Values written by ODYM_RECC_Main.py to ODYM_RECC_ModelResultsUUID_.xlsx for the indicators 'In-use stock, pass. vehicles', 'In-use stock, res. buildings', 'In-use stock, nonres. buildings' and the year 2015 are inconsistent. The values reported are based on per capita service demand (model input data) multiplied with (SSP) scenario dependent population data. In case the input data for historic in-use stock, per capita service demand, and 2015 model population data (2_P_RECC_Population_SSP_32R) are not harmonized (which is difficult, because 2015 population already differs across the SSP scenarios), then total in-use stock of pass. vehicles (res. buildings/ nonres. buildings) reported in ODYM_RECC_ModelResultsUUID_.xlsx differs from sum over in-use stocks of pass. vehicle types (res. buildings/ nonres. buildings types), which are reported based on dsm output (and represent input historic in-use stock data for the year 2015).
Values written by ODYM_RECC_Main.py to ODYM_RECC_ModelResultsUUID_.xlsx for the indicators 'In-use stock, pass. vehicles', 'In-use stock, res. buildings', 'In-use stock, nonres. buildings' and the year 2015 are inconsistent. The values reported are based on per capita service demand (model input data) multiplied with (SSP) scenario dependent population data. In case the input data for historic in-use stock, per capita service demand, and 2015 model population data (2_P_RECC_Population_SSP_32R) are not harmonized (which is difficult, because 2015 population already differs across the SSP scenarios), then total in-use stock of pass. vehicles (res. buildings/ nonres. buildings) reported in ODYM_RECC_ModelResultsUUID_.xlsx differs from sum over in-use stocks of pass. vehicle types (res. buildings/ nonres. buildings types), which are reported based on dsm output (and represent input historic in-use stock data for the year 2015).