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The Greenhouse Gas Reduction Fund (GGRF) represents an historic investment in climate resilience and equitable economic development in the United States. The GGRF, managed by the U.S. Environmental Protection Agency (EPA), will provide USD 27 billion in grants to state, local, and tribal governments as well as not-for-profit financial institutions to mobilize financing for projects that reduce greenhouse gas (GHG) emissions, particularly where the benefits of such projects flow to low-income and disadvantaged communities (LIDACs). To achieve the dual goals of the GGRF—to reduce emissions and to benefit low income and disadvantaged communities—the EPA, applicants seeking GGRF grants, and the ultimate grant awardees will need data, analysis, and best-practice models to refine their strategies and implement the public resources effectively.

CPI has prepared a data map displaying estimated investment needs in GGRF priority project categories and in each U.S. census tract, in order for the country to reach net zero GHG emissions by 2050. The three priority project categories, applicable to the GGRF’s Clean Communities Investment Accelerator and National Clean Investment Fund, are:

  1. Distributed energy generation and storage,
  2. Net zero emissions buildings, and
  3. Zero-emissions transportation.

These estimates are based on Evolved Energy Research’s Annual Decarbonization Perspective 2023 (ADP 2023). The data map also identifies census tracts that qualify as LIDACs under the GGRF program’s definition. We intend for data map to help GGRF applicants and awardees effectively allocate funding both geographically and across project types. Below, we describe potential uses of the data in more detail, give an overview of the aggregate results of the data analysis, and provide an overview of the methodology used to create the data map.

CPI is also happy to provide access to a datafile containing the full, census tract-level estimates upon request; please contact Chris Grant (chris.grant@cpiglobal.org) and Matthew Solomon (matthew.solomon@cpiglobal.org).

Potential uses of the data map

We see at least three specific use cases for the investment needs data map:

  1. GGRF intermediaries may use it to identify LIDACs in their areas of operations that have high investment needs in GGRF priority project categories.
  2. GGRF intermediaries or coalitions may use it to develop a baseline for allocating any GGRF funding received across geographies and project types. For example, they may use data on investment needs across project types to inform the allocation of GGRF funds in particular census tracts in which they are active.
  3. The Environmental Protection Agency and other federal, state, and local agencies may use the data to align other programs and funding to support the success of the GGRF.

This data map extends our previous estimates of GGRF-related investment needs by covering more technologies that fit within the three GGRF priority project categories and by covering investment needs in Alaska and Hawaii (our earlier estimates only covered the continental United States).  It also complements our analysis and final recommendations on actions to help meet these investment needs: Harnessing the transformative potential of the GGRF.

Overview of results

Our results indicate that nationwide investment needs in GGRF priority project categories add up to USD 9.1 trillion through 2035. Of this amount, USD 2.8 trillion (or 31%) will be needed in census tracts classified as LIDACs—in line with the share of the nation’s population in LIDACs. Zero-emissions transportation accounts for the largest share of total investment needs through 2035 at USD 6.8 trillion nationwide. Investment needs for net zero-emissions buildings totaled USD 1.8 trillion through 2035, and distributed energy generation and storage needs (covering rooftop PV panels and lithium-ion batteries) totaled USD 448 billion. The tables below provide more detail on our estimates.

Estimated national investment needs by LIDAC status (2002 USD)

Estimated national investment needs by LIDAC status

Estimated national investment needs by sector (2022 USD)

Estimated national investment needs by sector It is important to note that these are estimates of gross investment needs in technologies that fall within GGRF priority project categories under a modeled scenario leading to net zero national GHG emissions by 2050. That is, they do not represent the net increase in investment needed to substitute, for example, an electric vehicle for a combustion-engine vehicle or a high-efficiency heat pump for a gas furnace. This is appropriate for use by GGRF intermediaries because the gross cost of any new equipment purchase would need to be financed by a financial intermediary. These estimates are based on the ADP 2023 “Central” scenario, which is a least-cost pathway for net zero by 2050 with the fewest constraints on technologies and resources among the eight scenarios modeled. Therefore, these estimates do not represent the “correct” way for the nation to achieve net zero by 2050 but are rather dependent on the assumptions and judgments made by the ADP 2023 modelers and CPI’s own methodological decisions. Additionally, while the ADP 2023 model optimizes the overall cost of transitioning to net zero, it does not explicitly reflect priorities such as poverty reduction, job creation, or equity—so users of this data map need to rely on their own understanding of these issues when interpreting our estimates. Finally, while these estimates cover many technologies that fall under the three GGRF priority project categories (detailed below), it is possible that certain other types of investment, technology, or project that are not covered by our estimates could be eligible for GGRF support.

