def METHOD_NAME(*, df_list, year, **_):
    """
    Combine, parse, and format the provided dataframes
    :param df_list: list of dataframes to concat and format
    :return: df, parsed and partially formatted to
        flowbyactivity specifications
    """
    # concat list of dataframes (info on each page)
    df = pd.concat(df_list, sort=False)
    # subset by df
    df = df[df["Year"] == year]
    # remove non alphanumeric characters
    df["FlowName"] = df["FlowName"].str.replace('[^a-zA-Z0-9, ]', '',
                                                regex=True)
    # strip trailing white spaces
    df["FlowName"] = df["FlowName"].str.strip()
    df['SourceName'] = 'EPA_FactsAndFigures'
    df['Class'] = 'Other'
    df['FlowType'] = "WASTE_FLOW"
    df['Location'] = US_FIPS
    df = assign_fips_location_system(df, year)
    df['Year'] = str(year)
    df["FlowAmount"] = df["FlowAmount"].str.replace(',', '', regex=True)
    # Facts and Figures defines "Neg." as "Less than 5,000 tons or 0.05
    # percent," so replace with 0
    df["FlowAmount"] = df["FlowAmount"].str.replace('Neg.', '0', regex=True)
    df['DataReliability'] = 5  # tmp
    df['DataCollection'] = 5  # tmp
    return df