diff --git a/docs/src/modules.md b/docs/src/modules.md
index 139b1087..711e0bea 100644
--- a/docs/src/modules.md
+++ b/docs/src/modules.md
@@ -342,6 +342,19 @@ in countries with sub-national data (currently the US and India), the carbon int
 taken from the Ember value for the state hosting the data centre; otherwise the
 country-level Ember value is used.
 
+The figures are keyed by region and year, like [PWUE](#pwue): a line item gets the figure of
+the year it was incurred in, read from its usage date. When Ember has not published that year
+yet (the figures of a year come out in the course of the following one, some series lag
+further), the latest year published for the region is used; rows without a usable date get the
+latest year as well, and usage before 2022, the first year the file carries, gets the 2022
+figure. Ember revises published figures and its most recent year can include estimates, so
+refreshing the file can move past years too.
+
+The figures follow
+[Ember's methodology](https://files.ember-energy.org/public-downloads/ember_electricity_data_methodology.pdf):
+full lifecycle emissions, including upstream methane, supply chain and manufacturing, with all
+gases converted to CO2 equivalent over 100 years.
+
 The data is loaded from `ember/ember_co2_intensity.csv`, which is generated from
 [`cloud_regions.json`](#cloud-region-metadata) — see the scripts under
 [`scripts/`](https://github.com/DigitalPebble/spruce/tree/main/scripts) and the dedicated
@@ -351,7 +364,7 @@ refresh it.
 | | |
 |---|---|
 | **Class** | `com.digitalpebble.spruce.modules.ember.AverageCarbonIntensity` |
-| **Reads** | `region` |
+| **Reads** | `region`, the usage date of the line item |
 | **Writes** | `carbon_intensity` |
 
 ## Stage 4 — Impacts
diff --git a/scripts/README.md b/scripts/README.md
index 23f9bfd5..a6d66398 100644
--- a/scripts/README.md
+++ b/scripts/README.md
@@ -21,7 +21,7 @@ scripts/fix_cloud_regions.sh src/main/resources/cloud_regions.json
 scripts/fetch_ember_co2_intensity.sh src/main/resources/cloud_regions.json
 ```
 
-End result: `src/main/resources/ember/ember_co2_intensity.csv`, columns `provider,region,gCO2_per_kWh`.
+End result: `src/main/resources/ember/ember_co2_intensity.csv`, columns `provider,region,year,gCO2_per_kWh`, one row per region and year from 2022 on.
 
 ## Scripts
 
@@ -71,7 +71,7 @@ Usage: `./fix_cloud_regions.sh [cloud_regions.json]` (no default — pass the pa
 
 ### `fetch_ember_co2_intensity.sh`
 
-Downloads three Ember CSVs and emits one CSV row per keyed cloud region:
+Downloads three Ember CSVs and emits one CSV row per keyed cloud region and year:
 
 - `yearly_full_release_long_format.csv` — per-country power-sector intensity.
 - `us_yearly_full_release_long_format.csv` — per-US-state intensity.
@@ -80,27 +80,30 @@ Downloads three Ember CSVs and emits one CSV row per keyed cloud region:
 Filtering and reduction (all datasets):
 
 - `Unit == "gCO2/kWh"`.
-- Keep only the row with the highest `Year` per ISO3 code / state code.
+- Keep every year from `FROM_YEAR` (2022) on, per ISO3 code / state code.
 - Country rows are further restricted to countries that appear in
   `cloud_regions.json` (one alias: Ember's "United States of America" ↔
   cloud_regions' "United States").
 
 Joining to cloud regions:
 
-- For every keyed region under `aws`/`gcp`/`azure.cloud_regions`, emit
-  `(provider, region_code, gCO2_per_kWh)`.
+- For every keyed region under `aws`/`gcp`/`azure.cloud_regions`, emit one
+  `(provider, region_code, year, gCO2_per_kWh)` row per year.
 - For regions whose country has a sub-national source (US, India),
   reverse-geocode the region's `latitude`/`longitude` via OpenStreetMap
   Nominatim (`zoom=5`, read `address["ISO3166-2-lvl4"]`) to get an ISO
   3166-2 subdivision code (e.g. `US-VA`, `IN-MH`) and use the
   state-level Ember value.
-- If the subdivision can't be resolved (e.g. the coordinates point at DC,
-  which isn't a state) or has no Ember entry, fall back to the
-  country-level value.
-- Nominatim results are cached in `geocode_cache.tsv` (`lat`, `lon`,
-  ISO 3166-2 code). Repeat runs are free; the 1 req/sec rate limit only
-  matters on the first run or when new regions in supported countries
-  appear. Delete the cache to force a refresh.
+- If a region in one of those countries has no coordinates, or Nominatim
+  places its coordinates in no subdivision, or Ember has no figure for that
+  subdivision, the script stops without writing the csv and lists the
+  regions with the reason: each of them would otherwise get the national
+  figure.
+- Resolved subdivisions are cached in `scripts/.geocode_cache` (`lat`,
+  `lon`, ISO 3166-2 code); failed requests are not, so they are retried on
+  the next run. Repeat runs are free; the 1 req/sec rate limit only matters
+  on the first run or when new regions in supported countries appear.
+  Delete the cache to force a refresh.
 - `_unresolved` entries are skipped (no region code to emit).
 
 Sub-national configuration lives in two arrays at the top of the script:
@@ -121,7 +124,7 @@ Usage: `./fetch_ember_co2_intensity.sh [cloud_regions.json] [output.csv]`.
 Environment variables:
 
 - `EMBER_GEOCACHE` — override the geocode cache path (default
-  `./geocode_cache.tsv`).
+  `scripts/.geocode_cache`).
 
 ## Cloud region water data
 
diff --git a/scripts/fetch_ember_co2_intensity.sh b/scripts/fetch_ember_co2_intensity.sh
index 4cd97d66..68dbc451 100755
--- a/scripts/fetch_ember_co2_intensity.sh
+++ b/scripts/fetch_ember_co2_intensity.sh
@@ -8,13 +8,13 @@
 #   - Unit == "gCO2/kWh"
 # Country CSV:
 #   - ISO 3 code non-empty, Area in cloud_regions.json country set.
-#   - One value per ISO3: the row with the highest Year.
+#   - One value per ISO3 and year, from FROM_YEAR on.
 # Sub-national CSVs (US, India):
 #   - State code non-empty.
-#   - One value per state code: the row with the highest Year.
+#   - One value per state code and year, from FROM_YEAR on.
 # Join:
-#   - For every keyed region under aws/gcp/azure.cloud_regions, emit
-#     (provider, region_code, gCO2_per_kWh).
+#   - For every keyed region under aws/gcp/azure.cloud_regions, emit one
+#     (provider, region_code, year, gCO2_per_kWh) row per year.