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Methodology

As mentioned above, we based our estimates on the ADP 2023’s Central scenario. This scenario models state-level stocks of energy supply and demand technologies economy-wide, at five-year increments, leading to net zero GHG emissions in 2050. To produce our estimates of census tract-level investment needs, we first selected those technologies from the ADP 2023 dataset that fall within the three GGRF priority project categories (detailed below). We then “downscaled” the ADP 2023 state-level stocks for these technologies to the census-tract level based on different factors depending on the technology. Finally, we computed investment needs for each tract, for each five-year period, as the increase in modeled stock for that period multiplied by the price per unit for each technology in each time period (prices were also provided by the ADP 2023 dataset). (Note that estimating required investment based on the difference in stocks between time periods ignores the effects of stock rollover, so our figures are likely to underestimate true gross investment needs, particularly in later years.) Below, we detail the technologies we selected for inclusion under the three GGRF priority project categories, and the methods we used to downscale the ADP 2023 stocks to the census tract level. Distributed energy generation and storage

  • Customer-sited solar: State-level stocks for customer-sited solar in the ADP 2023 dataset are first divided into residential and non-residential components based on the number of single-family residential structures (including manufactured homes) and non-residential structures (including multi-family residential structures, which tend to be significantly larger than single-family structures) in each state, as reported in the FEMA USA Structures dataset; these are then downscaled to the tract level based on each tract’s share of the state total structures for each type. The downscaled estimates are matched to prices for residential and commercial rooftop solar in the ADP 2023 dataset and the resulting investment estimates are reported as “Rooftop PV – residential” and “Rooftop PV – nonresidential”, respectively, in the data map.
  • Li-ion battery storage: These stocks in the ADP 2023 dataset are reported at the zonal level, and are downscaled to the census tract level based on each tract’s share of the total housing units per zone, as reported by the American Community Survey’s 2022 5-year estimates.

Net-zero emissions buildings Commercial buildings technologies All commercial buildings technologies are downscaled to the tract level based on each tract’s share of total commercial structures in the state, which is derived from the FEMA USA Structures and NREL City and County Commercial Building Inventories datasets. ADP 2023 technologies included in this sector are listed below, grouped by subsector.

  • Air conditioning: High efficiency commercial air source heat pump – cooling; High efficiency commercial central air conditioner; High efficiency commercial ground source heat pump – cooling; High efficiency rooftop air conditioner; High efficiency wall/room air conditioner; Reference commercial air source heat pump – cooling; Reference commercial ground source heat pump -cooling.
  • Space heating: High efficiency commercial air source heat pump – heating; High efficiency commercial ground source heat pump – heating; Reference commercial air source heat pump – heating; Reference commercial ground source heat pump – heating.
  • Water heating: Commercial reference heat pump storage water heater; Commercial solar water heater with electric backup.
  • Cooking: Range, electric-induction, 4 burner, oven, 11 inch griddle; Range, electric, 4 burner, oven, 11 inch griddle.
  • Refrigeration: High efficiency commercial beverage merchandisers; High efficiency commercial ice-machines; High efficiency commercial reach-in freezers; High efficiency commercial reach-in refrigerators; High efficiency commercial refrigerated vending machines; High efficiency commercial walk-in freezers; High efficiency commercial walk-in refrigerators; High efficiency supermarket display cases.
  • Ventilation: High efficiency constant air commercial ventilation system; High efficiency variable air commercial ventilation system.

Residential buildings technologies All residential buildings technologies are downscaled to the tract level based on teach tract’s share of the state total housing units, as reported by the American Community Survey’s 2022 5-year estimates. ADP 2023 technologies included in this sector are listed below, grouped by subsector.

  • Air conditioning: High efficiency air source heat pump – cooling; High efficiency central air conditioner; High efficiency geothermal heat pump – cooling; High efficiency room air conditioner; Reference air source heat pump – cooling; Reference geothermal heat pump – cooling.
  • Space heating: Reference air source heat pump – heating; Reference geothermal heat pump – heating.
  • Water heating: Reference electric heat pump water heater; Solar water heater with electric backup.
  • Refrigeration: High efficiency bottom mount refrigerator; High efficiency side mount refrigerator; High efficiency top mount refrigerator.
  • Freezing: High efficiency chest freezer; High efficiency upright freezer.
  • Dishwashing: High efficiency dishwasher.
  • Clothes washing: High efficiency clothes washer – front loading; High efficiency clothes washer – top loading.
  • Clothes drying: High efficiency electric clothes dryer.

Zero-emissions transportation All transportation technologies are downscaled to the tract level based on each tract’s share of the weekday average state total passenger miles traveled, as reported by the BTS Local Area Transportation Characteristics for Households survey for 2019. ADP 2023 technologies included in this sector are listed below, grouped by subsector.

  • Light-duty autos: Electric light-duty auto – 200 mile range; Electric light-duty auto – long range; Hydrogen fuel-cell light-duty auto.
  • Light-duty trucks: Electric light-duty truck – 200 mile range; Electric light-duty truck – long range; Hydrogen fuel-cell light-duty truck.
  • Medium-duty trucks: Battery electric medium-duty vehicle; Hydrogen fuel cell medium-duty vehicle.
  • Heavy-duty trucks: Electric heavy duty vehicle; Hydrogen fcv heavy-duty vehicle.
  • Buses: Electric transit bus; Hydrogen transit bus.

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