Convolution over volume in CNNs

I have a simple question about convolution layers in CNNs. Consider that we have 32 features map with size $$100\times100$$. So, can we set 16 convolution layer with size $$9\times9\times16$$ after features map? There isn't any limit on depth of the convolution layer? Then if we can, so every $$9\times9\times16$$ layer produces just one layer? (How does depth=16 work on depth=32)?