diff --git a/packages/domain/src/domain/sap/worksheet/internal_gains.py b/packages/domain/src/domain/sap/worksheet/internal_gains.py
index d93f6584..d26eff8d 100644
--- a/packages/domain/src/domain/sap/worksheet/internal_gains.py
+++ b/packages/domain/src/domain/sap/worksheet/internal_gains.py
@@ -36,6 +36,16 @@ _APPLIANCES_E_A_EXPONENT: Final[float] = 0.4714
 _APPLIANCES_MONTHLY_AMPLITUDE: Final[float] = 0.157
 _APPLIANCES_MONTHLY_PHASE: Final[float] = 1.78
 
+# Appendix L lighting constants.
+_LIGHTING_LAMBDA_B_COEFF: Final[float] = 11.2 * 59.73
+_LIGHTING_LAMBDA_B_EXPONENT: Final[float] = 0.4714
+_LIGHTING_C_L_REF_PER_M2: Final[float] = 330.0
+_LIGHTING_TOPUP_EFFICACY_LM_PER_W: Final[float] = 21.3
+_LIGHTING_PORTABLE_EFFICACY_LM_PER_W: Final[float] = 21.3
+_LIGHTING_INTERNAL_FRACTION: Final[float] = 0.85
+_LIGHTING_MONTHLY_AMPLITUDE: Final[float] = 0.5
+_LIGHTING_MONTHLY_PHASE: Final[float] = 0.2
+
 
 _MONTHS_IN_YEAR: Final[int] = 12
 _DAYS_PER_MONTH: Final[tuple[int, ...]] = (31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31)
@@ -111,6 +121,66 @@ def appliances_monthly_w(
     return tuple(monthly)
 
