All Urban Areas' Energy Use Data Across 640 Indian Districts (AllUrE-India) provides electricity and fossil fuel use in households, industrial manufacturing, transportation, commercial buildings, and agricultural activities across 640 Indian urban districts for the year 2011. A novel top-down and bottom-up method was developed to estimate energy use, in a manner that aligns city-level data with national-level data.
Please cite the data as: Tong, K., Nagpure, A. S. & Ramaswami, A. All urban areas’ energy use data across 640 districts in India for the year 2011. Sci Data, http://doi.org/10.1038/s41597-021-00853-7 (2021).

All Urban Areas' Energy Use Data Across 640 Indian Districts (AllUrE-India) provides electricity and fossil fuel use in households, industrial manufacturing, transportation, commercial buildings, and agricultural activities across 640 Indian urban districts for the year 2011. A novel top-down and bottom-up method was developed to estimate energy use, in a manner that aligns city-level data with national-level data.
Please cite the data as: Tong, K., Nagpure, A. S. & Ramaswami, A. All urban areas’ energy use data across 640 districts in India for the year 2011. Sci Data, http://doi.org/10.1038/s41597-021-00853-7 (2021).

All Urban Areas' Energy Use Data Across 640 Indian Districts (AllUrE-India) provides electricity and fossil fuel use in households, industrial manufacturing, transportation, commercial buildings, and agricultural activities across 640 Indian urban districts for the year 2011. A novel top-down and bottom-up method was developed to estimate energy use, in a manner that aligns city-level data with national-level data.

All Urban Areas' Energy Use Data Across 640 Indian Districts (AllUrE-India) provides data on urban areas' electricity and fossil fuel use in households, industrial sectors, transportation, and commercial buildings and agricultural activities across 640 Indian districts for the year 2011, in a manner that aligns city-level data with national-level data. A novel top-down and bottom-up method was developed to estimate energy use.

AllUrE-India provides data on urban areas' electricity and fossil fuel use in households, industrial sectors, transportation, and commercial buildings and agricultural activities across 640 Indian districts for the year 2011, in a manner that aligns city-level data with national-level data. A novel top-down and bottom-up method was developed to estimate energy use.
Data file will be uploaded soon.

AllUrE-India provides data on urban areas' electricity and fossil fuel use in households, industrial sectors, transportation, and commercial buildings and agricultural activities across 640 Indian districts for the year 2011, in a manner that aligns city-level data with national-level data. A novel top-down and bottom-up method was developed to estimate energy use.

Data file will be uploaded soon.

Table 1. Energy-use benchmarks for the case-study cities. Comparative state-level benchmark shown in [bracket]. (Note: energy-use data: local retrieved from bottom-up data (ICLEI 2010), state retrieved from (EIA 2012); employment statistics: local retrieved from (MIG 2010), state retrieved from (Census 2011); population and households: local retrieved from (MIG 2010), state retrieved from (Census 2011); vehicles miles traveled (VMT): local retrieved from (ICLEI 2010), state retrieved from (FHWA 2008).) Abstract Three broad approaches have emerged for energy and greenhouse gas (GHG) accounting for individual cities: (a) purely in-boundary source-based accounting (IB); (b) community-wide infrastructure GHG emissions footprinting (CIF) incorporating life cycle GHGs (in-boundary plus trans-boundary) of key infrastructures providing water, energy, food, shelter, mobility–connectivity, waste management/sanitation and public amenities to support community-wide activities in cities—all resident, visitor, commercial and industrial activities; and (c) consumption-based GHG emissions footprints (CBF) incorporating life cycle GHGs associated with activities of a sub-set of the community—its final consumption sector dominated by resident households. The latter two activity-based accounts are recommended in recent GHG reporting standards, to provide production-dominated and consumption perspectives of cities, respectively. Little is known, however, on how to normalize and report the different GHG numbers that arise for the same city. We propose that CIF and IB, since they incorporate production, are best reported per unit GDP, while CBF is best reported per capita. Analysis of input–output models of 20 US cities shows that GHG^CIF/GDP is well suited to represent differences in urban energy intensity features across cities, while GHG^CBF/capita best represents variation in expenditures across cities. These results advance our understanding of the methods and metrics used to represent the energy and GHG performance of cities.

Table 2. Summary of different GHG accounting methods, and the correlation of the resulting GHGs normalized indifferent metrics with an aggregate urban energy/carbon intensity index (UEI) of cities. (a) Results for 20 US cities of diverse types, each modeled as a two-region MRIO with GHG intensity of electricity use modeled to vary randomly from ±50% higher or lower compared to the larger economy. (b) Results for the same 20 US cities in a SRIO; all cities have the same electricity GHG intensity as the larger economy. Abstract Three broad approaches have emerged for energy and greenhouse gas (GHG) accounting for individual cities: (a) purely in-boundary source-based accounting (IB); (b) community-wide infrastructure GHG emissions footprinting (CIF) incorporating life cycle GHGs (in-boundary plus trans-boundary) of key infrastructures providing water, energy, food, shelter, mobility–connectivity, waste management/sanitation and public amenities to support community-wide activities in cities—all resident, visitor, commercial and industrial activities; and (c) consumption-based GHG emissions footprints (CBF) incorporating life cycle GHGs associated with activities of a sub-set of the community—its final consumption sector dominated by resident households. The latter two activity-based accounts are recommended in recent GHG reporting standards, to provide production-dominated and consumption perspectives of cities, respectively. Little is known, however, on how to normalize and report the different GHG numbers that arise for the same city. We propose that CIF and IB, since they incorporate production, are best reported per unit GDP, while CBF is best reported per capita. Analysis of input–output models of 20 US cities shows that GHG^CIF/GDP is well suited to represent differences in urban energy intensity features across cities, while GHG^CBF/capita best represents variation in expenditures across cities. These results advance our understanding of the methods and metrics used to represent the energy and GHG performance of cities.

Table 1. Energy-use benchmarks for the case-study cities. Comparative state-level benchmark shown in [bracket]. (Note: energy-use data: local retrieved from bottom-up data (ICLEI 2010), state retrieved from (EIA 2012); employment statistics: local retrieved from (MIG 2010), state retrieved from (Census 2011); population and households: local retrieved from (MIG 2010), state retrieved from (Census 2011); vehicles miles traveled (VMT): local retrieved from (ICLEI 2010), state retrieved from (FHWA 2008).) Abstract Three broad approaches have emerged for energy and greenhouse gas (GHG) accounting for individual cities: (a) purely in-boundary source-based accounting (IB); (b) community-wide infrastructure GHG emissions footprinting (CIF) incorporating life cycle GHGs (in-boundary plus trans-boundary) of key infrastructures providing water, energy, food, shelter, mobility–connectivity, waste management/sanitation and public amenities to support community-wide activities in cities—all resident, visitor, commercial and industrial activities; and (c) consumption-based GHG emissions footprints (CBF) incorporating life cycle GHGs associated with activities of a sub-set of the community—its final consumption sector dominated by resident households. The latter two activity-based accounts are recommended in recent GHG reporting standards, to provide production-dominated and consumption perspectives of cities, respectively. Little is known, however, on how to normalize and report the different GHG numbers that arise for the same city. We propose that CIF and IB, since they incorporate production, are best reported per unit GDP, while CBF is best reported per capita. Analysis of input–output models of 20 US cities shows that GHG^CIF/GDP is well suited to represent differences in urban energy intensity features across cities, while GHG^CBF/capita best represents variation in expenditures across cities. These results advance our understanding of the methods and metrics used to represent the energy and GHG performance of cities.