diff --git a/message_ix/core.py b/message_ix/core.py
index e3b269f6e..32357e578 100644
--- a/message_ix/core.py
+++ b/message_ix/core.py
@@ -261,9 +261,9 @@ def add_par(
         | dict
         | pd.DataFrame
         | None = None,
-        value: float | Iterable[float] | None = None,
-        unit: str | Iterable[str] | None = None,
-        comment: str | Iterable[str] | None = None,
+        value: float | Sequence[float] | None = None,
+        unit: str | Sequence[str] | None = None,
+        comment: str | Sequence[str] | None = None,
     ) -> None:
         # ixmp.Scenario.add_par() is typed as accepting only str, but this method also
         # accepts int for "year"-like dimensions. Proxy the call to avoid type check
diff --git a/message_ix/tools/add_year/__init__.py b/message_ix/tools/add_year/__init__.py
index 92c50d7f9..50cd06364 100644
--- a/message_ix/tools/add_year/__init__.py
+++ b/message_ix/tools/add_year/__init__.py
@@ -829,7 +829,7 @@ def idx_check(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:
                 d_n = slice_df(df_yrs, idx, year_ref, [yr_nn], yr)
             d_n = d_n.loc[d_n.index.isin(d.index), :]
             d = d.loc[d.index.isin(d_n.index), :]
-            d[d.isnull() & d_n.notnull()] = d_n
+            d[d.isnull() & d_n.notnull()] = d_n  # type: ignore [call-overload]
             df2.loc[df2.index.isin(d.index), :] = d
 
         cond1 = df_dur.index <= yr_diff_new[0]
@@ -910,15 +910,15 @@ def idx_check(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:
             )  # type: ignore
             df_yr[np.isinf(df_pre)] = df_pre
 
-            # For those technolofies with one value for each year
+            # For those technologies with one value for each year
             df_to_fill_nans: pd.DataFrame = intpol(
                 df_pre, df_pp.shift(+1, axis=1), year_pre, year_pp, yr
             )  # type: ignore
             df_yr.loc[pd.isna(df_yr[yr])] = df_to_fill_nans.shift(+1, axis=1)
-            df_yr[pd.isna(df_yr)] = df_pre
+            df_yr[pd.isna(df_yr)] = df_pre  # type: ignore [call-overload]
 
             if extrapol_neg:
-                df_yr[(df_yr < 0) & (df_pre >= 0)] = df_pre * extrapol_neg
+                df_yr[(df_yr < 0) & (df_pre >= 0)] = df_pre * extrapol_neg  # type: ignore [call-overload]
             df_yr.loc[:, df_yr.columns < str(yr)] = np.nan
 
         # c) Otherwise, do intrapolation