 
+def lighting_monthly_w(
+    *,
+    total_floor_area_m2: float,
+    n_occupants: float,
+    fixed_lighting_capacity_lm: float,
+    fixed_lighting_efficacy_lm_per_w: float,
+    daylight_factor: float,
+) -> tuple[float, ...]:
+    """SAP 10.2 §5 line (67) — lighting gains in watts per month.
+
+    Applies the full Appendix L L1-L12 cascade with Column A (standard
+    gains) per Table 5. Caller pre-computes:
+      - fixed_lighting_capacity_lm (C_L,fixed, L5a): Σ(count × lumens) over
+        all fixed-lighting outlets. For existing dwellings RdSAP §12-1 gives
+        per-lamp-type defaults (LED 9 W/100 lm/W, CFL 19 W/55 lm/W, LEL
+        15 W/80 lm/W, incandescent 60 W/11.2 lm/W). L5b fallback C_L,fixed
+        = 185 × TFA applies only if no fixed lighting data lodged.
+      - fixed_lighting_efficacy_lm_per_w (ε_fixed, L8): C_L,fixed / Σpower.
+        Fall back to 21.3 lm/W per L8c when no fixed lighting present.
+      - daylight_factor (C_daylight, L2b): C_daylight = 52.2 G_L² - 9.94 G_L
+        + 1.433 for G_L ≤ 0.095, else 0.96. G_L per L2a uses **Table 6d
+        third column (light access factor Z_L), NOT solar Z** — a common
+        source of bias when conflated with the §6 solar calc.
+
+    L12 reduced-gain branch (L12a, used for new-build DPER/TPER) is deferred.
+    """
+    lambda_b = (
+        _LIGHTING_LAMBDA_B_COEFF
+        * (total_floor_area_m2 * n_occupants) ** _LIGHTING_LAMBDA_B_EXPONENT
+    )
+    lambda_req = (2.0 / 3.0) * lambda_b * daylight_factor
+    c_l_ref = _LIGHTING_C_L_REF_PER_M2 * total_floor_area_m2
+    lambda_prov = (
+        lambda_req * fixed_lighting_capacity_lm / c_l_ref if c_l_ref > 0 else 0.0
+    )
+    lambda_topup = max(0.0, lambda_req / 3.0 - lambda_prov)
+    e_l_fixed = (
+        max(lambda_req, lambda_prov) / fixed_lighting_efficacy_lm_per_w
+        if fixed_lighting_efficacy_lm_per_w > 0
+        else 0.0
+    )
+    e_l_topup = lambda_topup / _LIGHTING_TOPUP_EFFICACY_LM_PER_W
+    e_l_portable = (
+        (1.0 / 3.0) * lambda_b * daylight_factor / _LIGHTING_PORTABLE_EFFICACY_LM_PER_W
+    )
+    e_l_annual_kwh = e_l_fixed + e_l_topup + e_l_portable
+    monthly: list[float] = []
+    for m_idx, days in enumerate(_DAYS_PER_MONTH):
+        m = m_idx + 1
+        factor = 1.0 + _LIGHTING_MONTHLY_AMPLITUDE * cos(
+            2.0 * pi * (m - _LIGHTING_MONTHLY_PHASE) / _MONTHS_IN_YEAR
+        )
+        e_l_m_kwh = e_l_annual_kwh * factor * days / _DAYS_PER_YEAR
+        monthly.append(
+            e_l_m_kwh * _LIGHTING_INTERNAL_FRACTION * _KWH_TO_WH
+            / (_HOURS_PER_DAY * days)
+        )
+    return tuple(monthly)
+
+
 def water_heating_gains_monthly_w(
     *,
     heat_gains_from_water_heating_monthly_kwh: tuple[float, ...],
diff --git a/packages/domain/src/domain/sap/worksheet/tests/test_internal_gains.py b/packages/domain/src/domain/sap/worksheet/tests/test_internal_gains.py
index a4a4aafb..487c9e33 100644
--- a/packages/domain/src/domain/sap/worksheet/tests/test_internal_gains.py
+++ b/packages/domain/src/domain/sap/worksheet/tests/test_internal_gains.py
@@ -15,6 +15,7 @@ import pytest
 from domain.sap.worksheet.internal_gains import (
     appliances_monthly_w,
     cooking_monthly_w,
+    lighting_monthly_w,
     losses_monthly_w,
     metabolic_monthly_w,
     water_heating_gains_monthly_w,
@@ -155,3 +156,52 @@ def test_appliances_gains_match_appendix_l13_l14_l16a_for_000490() -> None:
     assert len(monthly) == 12
     for m, (actual, exp) in enumerate(zip(monthly, expected_w)):
         assert actual == pytest.approx(exp, abs=5e-2), f"month {m+1}"
+
+
+def test_lighting_gains_match_appendix_l1_l12_for_000490() -> None:
+    """SAP 10.2 Appendix L L1-L12 cascade — full lighting calculation.
+
+    Steps applied:
+        L1   Λ_B    = 11.2 × 59.73 × (TFA × N)^0.4714                    [klm·h/yr]
+        L3   Λ_req  = (2/3) × Λ_B × C_daylight                            [klm·h/yr]
+        L4   C_L,ref = 330 × TFA                                          [lm]
+        L6   Λ_prov = Λ_req × C_L,fixed / C_L,ref                         [klm·h/yr]
+        L7   Λ_topup = max(0, Λ_req/3 - Λ_prov)                           [klm·h/yr]
+        L9a  E_L,fixed = max(Λ_req, Λ_prov) / ε_fixed                     [kWh/yr]
+        L9b  E_L,topup = Λ_topup / 21.3                                   [kWh/yr]
+        L9c  E_L,portable = (1/3) × Λ_B × C_daylight / 21.3               [kWh/yr]
+        L9d  E_L = E_L,fixed + E_L,topup + E_L,portable                   [kWh/yr]
+        L10  E_L,m = E_L × (1 + 0.5 cos(2π(m-0.2)/12)) × n_m / 365        [kWh/mo]
+        L12  G_L,m = E_L,m × 0.85 × 1000 / (24 × n_m)                     [W]
+
+    Inputs for 000490 (back-derived from the worksheet bulb table and
+    Table 6b/c/d defaults):
+      - 8 LEL bulbs × 80 lm/W × 15 W → C_L,fixed=9600 lm, ε_fixed=80 lm/W
+      - 3 windows (NE 0.81 m² + SE 5.52 m² + NW 2.70 m² = 9.03 m² total),
+        all double-glazed air-filled → g_L=0.80 (Table 6b), PVC frames →
+        FF=0.7 (Table 6c), "Average" overshading → Z_L=0.83 (Table 6d
+        third column, NOT the 0.77 solar-heating column)
+      - G_L = 0.9 × 9.03 × 0.80 × 0.70 × 0.83 / 66.06 = 0.0572 (≤ 0.095)
+      - C_daylight = 52.2 × 0.0572² - 9.94 × 0.0572 + 1.433 = 1.0353
+
+    Verified against worksheet (67)m row to ≤5e-3 W/month (0.14% E_L).
+    """
+    # Arrange
+    expected_w = (
+        24.2665, 21.5533, 17.5283, 13.2701, 9.9195, 8.3745,
+        9.0489, 11.7621, 15.7871, 20.0454, 23.3959, 24.9410,
+    )
+
+    # Act
+    monthly = lighting_monthly_w(
+        total_floor_area_m2=66.06,
+        n_occupants=2.1468,
+        fixed_lighting_capacity_lm=9600.0,
+        fixed_lighting_efficacy_lm_per_w=80.0,
+        daylight_factor=1.0353,
+    )
+
+    # Assert
+    assert len(monthly) == 12
+    for m, (actual, exp) in enumerate(zip(monthly, expected_w)):
+        assert actual == pytest.approx(exp, abs=5e-3), f"month {m+1}"