Notebook code is executed on driver to achieve parallelism you need just to create Spark dataframe with your list.

As @Werner Stinckens​ said you can run multiple notebooks together also so in that case you will not use list just to every notebook pass 1 parameter from your list:

from multiprocessing.pool import ThreadPool
my_params =  ["Eu","JP","APAC"]
pool = ThreadPool(4) # match cpu cores here
pool.map(
    lambda my_param: run_notebook("my_notebook", 3600, {"my_widget": my_param}),
    my_params)