diff --git a/configs/resident/trip_destination.csv b/configs/resident/trip_destination.csv
index 5e3e890..e381878 100644
--- a/configs/resident/trip_destination.csv
+++ b/configs/resident/trip_destination.csv
@@ -6,7 +6,7 @@ local_dist_nd,,_nd_DIST@nd_skims['DIST'],1,1,1,1,1,1,1,1,1,1
 distance_deviation,distance deviation,_dist_dev@(_od_DIST +_dp_DIST - _op_DIST),1,1,1,1,1,1,1,1,1,1
 dist_deviation_logged,logged deviation distance,"_dist_dev_logged@np.where((_dist_dev > 0), np.log(_dist_dev),0)",1,1,1,1,1,1,1,1,1,1
 #,,,,,,,,,,,,
-util_sizeterm,size term,"@np.log1p(size_terms.get(df.dest_taz, df.purpose)) # sharrow: np.log1p(size_terms['sizearray'])",coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one
+util_sizeterm,size term,"@np.log1p(size_terms.get(df.dest_maz, df.purpose)) # sharrow: np.log1p(size_terms['sizearray'])",coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one
 util_Sampleofalternativescorrectionfactor,Sample of alternatives correction factor,"@np.minimum(np.log(df.pick_count/df.prob), 60)",coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one
 util_Modechoicelogsum,Mode choice logsum,od_logsum + dp_logsum,coef_mode_choice_logsum_mandatory,coef_mode_choice_logsum_mandatory,coef_mode_choice_logsum_mandatory,coef_mode_choice_logsum_maint,coef_mode_choice_logsum_maint,coef_mode_choice_logsum_maint,coef_mode_choice_logsum_discr,coef_mode_choice_logsum_discr,coef_mode_choice_logsum_discr,coef_mode_choice_logsum_discr
 #,,,,,,,,,,,,
diff --git a/configs/resident/trip_destination.yaml b/configs/resident/trip_destination.yaml
index e8c995c..6524041 100644
--- a/configs/resident/trip_destination.yaml
+++ b/configs/resident/trip_destination.yaml
@@ -17,7 +17,7 @@ DEST_CHOICE_SAMPLE_TABLE_NAME: trip_destination_sample
 
 # model-specific logsum-related settings
 TRIP_ORIGIN: origin
-ALT_DEST_COL_NAME: dest_taz
+ALT_DEST_COL_NAME: dest_maz
 PRIMARY_ORIGIN: tour_leg_origin
 PRIMARY_DEST: tour_leg_dest # must be created in preprocessor
 
diff --git a/configs/resident/trip_destination_annotate_alts_preprocessor.csv b/configs/resident/trip_destination_annotate_alts_preprocessor.csv
index 1d94ba6..ff03f08 100644
--- a/configs/resident/trip_destination_annotate_alts_preprocessor.csv
+++ b/configs/resident/trip_destination_annotate_alts_preprocessor.csv
@@ -1,2 +1,2 @@
 Description,Target,Expression
-max micromobility access time at destination,d_microAccTime,"land_use.sort_values(by='MicroAccessTime',ascending=False).drop_duplicates('TAZ',keep='first').set_index('TAZ')['MicroAccessTime'].reindex(df.index)"
+micromobility access time at destination,d_microAccTime,"land_use['MicroAccessTime'].reindex(df.index)"
diff --git a/configs/resident/trip_destination_sample.csv b/configs/resident/trip_destination_sample.csv
index 2a79354..52c1309 100644
--- a/configs/resident/trip_destination_sample.csv
+++ b/configs/resident/trip_destination_sample.csv
@@ -5,8 +5,8 @@ Description,Expression,work,univ,school,escort,shopping,eatout,othmaint,social,o
 ,_od_bikeL@odt_skims['BIKE_LOGSUM'],1,1,1,1,1,1,1,1,1,1
 ,_dp_bikeL@dpt_skims['BIKE_LOGSUM'],1,1,1,1,1,1,1,1,1,1
 #,,,,,,,,,,,
-size term,"@np.log1p(size_terms.get(df.dest_taz, df.purpose)) # sharrow: np.log1p(size_terms['sizearray'])",1,1,1,1,1,1,1,1,1,1
-no attractions,"@size_terms.get(df.dest_taz, df.purpose) == 0 # sharrow: size_terms['sizearray'] == 0",-999,-999,-999,-999,-999,-999,-999,-999,-999,-999
+size term,"@np.log1p(size_terms.get(df.dest_maz, df.purpose)) # sharrow: np.log1p(size_terms['sizearray'])",1,1,1,1,1,1,1,1,1,1
+no attractions,"@size_terms.get(df.dest_maz, df.purpose) == 0 # sharrow: size_terms['sizearray'] == 0",-999,-999,-999,-999,-999,-999,-999,-999,-999,-999
 #,,,,,,,,,,,
 ,"@df.walkTour * (np.where(_od_DIST > df.max_walk_distance,1,0) + np.where(_dp_DIST > df.max_walk_distance,1,0))",-10,-10,-10,-10,-10,-10,-10,-10,-10,-10
 ,@df.walkTour * (_od_DIST  +  _dp_DIST),-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5