 #   - For regions in a country with a sub-national source, reverse-geocode
 #     the region's lat/lon via OpenStreetMap Nominatim to get the ISO 3166-2
 #     subdivision code and use the sub-national value. If the subdivision
@@ -25,7 +25,7 @@
 #   - _unresolved entries are skipped (no region code).
 #   - Regions with no country/subdivision match are skipped.
 #
-# Output columns: provider,region,gCO2_per_kWh
+# Output columns: provider,region,year,gCO2_per_kWh
 #
 # Usage:  ./fetch_ember_co2_intensity.sh [cloud_regions.json] [output.csv]
 #
@@ -39,6 +39,9 @@ PROJECT_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
 URL="https://files.ember-energy.org/public-downloads/yearly_full_release_long_format.csv"
 CLOUD_REGIONS="${1:-cloud_regions.json}"
 OUTPUT="${2:-$PROJECT_ROOT/src/main/resources/ember/ember_co2_intensity.csv}"
+# First year of figures to ship. Usage before it gets the figures of this year (see
+# AverageCarbonIntensity); the PUE / WUE file starts the same year.
+FROM_YEAR=2022
 GEO_CACHE="${EMBER_GEOCACHE:-$SCRIPT_DIR/.geocode_cache}"
 NOMINATIM_UA="ember-cloud-region-script/1.0"
 
@@ -76,7 +79,9 @@ tmp_countries="$(mktemp)"
 tmp_lookup="$(mktemp)"
 tmp_sub_lookup="$(mktemp)"
 tmp_sub_csv="$(mktemp)"
-trap 'rm -f "$tmp_csv" "$tmp_countries" "$tmp_lookup" "$tmp_sub_lookup" "$tmp_sub_csv"' EXIT
+tmp_alias="$(mktemp)"
+tmp_out="$(mktemp)"
+trap 'rm -f "$tmp_csv" "$tmp_countries" "$tmp_lookup" "$tmp_sub_lookup" "$tmp_sub_csv" "$tmp_alias" "$tmp_out"' EXIT
 
 echo "Downloading $URL..." >&2
 curl --fail -sSL "$URL" -o "$tmp_csv"
@@ -93,9 +98,9 @@ jq -r '
     | .[]
 ' "$CLOUD_REGIONS" > "$tmp_countries"
 
-# Build country -> latest gCO2/kWh lookup (TSV: country<TAB>value).
-# Canonicalise the one known name mismatch so the join works.
-awk -F',' -v countries_file="$tmp_countries" '
+# Build country -> gCO2/kWh by year lookup (TSV: country<TAB>year<TAB>value),
+# from FROM_YEAR on. Canonicalise the one known name mismatch so the join works.
+awk -F',' -v countries_file="$tmp_countries" -v from="$FROM_YEAR" '
     BEGIN {
         while ((getline line < countries_file) > 0) {
             if (line != "") ok[line] = 1
@@ -104,45 +109,29 @@ awk -F',' -v countries_file="$tmp_countries" '
         if (ok["United States"]) ok["United States of America"] = 1
     }
     NR == 1 { next }
-    $15 == "gCO2/kWh" && $2 != "" && ($1 in ok) {
-        iso = $2
-        year = $3 + 0
-        if (year > best_year[iso]) {
-            best_year[iso] = year
-            best_country[iso] = $1
-            best_value[iso] = $16
-        }
-    }
-    END {
-        for (iso in best_value) {
-            name = best_country[iso]
-            if (name == "United States of America") name = "United States"
-            print name "\t" best_value[iso]
-        }
+    $15 == "gCO2/kWh" && $2 != "" && ($1 in ok) && $3 + 0 >= from {
+        name = $1
+        if (name == "United States of America") name = "United States"
+        print name "\t" $3 "\t" $16
     }
 ' "$tmp_csv" > "$tmp_lookup"
 
-# Build combined sub-national lookup (TSV: ISO_3166-2_code<TAB>value) by
-# pulling each configured source and prefixing bare state codes.
-# Ember sub-national CSVs share a schema: col 4=State code, 6=Year, 10=Unit,
-# 11=Value.
+# Build combined sub-national lookup (TSV: ISO_3166-2_code<TAB>year<TAB>value)
+# by pulling each configured source and prefixing bare state codes.
+# Ember sub-national CSVs share a schema: State code, Year, Unit and Value are
+# the 4th, 6th, 10th and 11th of 13 columns. A state name with a comma
+# ("Washington, D.C.") is quoted and shifts the columns after it, so the fields
+# are counted from the end of the line: the last three columns are Value,
+# YoY absolute change and YoY % change.
 : > "$tmp_sub_lookup"
 for entry in "${SUBNATIONAL[@]}"; do
     IFS='|' read -r sn_country sn_url sn_prefix <<< "$entry"
     echo "Downloading $sn_url..." >&2
     curl --fail -sSL "$sn_url" -o "$tmp_sub_csv"
-    awk -F',' -v prefix="$sn_prefix" '
+    awk -F',' -v prefix="$sn_prefix" -v from="$FROM_YEAR" '
         NR == 1 { next }
-        $10 == "gCO2/kWh" && $4 != "" {
-            code = $4
-            year = $6 + 0
-            if (year > best_year[code]) {
-                best_year[code] = year
-                best_value[code] = $11
-            }
-        }
-        END {
-            for (code in best_value) print prefix code "\t" best_value[code]
+        $(NF-3) == "gCO2/kWh" && $(NF-9) != "" && $(NF-7) + 0 >= from {
+            print prefix $(NF-9) "\t" $(NF-7) "\t" $(NF-2)
         }
     ' "$tmp_sub_csv" >> "$tmp_sub_lookup"
 done
@@ -151,11 +140,10 @@ done
 # even when the two systems use different codes for the same region.
 for alias in "${SUBNATIONAL_ALIASES[@]}"; do
     IFS='|' read -r nom_code ember_code <<< "$alias"
-    val=$(awk -F'\t' -v k="$ember_code" '$1==k {print $2; exit}' "$tmp_sub_lookup")
-    if [[ -n "$val" ]]; then
-        printf '%s\t%s\n' "$nom_code" "$val" >> "$tmp_sub_lookup"
-    fi
+    awk -F'\t' -v k="$ember_code" -v n="$nom_code" -v OFS='\t' '$1 == k {print n, $2, $3}' \
+        "$tmp_sub_lookup" >> "$tmp_alias"
 done
+cat "$tmp_alias" >> "$tmp_sub_lookup"
 
 # Check whether a country has a sub-national source configured.
 has_subnational() {
@@ -168,13 +156,15 @@ has_subnational() {
 }
 
 # Reverse-geocode (lat, lon) -> ISO 3166-2 subdivision code via Nominatim,
-# with caching. Returns empty if no subdivision can be resolved.
+# with caching. Prints the code, or nothing when Nominatim places the point in
+# no subdivision; returns 1 when the request fails. Only resolved codes are
+# cached, so a failed request is retried on the next run.
 touch "$GEO_CACHE"
 geo_to_subdivision() {
     local lat="$1" lon="$2"
     local hit
     hit=$(awk -F'\t' -v lat="$lat" -v lon="$lon" '
-        $1 == lat && $2 == lon { print $3; found=1; exit }
+        $1 == lat && $2 == lon && $3 != "" { print $3; found=1; exit }
         END { if (!found) exit 1 }
     ' "$GEO_CACHE") && { printf '%s' "$hit"; return; }
 
@@ -182,45 +172,53 @@ geo_to_subdivision() {
     local resp code
     resp=$(curl --fail -sSL -A "$NOMINATIM_UA" \
         "https://nominatim.openstreetmap.org/reverse?format=jsonv2&zoom=5&lat=${lat}&lon=${lon}" \
-        2>/dev/null || echo '{}')
+        2>/dev/null) || return 1
     code=$(jq -r '.address["ISO3166-2-lvl4"] // ""' <<< "$resp")
     # Validate shape: "XX-..." where XX is a 2-letter country code.
     if [[ ! "$code" =~ ^[A-Z]{2}-[A-Z0-9]+$ ]]; then code=""; fi
-    printf '%s\t%s\t%s\n' "$lat" "$lon" "$code" >> "$GEO_CACHE"
+    if [[ -n "$code" ]]; then
+        printf '%s\t%s\t%s\n' "$lat" "$lon" "$code" >> "$GEO_CACHE"
+    fi
     printf '%s' "$code"
 }
 
-lookup_value() {
-    awk -F'\t' -v key="$1" -v file="$2" '
-        BEGIN {
-            while ((getline line < file) > 0) {
-                split(line, a, "\t")
-                if (a[1] == key) { print a[2]; exit }
-            }
-        }
-    '
+# Print "year<TAB>value" lines for a key, in year order.
