The singular values of the solution to a Lyapunov equation determine the potential accuracy of the low-rank approximations constructed by iterative methods. Low-rank solutions are more accurate if most of the singular values are small, so a-priori bounds that describe coefficient matrix properties that correspond to rapid singular value decay are valuable. Previous bounds take similar forms, all of which weaken (quadratically) as the coefficient matrix departs from normality. Such bounds suggest that the farther from normal the coefficient matrix is, the slower the singular values of the solution will decay. This predicted slowing of decay is manifest in the ADI algorithm for solving Lyapunov equations, which converges more slowly when the coefficient is far from normal. However, simple examples typically exhibit an eventual acceleration of decay if the coefficient departs sufficiently from normality. This thesis shows that the decay acceleration principle is universal: decay always improves as departure from normality increases beyond a given threshold, specifically, as the numerical range of the coefficient matrix extends farther into the right half-plane. The concluding chapter gives examples showing that similar behavior can occur for general Sylvester equations, though the right-hand side plays a more important role.