Yes ofc. Think of a convolution as an sliding window. You can slide the kernel through a 1d signal right? You can think of a 2d convolution as an spatial kernel right? If one of the dimensions is 1 then it’s the same than a 1d convolution.
In fact you can do a sanity check which is applying a 1d convolution and use its weights to emulate the same result with a 2d convolution.