+lookup_years() {
+    awk -F'\t' -v key="$1" '$1 == key { print $2 "\t" $3 }' "$2" | sort -n
 }
 
 mkdir -p "$(dirname "$OUTPUT")"
 
+# Regions of a country with state figures that would get the national figure,
+# each with the reason. The csv is written only when there are none.
+problems=()
+
 # Emit a row per keyed cloud region.
 {
     echo "# https://ember-energy.org/creative-commons/"
     echo "# Creative Commons Attribution Licence (CC-BY-4.0)"
-    echo "#provider,region,gCO2_per_kWh"
+    echo "#provider,region,year,gCO2_per_kWh"
     while IFS=$'\t' read -r provider region country lat lon; do
-        value=""
-        if [[ -n "$lat" && -n "$lon" ]] && has_subnational "$country"; then
-            code=$(geo_to_subdivision "$lat" "$lon")
-            if [[ -n "$code" ]]; then
-                value=$(lookup_value "$code" "$tmp_sub_lookup")
+        years=""
+        if has_subnational "$country"; then
+            if [[ -z "$lat" || -z "$lon" ]]; then
+                problems+=("$provider $region: no coordinates in $CLOUD_REGIONS")
+            elif ! code=$(geo_to_subdivision "$lat" "$lon"); then
+                problems+=("$provider $region: Nominatim request failed for $lat,$lon")
+            elif [[ -z "$code" ]]; then
+                problems+=("$provider $region: no subdivision at $lat,$lon")
+            else
+                years=$(lookup_years "$code" "$tmp_sub_lookup")
+                if [[ -z "$years" ]]; then
+                    problems+=("$provider $region: no Ember figure for $code")
+                fi
             fi
         fi
-        if [[ -z "$value" ]]; then
-            value=$(lookup_value "$country" "$tmp_lookup")
+        if [[ -z "$years" ]]; then
+            years=$(lookup_years "$country" "$tmp_lookup")
         fi
-        if [[ -n "$value" ]]; then
-            echo "$provider,$region,$value"
+        if [[ -n "$years" ]]; then
+            awk -F'\t' -v p="$provider" -v r="$region" '{ print p "," r "," $1 "," $2 }' <<< "$years"
         fi
     done < <(jq -r '
         ["aws","gcp","azure"][] as $p
@@ -228,7 +226,15 @@ mkdir -p "$(dirname "$OUTPUT")"
         | to_entries[]
         | [$p, .key, .value.country, .value.latitude, .value.longitude] | @tsv
     ' "$CLOUD_REGIONS")
-} > "$OUTPUT"
+} > "$tmp_out"
+
+if (( ${#problems[@]} )); then
+    echo "error: these regions would get the national figure instead of their state's:" >&2
+    printf '  %s\n' "${problems[@]}" >&2
+    echo "$OUTPUT left unchanged" >&2
+    exit 1
+fi
+mv "$tmp_out" "$OUTPUT"
 
 rows=$(($(wc -l < "$OUTPUT") - 1))
 echo "Wrote $OUTPUT ($rows rows)" >&2
diff --git a/scripts/fix_cloud_regions.sh b/scripts/fix_cloud_regions.sh
index 6c10bae3..f4156dbd 100755
--- a/scripts/fix_cloud_regions.sh
+++ b/scripts/fix_cloud_regions.sh
@@ -9,6 +9,8 @@
 #     East US 2 at Richmond; East US is actually Ashburn/Sterling).
 #   - Fixes AWS us-east-1 coordinates (upstream points to Washington DC;
 #     the region is actually in Ashburn/Loudoun County, VA).
+#   - Fixes Azure US Gov Virginia coordinates (upstream points to Washington
+#     DC; the region is in Virginia).
 #   - Fixes AWS cn-northwest-1 (upstream labels it "Ningxiang" in Hunan;
 #     the region is in Ningxia, near Yinchuan).
 #   - Fixes AWS ca-central-1 coordinates (upstream points ~50 km west of
@@ -99,6 +101,12 @@ jq '
     | .azure.cloud_regions.eastus.longitude  = "-77.487442"
     | .azure.cloud_regions.eastus.metro_area = "Ashburn"
     | .azure.cloud_regions.eastus.name       = "East US (Ashburn)"
+
+    # US Gov Virginia is in Virginia, not Washington DC. Microsoft names only the
+    # state, so the coordinates are those of Richmond: any point in the state
+    # selects the state figure.
+    | .azure.cloud_regions.usgovvirginia.latitude  = "37.540700"
+    | .azure.cloud_regions.usgovvirginia.longitude = "-77.433654"
 ' "$FILE" > "$tmp"
 
 mv "$tmp" "$FILE"
diff --git a/src/main/java/com/digitalpebble/spruce/RowColumn.java b/src/main/java/com/digitalpebble/spruce/RowColumn.java
index 7d6b41ca..e4fb332c 100644
--- a/src/main/java/com/digitalpebble/spruce/RowColumn.java
+++ b/src/main/java/com/digitalpebble/spruce/RowColumn.java
@@ -99,7 +99,7 @@ public Integer getYear(Row r) {
             return null;
         }
         if (value instanceof java.sql.Timestamp timestamp) {
-            return timestamp.toLocalDateTime().getYear();
+            return timestamp.toInstant().atZone(ZoneOffset.UTC).getYear();
         }
         if (value instanceof java.time.Instant instant) {
             return instant.atZone(ZoneOffset.UTC).getYear();
diff --git a/src/main/java/com/digitalpebble/spruce/UsageDate.java b/src/main/java/com/digitalpebble/spruce/UsageDate.java
new file mode 100644
index 00000000..b11e11f6
--- /dev/null
+++ b/src/main/java/com/digitalpebble/spruce/UsageDate.java
@@ -0,0 +1,39 @@
+// SPDX-License-Identifier: Apache-2.0
+
+package com.digitalpebble.spruce;
+
+import org.apache.spark.sql.Row;
+
+/**
+ * Reads the date a line item was incurred on, whichever column the report carries it in.
+ * Shared by the modules that key their factors by year (PUE / WUE, carbon intensity) so they
+ * agree on which column wins.
+ */
+public final class UsageDate {
+
+    /**
+     * Columns a usage date can be read from, in the order they are probed. All are optional: a
+     * report only carries the ones its provider and format define, and the FOCUS columns exist
+     * but are still null in native reports, where the FOCUS bridge module fills them in later.
