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. In this paper, an automated algorithm isdeveloped, which is used to identify the spectral gap during the heavy hazepollution process, reconstruct acquired data, and obtain pure turbulencedata. Comparisons of the reconstructed turbulent flux and eddy covariance(EC) flux show that there are overestimations regarding the exchange betweenthe surface and the atmosphere during heavy haze pollution episodes. Afterreconstruction via the automated algorithm, pure turbulence data can beobtained. We introduce a definition to characterize the local intermittentstrength of turbulence (LIST). The trend in the LIST during pollutionepisodes shows that when pollution is more intense, the LIST is smaller, andintermittency is stronger; when pollution is weaker, the LIST is larger, andintermittency is weaker. At the same time, the LIST at the city site isgreater than at the suburban site, which means that intermittency over thecomplex city area is weaker than over the flat terrain area. Urbanizationseems to reduce intermittency during heavy haze pollution episodes, whichmeans that urbanization reduces the degree of weakening in turbulent exchangeduring pollution episodes. This result is confirmed by comparing the averagediurnal variations in turbulent fluxes at urban and suburban sites duringpolluted and clean periods. The sensible heat flux, latent heat flux,momentum flux, and turbulent kinetic energy (TKE) in urban and suburban areasare all affected when pollution occurs. Material and energy exchanges betweenthe surface and the atmosphere are inhibited. Moreover, the impact of thepollution process on suburban areas is much greater than on urban areas. Theturbulent effects caused by urbanization seem to help reduce the consequencesof pollution under the same weather and pollution source condition, becausethe turbulence intermittency is weaker, and the reduction in turbulenceexchange is smaller over the urban underlying surface.

Effects of turbulence structure and urbanization on the heavy haze pollution process