  Turbulent puffs are ubiquitous in everyday life phenomena. Understanding
their dynamics is important in a variety of situations ranging from industrial
processes to pure and applied science. In all these fields, a deep knowledge of
the statistical structure of temperature and velocity space/time fluctuations
is of paramount importance to construct models of chemical reaction (in
chemistry), of condensation of virus-containing droplets (in virology and/or
biophysics), and optimal mixing strategies in industrial applications. As a
matter of fact, results of turbulence in a puff are confined to bulk properties
(i.e. average puff velocity and typical decay/growth time) and dates back to
the second half of the 20th century. There is thus a huge gap to fill to pass
from bulk properties to two-point statistical observables. Here we fill this
gap exploiting theory and numerics in concert to predict and validate the
space/time scaling behaviors of both velocity and temperature structure
functions including intermittency corrections. Excellent agreement between
theory and simulations is found. Our results are expected to have profound
impact to develop evaporation models for virus-containing droplets carried by a
turbulent puff, with benefits to the comprehension of the airborne route of
virus contagion.