+     */
+    private static final RowColumn[] DATE_COLUMNS = {
+            FOCUSColumn.CHARGE_PERIOD_START,
+            CURColumn.LINE_ITEM_USAGE_START_DATE,
+            AzureColumn.DATE,
+            CURColumn.BILLING_PERIOD
+    };
+
+    private UsageDate() {
+    }
+
+    /** Returns the year the line item was incurred in, or null if the row has no usable date. */
+    public static Integer year(Row row) {
+        for (RowColumn column : DATE_COLUMNS) {
+            Integer year = column.getYear(row);
+            if (year != null) {
+                return year;
+            }
+        }
+        return null;
+    }
+}
diff --git a/src/main/java/com/digitalpebble/spruce/modules/PWUE.java b/src/main/java/com/digitalpebble/spruce/modules/PWUE.java
index 9725997c..6d9d066d 100644
--- a/src/main/java/com/digitalpebble/spruce/modules/PWUE.java
+++ b/src/main/java/com/digitalpebble/spruce/modules/PWUE.java
@@ -2,14 +2,11 @@
 
 package com.digitalpebble.spruce.modules;
 
-import com.digitalpebble.spruce.AzureColumn;
-import com.digitalpebble.spruce.CURColumn;
 import com.digitalpebble.spruce.Column;
 import com.digitalpebble.spruce.EnrichmentModule;
-import com.digitalpebble.spruce.FOCUSColumn;
 import com.digitalpebble.spruce.Provider;
-import com.digitalpebble.spruce.RowColumn;
 import com.digitalpebble.spruce.SpruceColumn;
+import com.digitalpebble.spruce.UsageDate;
 import com.digitalpebble.spruce.Utils;
 import org.apache.spark.sql.Row;
 
@@ -62,18 +59,6 @@ public class PWUE implements EnrichmentModule {
     /** Year used for rows with no usable usage date: yields the most recent figures. */
     private static final int LATEST = Integer.MAX_VALUE;
 
-    /**
-     * Columns a usage date can be read from, in the order they are probed. All are optional: a
-     * report only carries the ones its provider and format define, and the FOCUS columns exist
-     * but are still null in native reports, where the FOCUS bridge module fills them in later.
-     */
-    private static final RowColumn[] DATE_COLUMNS = {
-            FOCUSColumn.CHARGE_PERIOD_START,
-            CURColumn.LINE_ITEM_USAGE_START_DATE,
-            AzureColumn.DATE,
-            CURColumn.BILLING_PERIOD
-    };
-
     /** PUE and WUE by year for one CSV key — a region id, or a regex over region ids. */
     private static class Factors implements Serializable {
         /** null when the key is an exact region id rather than a pattern. */
@@ -215,13 +200,8 @@ public void enrich(Row row, Map<Column, Object> enrichedValues) {
 
     /** Returns the year the line item was incurred in, or {@link #LATEST} if it has no date. */
     private static int usageYear(Row row) {
-        for (RowColumn column : DATE_COLUMNS) {
-            Integer year = column.getYear(row);
-            if (year != null) {
-                return year;
-            }
-        }
-        return LATEST;
+        Integer year = UsageDate.year(row);
+        return year != null ? year : LATEST;
     }
 
     private Double lookup(String region, int year, boolean water) {
diff --git a/src/main/java/com/digitalpebble/spruce/modules/ember/AbstractEmberCarbonIntensity.java b/src/main/java/com/digitalpebble/spruce/modules/ember/AbstractEmberCarbonIntensity.java
index d85a1127..f3c62a58 100644
--- a/src/main/java/com/digitalpebble/spruce/modules/ember/AbstractEmberCarbonIntensity.java
+++ b/src/main/java/com/digitalpebble/spruce/modules/ember/AbstractEmberCarbonIntensity.java
@@ -13,6 +13,8 @@
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
+import java.util.NavigableMap;
+import java.util.TreeMap;
 
 import static com.digitalpebble.spruce.SpruceColumn.CARBON_INTENSITY;
 
@@ -22,8 +24,8 @@ public abstract class AbstractEmberCarbonIntensity implements EnrichmentModule {
 
     private static final String DEFAULT_RESOURCE_LOCATION = "ember/ember_co2_intensity.csv";
 
-    // keyed by "provider:region" e.g. "aws:us-east-1"
-    private final Map<String, Double> intensities = new HashMap<>();
+    // keyed by "provider:region" e.g. "aws:us-east-1", then by year
+    private final Map<String, NavigableMap<Integer, Double>> intensities = new HashMap<>();
 
     /** Set via {@link #init(Map, Provider)} — left null on purpose so any call path that
      *  bypasses provider-aware init fails loudly rather than silently using AWS. */
@@ -49,10 +51,11 @@ public void init(Map<String, Object> params) {
                     return;
                 }
                 String[] parts = line.split(",");
-                if (parts.length == 3) {
+                if (parts.length == 4) {
                     String key = parts[0].trim() + ":" + parts[1].trim();
-                    double value = Double.parseDouble(parts[2].trim());
-                    intensities.put(key, value);
+                    int year = Integer.parseInt(parts[2].trim());
+                    double value = Double.parseDouble(parts[3].trim());
+                    intensities.computeIfAbsent(key, k -> new TreeMap<>()).put(year, value);
                 } else {
                     throw new RuntimeException("Invalid ember intensity line: " + line);
                 }
@@ -68,15 +71,28 @@ public Column[] columnsAdded() {
     }
 
     /**
-     * Returns the carbon intensity in gCO2/kWh for the given provider and region,
-     * or null if not found.
+     * Returns the carbon intensity in gCO2/kWh for the given provider and region in that year,
+     * see {@link #forYear} for the years the file does not cover; null if the region is not
+     * found.
      */
-    protected Double getIntensity(Provider provider, String region) {
-        String key = provider.csvKey + ":" + region;
-        Double value = intensities.get(key);
-        if (value == null) {
+    protected Double getIntensity(Provider provider, String region, Integer year) {
+        NavigableMap<Integer, Double> byYear = intensities.get(provider.csvKey + ":" + region);
+        if (byYear == null) {
             log.info("No Ember carbon intensity for {} region {}", provider, region);
+            return null;
         }
-        return value;
+        return forYear(byYear, year);
+    }
+
+    /**
+     * Returns the figure published for that year, else the closest earlier year, else the first
+     * year published; the latest year when the year is null, i.e. the row has no usable date.
+     */
+    static Double forYear(NavigableMap<Integer, Double> byYear, Integer year) {
+        Map.Entry<Integer, Double> entry = year == null ? byYear.lastEntry() : byYear.floorEntry(year);
+        if (entry == null) {
+            entry = byYear.firstEntry();
+        }
+        return entry == null ? null : entry.getValue();
     }
 }
diff --git a/src/main/java/com/digitalpebble/spruce/modules/ember/AverageCarbonIntensity.java b/src/main/java/com/digitalpebble/spruce/modules/ember/AverageCarbonIntensity.java
index 72c2c948..56d26de0 100644
--- a/src/main/java/com/digitalpebble/spruce/modules/ember/AverageCarbonIntensity.java
+++ b/src/main/java/com/digitalpebble/spruce/modules/ember/AverageCarbonIntensity.java
@@ -3,6 +3,7 @@
 package com.digitalpebble.spruce.modules.ember;
 
 import com.digitalpebble.spruce.Column;
+import com.digitalpebble.spruce.UsageDate;
 import org.apache.spark.sql.Row;
 
 import java.util.Map;
@@ -10,7 +11,8 @@
 import static com.digitalpebble.spruce.SpruceColumn.*;
 
 /**
- * Populate the CARBON_INTENSITY field using Ember's cloud region carbon intensity data.
