Find elasticities that may not apply to counties or might apply differently to counties; identify what elasticities or data dependencies may create problems, and what strategies these impact for emissions reductions estimations.
Initially known: possible issues with ZTRAX data (used for avg square footage of residential units); residential/non-residential building energy strategies in general may be difficult to calculate emissions reduction estimations for given we don't have res/non-res energy breakdowns for county-level data
Also, land cover data is required for calculating tree planting strategy impacts, unclear if we have/could get that easily for counties and years other than 2018.
Consider whether running CTU data for 2018 numbers and compiling up to county level is an option (complexity for CTUs that are in multiple counties, though not many have substantive housing/commercial activity in more than one county).
Find elasticities that may not apply to counties or might apply differently to counties; identify what elasticities or data dependencies may create problems, and what strategies these impact for emissions reductions estimations.
Initially known: possible issues with ZTRAX data (used for avg square footage of residential units); residential/non-residential building energy strategies in general may be difficult to calculate emissions reduction estimations for given we don't have res/non-res energy breakdowns for county-level data
Also, land cover data is required for calculating tree planting strategy impacts, unclear if we have/could get that easily for counties and years other than 2018.
Consider whether running CTU data for 2018 numbers and compiling up to county level is an option (complexity for CTUs that are in multiple counties, though not many have substantive housing/commercial activity in more than one county).