To answer (2), we still have linearity of expected value and variance, i.e. $$ \mathbb{E}[|X| + |Y|] = \mathbb{E}[|X|] + \mathbb{E}[|Y|] $$ and same for variance. You should be able to find the mean and variance of the folded normal from the parameters of the original normal using the definition, e.g. $$ \mathbb{E}[|X|] = \int_{-\infty}^\infty |x| \phi(x; \mu, \sigma) dx... $$