+ * Populate the CARBON_INTENSITY field with Ember's figure for the cloud region and the year the
+ * usage was incurred in.
  */
 public class AverageCarbonIntensity extends AbstractEmberCarbonIntensity {
 
@@ -30,7 +32,7 @@ public void enrich(Row row, Map<Column, Object> enrichedValues) {
             return;
         }
 
-        Double coeff = getIntensity(getProvider(), locationCode);
+        Double coeff = getIntensity(getProvider(), locationCode, UsageDate.year(row));
         if (coeff == null) {
             return;
         }
diff --git a/src/main/resources/cloud_regions.json b/src/main/resources/cloud_regions.json
index abf697c9..f6502670 100644
--- a/src/main/resources/cloud_regions.json
+++ b/src/main/resources/cloud_regions.json
@@ -1516,8 +1516,8 @@
         "zones": "1"
       },
       "usgovvirginia": {
-        "latitude": "38.890370",
-        "longitude": "-77.031959",
+        "latitude": "37.540700",
+        "longitude": "-77.433654",
         "metro_area": "Washington",
         "country": "United States",
         "name": "US Gov Virginia ",
diff --git a/src/main/resources/ember/ember_co2_intensity.csv b/src/main/resources/ember/ember_co2_intensity.csv
index b898465c..74fcbb5f 100644
--- a/src/main/resources/ember/ember_co2_intensity.csv
+++ b/src/main/resources/ember/ember_co2_intensity.csv
@@ -1,160 +1,614 @@
 # https://ember-energy.org/creative-commons/
 # Creative Commons Attribution Licence (CC-BY-4.0)
-#provider,region,gCO2_per_kWh
-aws,ap-southeast-4,525.18
-aws,ap-southeast-2,525.18
-aws,me-south-1,902.24
-aws,sa-east-1,109.95
-aws,ca-west-1,190.72
-aws,ca-central-1,190.72
-aws,cn-north-1,525.34
-aws,ap-east-1,525.34
-aws,cn-northwest-1,525.34
-aws,eu-west-3,41.44
-aws,eu-central-1,329.65
-aws,ap-south-2,679.88
-aws,ap-south-1,658.97
-aws,ap-southeast-3,680.25
-aws,eu-west-1,256.54
-aws,il-central-1,492.69
-aws,eu-south-1,284.78
-aws,ap-northeast-3,477.26
-aws,ap-northeast-1,477.26
-aws,ap-southeast-1,497.09
-aws,af-south-1,699.29
-aws,ap-northeast-2,417.06
-aws,eu-south-2,153.6
-aws,eu-north-1,35.26
-aws,eu-central-2,39.22
-aws,ap-southeast-7,545.74
-aws,me-central-1,467.51
-aws,eu-west-2,217.41
-aws,us-gov-east-1,479.05
-aws,us-east-2,479.05
-aws,us-gov-west-1,184.02
-aws,us-west-1,177.11
-aws,us-west-2,184.02
-aws,us-east-1,384.4
-aws,ap-southeast-6,92.76
-aws,ap-southeast-5,601.97
-aws,mx-central-1,474.02
-aws,ap-east-2,633.21
-gcp,australia-southeast2,525.18
-gcp,australia-southeast1,525.18
-gcp,europe-west1,149.82
-gcp,southamerica-east1,109.95
-gcp,northamerica-northeast1,190.72
-gcp,northamerica-northeast2,190.72
-gcp,southamerica-west1,289.49
-gcp,asia-east2,525.34
-gcp,europe-north1,57.47
-gcp,europe-west9,41.44
-gcp,europe-west10,329.65
-gcp,europe-west3,329.65
-gcp,asia-south1,658.97
-gcp,asia-south2,421.04
-gcp,asia-southeast2,680.25
-gcp,me-west1,492.69
-gcp,europe-west8,284.78
-gcp,europe-west12,284.78
-gcp,asia-northeast2,477.26
-gcp,asia-northeast1,477.26
-gcp,europe-west4,253.56
-gcp,europe-central2,588.6
-gcp,me-central1,581.52
-gcp,me-central2,691.95
-gcp,asia-southeast1,497.09
-gcp,africa-south1,699.29
-gcp,asia-northeast3,417.06
-gcp,europe-southwest1,153.6
-gcp,europe-north2,35.26
-gcp,europe-west6,39.22
-gcp,asia-east1,633.21
-gcp,europe-west2,217.41
-gcp,us-east1,259.37
-gcp,us-east5,479.05
-gcp,us-south1,342.52
-gcp,us-west4,299.02
-gcp,us-west2,177.11
-gcp,us-central1,400.49
-gcp,us-west3,542.89
-gcp,us-west1,184.02
-gcp,us-east4,327.17
-gcp,northamerica-south1,474.02
-gcp,asia-southeast3,545.74
-azure,australiacentral,525.18
-azure,australiacentral2,525.18
-azure,australiasoutheast,525.18
-azure,australiaeast,525.18
-azure,austriaeast,116.91
-azure,belgiumcentral,149.82
-azure,brazilsoutheast,109.95
-azure,brazilsouth,109.95
-azure,canadaeast,190.72
-azure,canadacentral,190.72
-azure,chilecentral,289.49
-azure,chinanorth,525.34
-azure,chinanorth2,525.34
-azure,chinanorth3,525.34
-azure,eastasia,525.34
-azure,chinaeast3,525.34
-azure,chinaeast,525.34
-azure,chinaeast2,525.34
-azure,denmarkeast,114.41
-azure,finlandcentral,57.47
-azure,francesouth,41.44
-azure,francecentral,41.44
-azure,germanynorth,329.65
-azure,germanywestcentral,329.65
-azure,greececentral,315.09
-azure,southindia,493.19
-azure,indiasouthcentral,679.88
-azure,westindia,658.97
-azure,centralindia,658.97
-azure,indonesiacentral,680.25
-azure,northeurope,256.54
-azure,israelcentral,492.69
-azure,italynorth,284.78
-azure,japanwest,477.26
-azure,japaneast,477.26
-azure,malaysiawest,601.97
-azure,mexicocentral,474.02
-azure,westeurope,253.56
-azure,newzealandnorth,92.76
-azure,norwayeast,28.11
-azure,norwaywest,28.11
-azure,polandcentral,588.6
-azure,qatarcentral,581.52
-azure,saudiarabiasouthcentral,691.95
-azure,southeastasia,497.09
-azure,southafricawest,699.29
-azure,southafricanorth,699.29
-azure,koreasouth,417.06
-azure,koreacentral,417.06
-azure,spaincentral,153.6
-azure,swedencentral,35.26
-azure,swedensouth,35.26
-azure,switzerlandwest,39.22
-azure,switzerlandnorth,39.22
-azure,taiwannorth,633.21
-azure,uaecentral,467.51
-azure,uaenorth,467.51
-azure,ukwest,217.41
-azure,uksouth,217.41
-azure,eastus3,317.96
-azure,usgovtexas,342.52
-azure,westcentralus,539.33
-azure,northcentralus,222.41
-azure,centralus,275.36
-azure,usdodwest,275.36
-azure,westus2,124.36
-azure,usgovarizona,282.98
-azure,westus3,282.98
-azure,eastus2,327.17
-azure,usdodeast,327.17
-azure,eastus,327.17
-azure,usseceast,327.17
-azure,southcentralus,342.52
-azure,westus,177.11
-azure,ussecwest,177.11
-azure,usgovvirginia,384.4
+#provider,region,year,gCO2_per_kWh
+aws,ap-southeast-4,2022,578.01
+aws,ap-southeast-4,2023,556.85
+aws,ap-southeast-4,2024,554.01
+aws,ap-southeast-4,2025,524.59
+aws,ap-southeast-2,2022,578.01
