Flowers emit mixtures of scents that mediate plant-insect interactions such as attracting insect pollinators. Because of their volatile nature, however, floral scents readily react with ozone, nitrate radical, and hydroxyl radical. The result of such reactions is the degradation and the chemical modification of scent plumes downwind of floral sources. Large Eddy Simulations (LES) are developed to investigate dispersion and chemical degradation and modification of floral scents due to reactions with ozone, hydroxyl radical, and nitrate radical within the atmospheric surface layer. Impacts on foraging insects are investigated by utilizing a random walk model to simulate insect search behavior. Results indicate that even moderate air pollutant levels (e.g., ozone mixing ratios greater than 60 parts per billion on a per volume basis, ppbv) substantially degrade floral volatiles and alter the chemical composition of released floral scents. As a result, insect success rates of locating plumes of floral scents were reduced and foraging times increased in polluted air masses due to considerable degradation and changes in the composition of floral scents. Results also indicate that plant-pollinator interactions could be sensitive to changes in floral scent composition, especially if insects are unable to adapt to the modified scentscape. The increase in foraging time could have severe cascading and pernicious impacts on the fitness of foraging insects by reducing the time devoted to other necessary tasks.

Turbulent fluid flows have long been recognized as a superior means of diluting initial concentrations of scalars due to rapid stirring. Conversely, experiments have shown that the structures responsible for this rapid dilution can also aggregate initially distant reactive scalars and thereby greatly enhance reaction rates. Indeed, chaotic flows not only enhance dilution by shearing and stretching but also organize initially distant scalars along transiently attracting regions in the flow. To show the robustness of this phenomenon, a hierarchical set of three numerical flows is used: the periodic wake downstream of a stationary cylinder, a chaotic double gyre flow, and a chaotic, aperiodic flow consisting of interacting Taylor vortices. We demonstrate that Lagrangian coherent structures (LCS), as identified by ridges in finite time Lyapunov exponents, are directly responsible for this coalescence of reactive scalar filaments. When highly concentrated filaments coalesce, reaction rates can be orders of magnitude greater than would be predicted in a well-mixed system. This is further supported by an idealized, analytical model that was developed to quantify the competing e↵ects of scalar dilution and coalescence. Chaotic flows, known for their ability to e ciently dilute scalars, therefore have the competing e↵ect of organizing initially distant scalars along the LCS at timescales shorter than that required for dilution, resulting in reaction enhancement. C 2015 AIP Publishing LLC. [http://dx.

Particles that float on the surface of a 3D incompressible turbulent flow are exposed to non-divergencefree properties that result in clustering and unmixing, a reversal of how turbulence normally acts to mix and dilute scalars. Particle clustering is dominated by Lagrangian processes that depend on the time history of the flow; this suggests that Lagrangian coherent structures (LCS) might serve as templates for cluster formation. In this study, non-divergence-free clustering is examined both experimentally and numerically to elucidate the role of LCS in the formation of particle clusters and voids. Experiments are performed on the free-surface of a water-filled tank with turbulence driven by the random pulsing of centrifugal pumps on the tank bottom. Clustering is quantified by imaging fluorescent, buoyant particles that are placed in an initially random distribution on the freesurface. Within clusters, concentrations are observed to increase by an order of magnitude, with the likelihood of observing enhanced concentrations increasing by two orders of magnitude. LCS, obtained from velocity fields utilizing particle image velocimetry, are shown to act as templates for cluster formation. In addition, LCS are shown to possess a dilatation component in non-divergence-free flows that is responsible for unmixing. Numerically, a non-divergence-free chaotic model consisting of interacting Taylor vortices is utilized to investigate processes responsible for cluster formation seen in the experiments. The model results support the experimental finding that LCS act as templates for particle clusters, with scalar unmixing driven by the dilatation component.