  Computer simulation with Monte Carlo is an important tool to investigate the
function and equilibrium properties of many systems with biological and soft
matter materials solvable in solvents. The appropriate treatment of long-range
electrostatic interaction is essential for these charged systems, but remains a
challenging problem for large-scale simulations. We have developed an efficient
Barnes-Hut treecode algorithm for electrostatic evaluation in Monte Carlo
simulations of Coulomb many-body systems. The algorithm is based on a
divide-and-conquer strategy and fast update of the octree data structure in
each trial move through a local adjustment procedure. We test the accuracy of
the tree algorithm, and use it to perform computer simulations of electric
double layer near a spherical interface. It has been shown that the
computational cost of the Monte Carlo method with treecode acceleration scales
as $\log N$ in each move. For a typical system with ten thousand particles, by
using the new algorithm, the speed has been improved by two orders of magnitude
from the direct summation.