+aws,ap-southeast-2,2023,556.85
+aws,ap-southeast-2,2024,554.01
+aws,ap-southeast-2,2025,524.59
+aws,me-south-1,2022,902.75
+aws,me-south-1,2023,902.59
+aws,me-south-1,2024,902.24
+aws,sa-east-1,2022,103.39
+aws,sa-east-1,2023,96.26
+aws,sa-east-1,2024,106.06
+aws,sa-east-1,2025,109.95
+aws,ca-west-1,2022,160.69
+aws,ca-west-1,2023,174.43
+aws,ca-west-1,2024,185.41
+aws,ca-west-1,2025,190.73
+aws,ca-central-1,2022,160.69
+aws,ca-central-1,2023,174.43
+aws,ca-central-1,2024,185.41
+aws,ca-central-1,2025,190.73
+aws,cn-north-1,2022,586.86
+aws,cn-north-1,2023,583.25
+aws,cn-north-1,2024,556.27
+aws,cn-north-1,2025,526.19
+aws,ap-east-1,2022,586.86
+aws,ap-east-1,2023,583.25
+aws,ap-east-1,2024,556.27
+aws,ap-east-1,2025,526.19
+aws,cn-northwest-1,2022,586.86
+aws,cn-northwest-1,2023,583.25
+aws,cn-northwest-1,2024,556.27
+aws,cn-northwest-1,2025,526.19
+aws,eu-west-3,2022,78.55
+aws,eu-west-3,2023,53.26
+aws,eu-west-3,2024,40.49
+aws,eu-west-3,2025,41.45
+aws,eu-central-1,2022,419.74
+aws,eu-central-1,2023,363.59
+aws,eu-central-1,2024,337.12
+aws,eu-central-1,2025,329.65
+aws,ap-south-2,2022,655.89
+aws,ap-south-2,2023,710.49
+aws,ap-south-2,2024,679.88
+aws,ap-south-1,2022,658.3
+aws,ap-south-1,2023,663.23
+aws,ap-south-1,2024,658.97
+aws,ap-southeast-3,2022,676.05
+aws,ap-southeast-3,2023,681.03
+aws,ap-southeast-3,2024,681.11
+aws,eu-west-1,2022,331.16
+aws,eu-west-1,2023,282.5
+aws,eu-west-1,2024,270.91
+aws,eu-west-1,2025,255.9
+aws,il-central-1,2022,583.32
+aws,il-central-1,2023,558.83
+aws,il-central-1,2024,540.55
+aws,il-central-1,2025,492.69
+aws,eu-south-1,2022,377.84
+aws,eu-south-1,2023,323.3
+aws,eu-south-1,2024,281.43
+aws,eu-south-1,2025,284.63
+aws,ap-northeast-3,2022,519.7
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+aws,ap-southeast-1,2022,504.22
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+aws,eu-south-2,2022,217.13
+aws,eu-south-2,2023,169.68
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+aws,eu-south-2,2025,153.56
+aws,eu-north-1,2022,41.03
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+aws,eu-north-1,2024,34.91
+aws,eu-north-1,2025,35.35
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+aws,eu-central-2,2023,34.82
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+aws,eu-central-2,2025,39.22
+aws,ap-southeast-7,2022,561.12
+aws,ap-southeast-7,2023,549.93
+aws,ap-southeast-7,2024,555.38
+aws,ap-southeast-7,2025,546.32
+aws,me-central-1,2022,558.49
+aws,me-central-1,2023,483.79
+aws,me-central-1,2024,467.51
+aws,eu-west-2,2022,254.98
+aws,eu-west-2,2023,235.6
+aws,eu-west-2,2024,216.5
+aws,eu-west-2,2025,217.41
+aws,us-gov-east-1,2022,519.12
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+aws,us-east-2,2024,475.34
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+aws,us-gov-west-1,2022,170.58
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+aws,us-east-1,2022,321.4
+aws,us-east-1,2023,302.97
+aws,us-east-1,2024,322.4
+aws,us-east-1,2025,327.17
+aws,ap-southeast-6,2022,103.12
+aws,ap-southeast-6,2023,87.2
+aws,ap-southeast-6,2024,112.02
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+aws,ap-southeast-5,2022,605.24
+aws,ap-southeast-5,2023,609.11
+aws,ap-southeast-5,2024,601.71
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+aws,mx-central-1,2022,464.38
+aws,mx-central-1,2023,489.05
+aws,mx-central-1,2024,483.14
+aws,mx-central-1,2025,474.02
+aws,ap-east-2,2022,639.96
+aws,ap-east-2,2023,645.32
+aws,ap-east-2,2024,636.23
+aws,ap-east-2,2025,634.07
+gcp,australia-southeast2,2022,578.01
+gcp,australia-southeast2,2023,556.85
+gcp,australia-southeast2,2024,554.01
+gcp,australia-southeast2,2025,524.59
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+gcp,australia-southeast1,2024,554.01
+gcp,australia-southeast1,2025,524.59
+gcp,europe-west1,2022,139.4
+gcp,europe-west1,2023,134.67
+gcp,europe-west1,2024,127.28
+gcp,europe-west1,2025,109.3
+gcp,southamerica-east1,2022,103.39
+gcp,southamerica-east1,2023,96.26
+gcp,southamerica-east1,2024,106.06
+gcp,southamerica-east1,2025,109.95
+gcp,northamerica-northeast1,2022,160.69
+gcp,northamerica-northeast1,2023,174.43
+gcp,northamerica-northeast1,2024,185.41
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+gcp,northamerica-northeast2,2022,160.69
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+gcp,northamerica-northeast2,2025,190.73
+gcp,southamerica-west1,2022,373.9
+gcp,southamerica-west1,2023,304.83
+gcp,southamerica-west1,2024,260.89
+gcp,southamerica-west1,2025,290.51
+gcp,asia-east2,2022,586.86
+gcp,asia-east2,2023,583.25
+gcp,asia-east2,2024,556.27
+gcp,asia-east2,2025,526.19
+gcp,europe-north1,2022,129.97
+gcp,europe-north1,2023,81.33
+gcp,europe-north1,2024,66.75
+gcp,europe-north1,2025,57.47
+gcp,europe-west9,2022,78.55
+gcp,europe-west9,2023,53.26
+gcp,europe-west9,2024,40.49
+gcp,europe-west9,2025,41.45
+gcp,europe-west10,2022,419.74
+gcp,europe-west10,2023,363.59
+gcp,europe-west10,2024,337.12
+gcp,europe-west10,2025,329.65
+gcp,europe-west3,2022,419.74
+gcp,europe-west3,2023,363.59
+gcp,europe-west3,2024,337.12
+gcp,europe-west3,2025,329.65
+gcp,asia-south1,2022,658.3
+gcp,asia-south1,2023,663.23
+gcp,asia-south1,2024,658.97
+gcp,asia-south2,2022,442.37
+gcp,asia-south2,2023,417.71
+gcp,asia-south2,2024,421.04
+gcp,asia-southeast2,2022,676.05
+gcp,asia-southeast2,2023,681.03
+gcp,asia-southeast2,2024,681.11
+gcp,me-west1,2022,583.32
+gcp,me-west1,2023,558.83
+gcp,me-west1,2024,540.55
+gcp,me-west1,2025,492.69
+gcp,europe-west8,2022,377.84
+gcp,europe-west8,2023,323.3
+gcp,europe-west8,2024,281.43
+gcp,europe-west8,2025,284.63
+gcp,europe-west12,2022,377.84
+gcp,europe-west12,2023,323.3
+gcp,europe-west12,2024,281.43
+gcp,europe-west12,2025,284.63
+gcp,asia-northeast2,2022,519.7
