenging task due in part to chaotic transport of the odor through turbulent air. Despite broad ecological, industrial, and environmental importance, experimental investigation of such plumes remains limited, due largely to significant technical challenges associated with acquiring gaseous plume measurements at sufficient spatiotemporal resolutions. Here, we use simultaneous stereo particle image velocimetry and planar laser-induced fluorescence to jointly measure time-resolved velocity and scalar concentration fields for airborne odors transported by low Reynolds number grid turbulence in a recirculating wind tunnel. We introduce six datasets, including a baseline case (isokinetic, freestream release with neutral buoyancy) and five cases with perturbations to the source configuration (size, mass flow rate, buoyancy, bed proximity) or flow configuration (turbulence grid geometry). For each case, we present representative instantaneous flow and odor fields along with select statistical properties, highlighting Gaussian mean plumes, single-point concentration PDFs well-characterized by one-parameter Gamma distributions, and turbulence intensities that exhibit a combination of grid turbulence and a wake structure from the source tube. Finally, we leverage the multimodal data to compute turbulent odor fluxes and illustrate the connection between the velocity-derived finite-time Lyapunov exponent field and evolving structures in the odor field. These high-resolution measurements provide a rich suite of experimental data for use in fundamental studies of plume dispersion, olfactory neuroscience, and odor navigation in the data-scarce regime of low Schmidt number, low Reynolds number scalar transport.