diff --git a/pipt/misc_tools/analysis_tools.py b/pipt/misc_tools/analysis_tools.py
index a0e4f5d..a1afc0a 100644
--- a/pipt/misc_tools/analysis_tools.py
+++ b/pipt/misc_tools/analysis_tools.py
@@ -551,7 +551,7 @@ def calc_objectivefun(pert_obs, pred_data, Cd):
     """
     #ne = pred_data.shape[1]
     ne = pert_obs.shape[1]
-    r = (pred_data[:, :ne] - pert_obs)  # This is necessary to use to gies code that xilu has implemented
+    r = (pred_data[:, :ne] - pert_obs)  # Only use ne members (gies code has ne+1 predicted data)
     if len(Cd.shape) == 1:
         precission = Cd**(-1)
         data_misfit = np.diag(r.T.dot(r*precission[:, None]))
diff --git a/popt/cost_functions/ecalc_npv.py b/popt/cost_functions/ecalc_npv.py
index bfeded9..f080486 100644
--- a/popt/cost_functions/ecalc_npv.py
+++ b/popt/cost_functions/ecalc_npv.py
@@ -143,7 +143,7 @@ def ecalc_npv(pred_data, **kwargs):
 
         # Save emissions and electrisity usage for later inspection
         np.savez(f'em_values_level{l}.npz', em_values=np.array([em_values]))
-        np.savez(f'el_values_level{l}.npz', em_values=np.array([el_values]))
+        np.savez(f'el_values_level{l}.npz', el_values=np.array([el_values]))
 
         objective[l] = np.array(objective[l]) / npv_const.get('obj_scaling', 1)