+gcp,asia-northeast2,2023,492.6
+gcp,asia-northeast2,2024,483.58
+gcp,asia-northeast2,2025,477.37
+gcp,asia-northeast1,2022,519.7
+gcp,asia-northeast1,2023,492.6
+gcp,asia-northeast1,2024,483.58
+gcp,asia-northeast1,2025,477.37
+gcp,europe-west4,2022,325.61
+gcp,europe-west4,2023,268.17
+gcp,europe-west4,2024,250.72
+gcp,europe-west4,2025,253.56
+gcp,europe-central2,2022,732.53
+gcp,europe-central2,2023,650.86
+gcp,europe-central2,2024,608.36
+gcp,europe-central2,2025,590.8
+gcp,me-central1,2022,596.9
+gcp,me-central1,2023,584.25
+gcp,me-central1,2024,581.69
+gcp,me-central1,2025,581.52
+gcp,me-central2,2022,700.05
+gcp,me-central2,2023,697.31
+gcp,me-central2,2024,691.95
+gcp,asia-southeast1,2022,504.22
+gcp,asia-southeast1,2023,500.87
+gcp,asia-southeast1,2024,498.74
+gcp,asia-southeast1,2025,497.09
+gcp,africa-south1,2022,729.02
+gcp,africa-south1,2023,714.4
+gcp,africa-south1,2024,717.72
+gcp,africa-south1,2025,698.96
+gcp,asia-northeast3,2022,438.11
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+azure,northeurope,2023,282.5
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+azure,newzealandnorth,2023,87.2
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+azure,usgovvirginia,2022,321.4
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diff --git a/src/test/java/com/digitalpebble/spruce/RowColumnTest.java b/src/test/java/com/digitalpebble/spruce/RowColumnTest.java
index e0c276a1..e4395f0d 100644
--- a/src/test/java/com/digitalpebble/spruce/RowColumnTest.java
+++ b/src/test/java/com/digitalpebble/spruce/RowColumnTest.java
@@ -42,6 +42,20 @@ void readsTheYearFromTheRepresentationsTheReportsUse() {
         assertEquals(2025, COLUMN.getYear(row(java.time.Instant.parse("2025-06-15T12:00:00Z"))));
     }
 
+    @Test
+    void bucketsTimestampsByUtcYearWhateverTheJvmTimeZone() {
+        // CUR timestamps are UTC; a JVM west of Greenwich must not push the first hours of a
+        // year into the previous one
+        java.util.TimeZone jvmZone = java.util.TimeZone.getDefault();
+        java.util.TimeZone.setDefault(java.util.TimeZone.getTimeZone("America/Los_Angeles"));
+        try {
+            java.sql.Timestamp newYear = java.sql.Timestamp.from(java.time.Instant.parse("2026-01-01T00:00:00Z"));
+            assertEquals(2026, COLUMN.getYear(row(newYear)));
+        } finally {
+            java.util.TimeZone.setDefault(jvmZone);
+        }
+    }
+
     @Test
     void returnsNullWhenThereIsNoYearToRead() {
         assertNull(COLUMN.getYear(row(null)));
diff --git a/src/test/java/com/digitalpebble/spruce/UsageDateTest.java b/src/test/java/com/digitalpebble/spruce/UsageDateTest.java
new file mode 100644
index 00000000..5ae9d691
--- /dev/null
+++ b/src/test/java/com/digitalpebble/spruce/UsageDateTest.java
@@ -0,0 +1,53 @@
+// SPDX-License-Identifier: Apache-2.0
+
+package com.digitalpebble.spruce;
+
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+import org.junit.jupiter.api.Test;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertNull;
+
+class UsageDateTest {
+
+    private static final StructType SCHEMA = new StructType(new StructField[]{
+            StructField.apply(FOCUSColumn.CHARGE_PERIOD_START.getLabel(), DataTypes.StringType, true, null),
+            StructField.apply(CURColumn.LINE_ITEM_USAGE_START_DATE.getLabel(), DataTypes.StringType, true, null),
+            StructField.apply(CURColumn.BILLING_PERIOD.getLabel(), DataTypes.StringType, true, null)});
+
+    private static Row row(String focusStart, String curStart, String billingPeriod) {
+        return new GenericRowWithSchema(new Object[]{focusStart, curStart, billingPeriod}, SCHEMA);
+    }
+
+    @Test
+    void readsTheYearFromTheFirstDateColumnThatIsFilled() {
+        assertEquals(2025, UsageDate.year(row("2025-03-01T00:00:00Z", "2024-01-01T00:00:00Z", "2023-01")));
+        assertEquals(2024, UsageDate.year(row(null, "2024-01-01T00:00:00Z", "2023-01")));
+        assertEquals(2023, UsageDate.year(row(null, null, "2023-01")));
+    }
+
+    @Test
+    void returnsNullWhenNoDateColumnIsFilled() {
+        assertNull(UsageDate.year(row(null, null, null)));
+    }
+
+    @Test
+    void readsTheAzureDateColumn() {
+        StructType azure = new StructType(new StructField[]{
+                StructField.apply(AzureColumn.DATE.getLabel(), DataTypes.DateType, true, null)});
+        Row row = new GenericRowWithSchema(new Object[]{java.sql.Date.valueOf("2024-06-01")}, azure);
+        assertEquals(2024, UsageDate.year(row));
+    }
+
+    @Test
+    void ignoresColumnsTheReportDoesNotCarry() {
+        StructType curOnly = new StructType(new StructField[]{
+                StructField.apply(CURColumn.LINE_ITEM_USAGE_START_DATE.getLabel(), DataTypes.StringType, true, null)});
+        Row row = new GenericRowWithSchema(new Object[]{"2024-11-05"}, curOnly);
+        assertEquals(2024, UsageDate.year(row));
+    }
+}
diff --git a/src/test/java/com/digitalpebble/spruce/modules/ember/AverageCarbonIntensityTest.java b/src/test/java/com/digitalpebble/spruce/modules/ember/AverageCarbonIntensityTest.java
index 85f2804f..5e727e04 100644
--- a/src/test/java/com/digitalpebble/spruce/modules/ember/AverageCarbonIntensityTest.java
+++ b/src/test/java/com/digitalpebble/spruce/modules/ember/AverageCarbonIntensityTest.java
@@ -2,23 +2,30 @@
 
 package com.digitalpebble.spruce.modules.ember;
 
+import com.digitalpebble.spruce.CURColumn;
 import com.digitalpebble.spruce.Column;
 import com.digitalpebble.spruce.Provider;
-import com.digitalpebble.spruce.Utils;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.StructField;
 import org.apache.spark.sql.types.StructType;
 import org.junit.jupiter.api.BeforeEach;
 import org.junit.jupiter.api.Test;
 
