feat(flights): cumulative fuel burned + CO2 emitted per flight

Pre-fix the emissions tooltip only showed the per-hour *rate* — what most
users actually want is the cumulative *amount* burned. This adds running
totals computed by multiplying the model-based rate by the elapsed
observation time since we first saw the airframe.

New module ``flight_observations.py``:
* Tracks first_seen_at + last_seen_at per icao24 hex.
* Re-opens a fresh session when an aircraft is unseen for > 15 min
  (treated as a new flight — landed and took off, or transited a dead
  zone). Prevents the cumulative counter from resetting mid-flight if
  the trail-rendering cache prunes the trail.
* Clamps elapsed time to 24h max so clock skew can't produce comically
  large numbers.
* Pruned every 5 min via a new scheduler job (mirrors ais_prune cadence).

flights.py + military.py emission enrichment now also attaches:
* observed_seconds — how long we've been tracking this airframe.
* fuel_gallons_burned — rate * elapsed_h.
* co2_kg_emitted — rate * elapsed_h.

The existing per-hour rate fields stay in the dict for backward compat
and are shown as small secondary context in the tooltip.

Frontend EmissionsEstimateBlock (NewsFeed.tsx) now prominently shows
the cumulative totals with the rate as smaller context underneath plus
"Observed in flight for Xh Ym". When observed_seconds is 0 (first refresh)
it renders "Just observed · totals will appear on next refresh" instead
of a misleading "0 gal".

12 backend tests cover record/accumulate/reset, the 24h clamp, prune,
case-insensitive key normalization, and end-to-end emission integration
in _classify_and_publish.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backend/services/data_fetcher.py

@@ -777,6 +777,19 @@ def start_scheduler():
         misfire_grace_time=60,
     )
 
+    # Flight observation pruning — drops icao24 → first_seen_at entries we
+    # haven't seen in an hour. Same cadence as AIS prune for symmetry; the
+    # per-tick scan is O(in-flight aircraft) so it's cheap.
+    from services.fetchers.flight_observations import prune as _prune_flight_observations
+    _scheduler.add_job(
+        lambda: _run_task_with_health(_prune_flight_observations, "prune_flight_observations"),
+        "interval",
+        minutes=5,
+        id="flight_observation_prune",
+        max_instances=1,
+        misfire_grace_time=60,
+    )
+
     # AISHub REST fallback — slow polling when the AISStream WebSocket
     # primary is offline. Configurable interval via
     # AISHUB_POLL_INTERVAL_MINUTES env (default 20 min). Operator must