diff --git a/docs/CICs/UNFAOPostProcessorManager.md b/docs/CICs/UNFAOPostProcessorManager.md
index b4d6b29..568bbaa 100644
--- a/docs/CICs/UNFAOPostProcessorManager.md
+++ b/docs/CICs/UNFAOPostProcessorManager.md
@@ -36,7 +36,7 @@ It is the single entrypoint for producing and delivering UN FAO-formatted predic
 - Guarantees that geographic metadata is added via `GaulLookupEnricher.enrich_dataframe_with_pg_info()` (a cell-id merge against the precomputed lookup)
 - Guarantees that required metadata columns are validated before upload
 - Guarantees that both historical and forecast datasets are uploaded to the UN FAO Appwrite bucket with correct metadata (name, loa, type, category)
-- **Partially** logs-and-raises structural failures (ADR-008): the `_validate` gates and the S0–S6 delivery guards comply, but 3 raises in `unfao.py` (missing `ensemble`, missing `loa`, datasets-None in `_save`) still raise without a preceding `logger.error` — tracked by **C-19 / #13**
+- Logs structural failures before raising them (ADR-008): the config/`loa` guards, the `_validate` gates, and the dataset/`_save` guard all `logger.error`-then-raise (#13 / C-19 resolved); the `delivery/` invariants raise representation-free, with the manager logging context at each call site
 
 ---
 
diff --git a/views_postprocessing/unfao/managers/unfao.py b/views_postprocessing/unfao/managers/unfao.py
index 8e1e60b..08ecaee 100644
--- a/views_postprocessing/unfao/managers/unfao.py
+++ b/views_postprocessing/unfao/managers/unfao.py
@@ -67,7 +67,9 @@ def _read_forecast_data(self):
         # Forecast Data
         ensemble_name = self.configs.get("ensemble", None)
         if not ensemble_name:
-            raise ValueError("Ensemble name must be provided in configs with the `ensemble` key for forecasting. Cannot proceed.")
+            err_msg = "Ensemble name must be provided in configs with the `ensemble` key for forecasting. Cannot proceed."
+            logger.error(err_msg)
+            raise ValueError(err_msg)
         
         self.ensemble_path_manager = EnsemblePathManager(ensemble_name_or_path=ensemble_name, validate=False)
         # ensemble_configs = EnsembleManager(
@@ -77,7 +79,9 @@ def _read_forecast_data(self):
         # loa = ensemble_configs.get("level", None)
         loa = "pgm"
         if not loa:
-            raise ValueError("level must be defined in the ensemble configurations (e.g, pgm, cm). Cannot proceed.")
+            err_msg = "level must be defined in the ensemble configurations (e.g, pgm, cm). Cannot proceed."
+            logger.error(err_msg)
+            raise ValueError(err_msg)
         
         # Force it to the correct .env just to be safe
         load_dotenv(dotenv_path=str(self.ensemble_path_manager.dotenv))
@@ -284,7 +288,9 @@ def _check_coverage(self) -> None:
 
     def _save(self) -> list:
         if self._historical_dataset is None or self._forecast_dataset is None:
-            raise ValueError("Datasets could not be initialized properly.")
+            err_msg = "Datasets could not be initialized properly."
+            logger.error(err_msg)
+            raise ValueError(err_msg)
         
         # self._historical_dataset.dataframe.to_parquet(
         #     self._model_path.data_generated / "historical_dataset.parquet"