 import java.util.HashMap;
 import java.util.Map;
+import java.util.NavigableMap;
+import java.util.TreeMap;
 
 import static com.digitalpebble.spruce.SpruceColumn.*;
 import static org.junit.jupiter.api.Assertions.*;
 
 class AverageCarbonIntensityTest {
 
+    private static final StructType SCHEMA = new StructType(new StructField[]{
+            StructField.apply(CURColumn.LINE_ITEM_USAGE_START_DATE.getLabel(), DataTypes.StringType, true, null)});
+
     private AverageCarbonIntensity module;
 
     @BeforeEach
@@ -27,88 +34,94 @@ void setUp() {
         module.init(Map.of(), Provider.AWS);
     }
 
+    private static Row row(String usageStart) {
+        return new GenericRowWithSchema(new Object[]{usageStart}, SCHEMA);
+    }
+
+    private Map<Column, Object> enrich(Row row, String region) {
+        Map<Column, Object> enriched = new HashMap<>();
+        enriched.put(ENERGY_USED, 1.0);
+        enriched.put(REGION, region);
+        module.enrich(row, enriched);
+        return enriched;
+    }
+
+    @Test
+    void returnsTheFigureOfTheYear() {
+        // Virginia moved from 322.4 in 2024 to 327.17 in 2025
+        assertEquals(322.4, module.getIntensity(Provider.AWS, "us-east-1", 2024));
+        assertEquals(327.17, module.getIntensity(Provider.AWS, "us-east-1", 2025));
+    }
+
+    @Test
+    void usesTheLatestYearWhenTheYearIsNotPublishedYet() {
+        assertEquals(327.17, module.getIntensity(Provider.AWS, "us-east-1", 2030));
+    }
+
+    @Test
+    void usesTheFirstYearBeforeTheFileStarts() {
+        // the file starts in 2022
+        assertEquals(321.4, module.getIntensity(Provider.AWS, "us-east-1", 2019));
+    }
+
     @Test
-    void awsKnownRegionReturnsIntensity() {
-        assertEquals(384.4, module.getIntensity(Provider.AWS, "us-east-1"));
+    void usesTheLatestYearWithoutAYear() {
+        assertEquals(327.17, module.getIntensity(Provider.AWS, "us-east-1", null));
     }
 
     @Test
-    void awsAnotherRegionReturnsIntensity() {
-        assertEquals(256.54, module.getIntensity(Provider.AWS, "eu-west-1"));
+    void usesTheClosestEarlierYearAcrossAGap() {
+        NavigableMap<Integer, Double> byYear = new TreeMap<>(Map.of(2022, 100.0, 2024, 200.0));
+        assertEquals(100.0, AbstractEmberCarbonIntensity.forYear(byYear, 2023));
     }
 
     @Test
     void gcpKnownRegionReturnsIntensity() {
-        assertEquals(259.37, module.getIntensity(Provider.GOOGLE, "us-east1"));
+        assertEquals(259.37, module.getIntensity(Provider.GOOGLE, "us-east1", 2025));
     }
 
     @Test
     void azureKnownRegionReturnsIntensity() {
-        assertEquals(327.17, module.getIntensity(Provider.AZURE, "eastus"));
+        assertEquals(327.17, module.getIntensity(Provider.AZURE, "eastus", 2025));
     }
 
     @Test
     void unknownRegionReturnsNull() {
-        assertNull(module.getIntensity(Provider.AWS, "us-fake-99"));
+        assertNull(module.getIntensity(Provider.AWS, "us-fake-99", 2025));
     }
 
     @Test
     void wrongProviderReturnsNull() {
         // us-east-1 is valid for AWS but not for GCP
-        assertNull(module.getIntensity(Provider.GOOGLE, "us-east-1"));
+        assertNull(module.getIntensity(Provider.GOOGLE, "us-east-1", 2025));
     }
 
     @Test
-    void enrichSetsCarbonIntensity() {
-        StructType schema = Utils.getSchema(module);
-        Row row = new GenericRowWithSchema(new Object[schema.fields().length], schema);
-
-        Map<Column, Object> enriched = new HashMap<>();
-        enriched.put(ENERGY_USED, 1.0);
-        enriched.put(REGION, "us-east-1");
-
-        module.enrich(row, enriched);
-
-        assertEquals(384.4, enriched.get(CARBON_INTENSITY));
+    void enrichSetsTheCarbonIntensityOfTheUsageYear() {
+        assertEquals(322.4, enrich(row("2024-06-15T00:00:00Z"), "us-east-1").get(CARBON_INTENSITY));
+        assertEquals(327.17, enrich(row("2025-06-15T00:00:00Z"), "us-east-1").get(CARBON_INTENSITY));
     }
 
     @Test
-    void enrichSkipsWhenNoEnergy() {
-        StructType schema = Utils.getSchema(module);
-        Row row = new GenericRowWithSchema(new Object[schema.fields().length], schema);
-
-        Map<Column, Object> enriched = new HashMap<>();
-        enriched.put(REGION, "us-east-1");
-
-        module.enrich(row, enriched);
-
-        assertFalse(enriched.containsKey(CARBON_INTENSITY));
+    void enrichUsesTheLatestYearWithoutADate() {
+        assertEquals(327.17, enrich(row(null), "us-east-1").get(CARBON_INTENSITY));
     }
 
     @Test
     void enrichSkipsWhenNoRegion() {
-        StructType schema = Utils.getSchema(module);
-        Row row = new GenericRowWithSchema(new Object[schema.fields().length], schema);
-
-        Map<Column, Object> enriched = new HashMap<>();
-        enriched.put(ENERGY_USED, 1.0);
-
-        module.enrich(row, enriched);
-
-        assertFalse(enriched.containsKey(CARBON_INTENSITY));
+        assertFalse(enrich(row("2025-06-15T00:00:00Z"), null).containsKey(CARBON_INTENSITY));
     }
 
     @Test
     void enrichSkipsUnknownRegion() {
-        StructType schema = Utils.getSchema(module);
-        Row row = new GenericRowWithSchema(new Object[schema.fields().length], schema);
+        assertFalse(enrich(row("2025-06-15T00:00:00Z"), "us-nowhere-99").containsKey(CARBON_INTENSITY));
+    }
 
+    @Test
+    void enrichSkipsWhenNoEnergy() {
         Map<Column, Object> enriched = new HashMap<>();
-        enriched.put(ENERGY_USED, 1.0);
-        enriched.put(REGION, "us-nowhere-99");
-
-        module.enrich(row, enriched);
-
+        enriched.put(REGION, "us-east-1");
+        module.enrich(row("2025-06-15T00:00:00Z"), enriched);
         assertFalse(enriched.containsKey(CARBON_INTENSITY));
     }
 }