diff --git a/scripts/us_cdc/environmental_health_toxicology/parse_air_quality.py b/scripts/us_cdc/environmental_health_toxicology/parse_air_quality.py
index 1c658b3d8a..943973a299 100644
--- a/scripts/us_cdc/environmental_health_toxicology/parse_air_quality.py
+++ b/scripts/us_cdc/environmental_health_toxicology/parse_air_quality.py
@@ -58,7 +58,9 @@
 
 def main():
     """Main function to generate the cleaned csv file."""
+    print(sys.argv[1])
     file_path = sys.argv[1]
+    print("filepath--------", file_path)
     output_file = sys.argv[2]
     clean_air_quality_data(file_path, output_file)
 
@@ -73,12 +75,9 @@ def clean_air_quality_data(file_path, output_file):
     """
     print("Cleaning file...")
     data = pd.read_csv(file_path)
-    if "Ozone" in file_path and "County" in file_path:
-        data["Month"] = data["Month"].map(MONTH_MAP)
-        data["date"] = pd.to_datetime(data[["Year", "Month", "Day"]],
-                                      yearfirst=True)
-    else:
-        data["date"] = pd.to_datetime(data["date"], yearfirst=True)
+    data["date"] = pd.to_datetime(data["date"], yearfirst=True)
+    data["statefips"] = data["statefips"].astype(str).str.zfill(2)
+
     if "PM2.5" in file_path:
         census_tract = "DS_PM"
     elif "Ozone" in file_path:
@@ -96,11 +95,11 @@ def clean_air_quality_data(file_path, output_file):
         data["dcid"] = "geoId/" + data["ctfips"].astype(str)
         data['StatisticalVariable'] = data['StatisticalVariable'].map(STATVARS)
     elif "County" in file_path and "PM" in file_path:
-        data["countyfips"] = "1200" + data["countyfips"].astype(str)
-        data["dcid"] = "geoId/" + data["countyfips"].astype(str)
+        data["countyfips"] = data["countyfips"].astype(str).str.zfill(3)
+        data["dcid"] = "geoId/" + data["statefips"] + data["countyfips"]
     elif "County" in file_path and "Ozone" in file_path:
-        data["countyfips"] = "1200" + data["countyfips"].astype(str)
-        data["dcid"] = "geoId/" + data["countyfips"].astype(str)
+        data["countyfips"] = data["countyfips"].astype(str).str.zfill(3)
+        data["dcid"] = "geoId/" + data["statefips"] + data["countyfips"]
     data.to_csv(output_file, float_format='%.6f', index=False)
     print("Finished cleaning file!")