Effect of emission variability on concentration fluctuations in idealised deep urban street canyons

The level of air pollution in a street canyon depends on the non -trivial interplay between vehicular exhaust emissions, atmospheric transport, and physico-chemical transformation of pollutants. In this study, we investigate the temporal dynamics of air pollutant concentration in a deep street canyon orthogonal to the wind direction using a two -box model. Simulations provide insights into both steady-state mean concentrations and the magnitude of concentration fluctuations as pollutant nature (inert or reactive), emission signal stochasticity, and the fundamental rates of turbulent transport and chemical transformations vary. Beyond elucidating the role of different parameters on mean pollution levels, the results reveal that extreme air pollutant concentrations are more likely to occur when the characteristic time scale of vehicular exhaust emissions significantly exceeds the ventilation time scale of the street canyon. The innovative modelling approach paves the way for various applications, particularly in the field of optimal traffic management and the study of citizens' exposure to air pollution

Experimental investigation of vertical turbulent transport of a passive scalar in a boundary layer: Statistics and visibility graph analysis

The dynamics of a passive scalar plume in a turbulent boundary layer is experimentally investigated via vertical turbulent transport time-series. Data are acquired in a rough-wall turbulent boundary layer that develops in a recirculating wind tunnel set-up. Two source sizes in an elevated position are considered in order to investigate the influence of the emission conditions on the plume dynamics. The analysis is focused on the effects of the meandering motion and the relative dispersion. First, classical statistics are investigated. We found that (in accordance with previous studies) the meandering motion is the main responsible for differences in the variance and intermittency, as well as the kurtosis and power spectral density, between the two source sizes. On the contrary, the mean and the skewness are slightly affected by the emission conditions. To characterize the temporal structure of the turbulent transport series, the visibility algorithm is exploited to carry out a complex network-based analysis. Two network metrics -- the average peak occurrence and the assortativity coefficient -- are analysed, as they can capture the temporal occurrence of extreme events and their relative intensity in the series. The effects of the meandering motion and the relative dispersion of the plume are discussed in the view of the network metrics, revealing that a stronger meandering motion is associated with higher values of both the average peak occurrence and the assortativity coefficient. The network-based analysis advances the level of information of classical statistics, by characterizing the impact of the emission conditions on the temporal structure of the signals in terms of extreme events and their relative intensity. In this way, complex networks provide -- through the evaluation of network metrics -- an effective tool for time-series analysis of experimental data

Gravitational Instantons from Gauge Theory

A gauge theory can be formulated on a noncommutative (NC) spacetime. This NC gauge theory has an equivalent dual description through the so-called Seiberg-Witten (SW) map in terms of an ordinary gauge theory on a commutative spacetime. We show that all NC U(1) instantons of Nekrasov-Schwarz type are mapped to ALE gravitational instantons by the exact SW map and that the NC gauge theory of U(1) instantons is equivalent to the theory of hyper-Kaehler geometries. It implies the remarkable consequence that ALE gravitational instantons can emerge from local condensates of purely NC photons.Comment: 4 pages with two columns; comments and references added, to appear in Phys. Rev. Let