Averaging principle for semilinear stochastic partial differential equations involving space–time white noise

We study the averaging principle for a class of semilinear stochastic partial differential equations perturbed by space–time white noise. Using the factorization method and Burkholder’s inequality, the estimation of stochastic integral involving the heat kernel is obtained. Under suitable assumptions, we show that the original stochastic systems can be approximated by the averaged equations.