  Motivated by uncertainty quantification in natural transport systems, we
investigate an individual-based transport process involving particles
undergoing a random walk along a line of point sinks whose strengths are
themselves independent random variables. We assume particles are removed from
the system via first-order kinetics. We analyse the system using a hierarchy of
approaches when the sinks are sparsely distributed, including a stochastic
homogenization approximation that yields explicit predictions for the extrinsic
disorder in the stationary state due to sink strength fluctuations. The
extrinsic noise induces long-range spatial correlations in the particle
concentration, unlike fluctuations due to the intrinsic noise alone.
Additionally, the mean concentration profile, averaged over both intrinsic and
extrinsic noise, is elevated compared with the corresponding profile from a
uniform sink distribution, showing that the classical homogenization
approximation can be a biased estimator of the true mean.
