Nonatomic total rewards Markov decision processes with multiple criteria

We consider a Markov decision process with an uncountable state space for which the vector performance functional has the form of expected total rewards. Under the single condition that the fixed initial distribution and transition probabilities are nonatomic, we prove that for any policy there is a nonrandomized Markov policy such that for these two policies the performance vectors are equal