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GCAM-USA Scenarios for GODEEEP
<h1>GCAM-USA Scenarios for GODEEEP</h1> <p>This dataset contains a set of twelve future (2020-2050) scenarios modeled by <a href="https://gcims.pnnl.gov/modeling/gcam-global-change-analysis-model">GCAM-USA</a> for the <a href="https://godeeep.pnnl.gov">GODEEEP</a> project for the purpose of studying the effects of climate, socioeconomic change, technology change, current decarbonization incentives, and longer-term decarbonization policies on the U.S. energy-economy, the electricity grid, human well-being, and the environment.</p> <p>GCAM-USA is a version of the Global Change Analysis Model (GCAM) with state-level detail in the United States. GCAM-USA simulates the supply/demand dynamics and interactions of four systems (energy, water, agriculture and land use, and the economy) in 32 geopolitical regions in the world, including the 50 states and the District of Columbia within the U.S. It can be configured to include climate impacts on energy demands, water availability, and crop yields. The GCAM-USA scenarios for GODEEEP include business-as-usual (BAU) as well as net-zero (NZ) greenhouse gas emissions by 2050 policy scenarios. All the NZ policy scenarios include a carbon-free electricity system by 2035, also referred to as a "clean grid." Net-zero greenhouse gas emissions by 2050 requires a combination of solutions including carbon sequestration, new fuels, long- and short-term energy storage, and new technologies such as direct air capture that have not previously been included in GCAM-USA. The GCAM-USA scenarios for GODEEEP represent alternative combinations of assumptions for climate impacts, decarbonization policies, decarbonization incentives, and carbon capture and sequestration technology availability.</p> <p>GCAM-USA outputs are provided as XML databases, which can be read by the <a href="https://github.com/JGCRI/modelinterface">GCAM Model Interface</a> or packages such as <a href="https://github.com/JGCRI/gcamreader">gcamreader</a> for Python or <a href="https://github.com/JGCRI/gcamextractor">gcamextractor</a> for R.</p> <p>Summaries of each scenario are provided below. For additional discourse on the scenarios, see <a href="https://doi.org/10.1016/j.egycc.2023.100117">Ou et al 2023</a> and other upcoming papers to be announced on the <a href="https://godeeep.pnnl.gov">GODEEEP website</a>.</p> <h5>Abbreviations used in scenario names and descriptions</h5> <ul> <li><strong>BAU</strong>: Business-As-Usual. These scenarios represent the continuation of policies from the recent past and include major state-level clean energy policies but do not include any federal policies or incentives for a clean grid or a net-zero economy.</li> <li><strong>NZ</strong>: Net-Zero. These scenarios represent a <a href="https://www.whitehouse.gov/wp-content/uploads/2021/10/us-long-term-strategy.pdf">U.S. decarbonization goal</a> that requires a carbon-free electricity grid by 2035 and a net-zero greenhouse gas emissions economy by 2050.</li> <li><strong>IRA</strong>: Inflation Reduction Act. These scenarios include the <a href="https://www.whitehouse.gov/cleanenergy/inflation-reduction-act-guidebook/">IRA incentives</a> for energy efficiency as well as clean energy, transportation, and fuels between 2025 and 2035.</li> <li><strong>CCS</strong>: Carbon Capture and Sequestration. These scenarios assume that electricity generators equipped with CCS technology are available, whereas the other scenarios assume CCS technology is unavailable.</li> <li><strong>Climate</strong>. These scenarios include the dynamic effects of a climate pathway (<a href="https://www.nature.com/articles/s41597-023-02485-5">RCP8.5</a>) on heating and cooling degree days (HDD/CDD) in the period 2020-2050. Note that in scenarios without "climate" in their name, HDD/CDD are left static at their 2020 levels.</li> <li><strong>SSP2</strong>: <a href="https://doi.org/10.1016/j.gloenvcha.2015.01.004">Shared Socioeconomic Pathway 2</a>. A "middle of the road" socioeconomic pathway where population and economic growth trends follow historical patterns.</li> </ul> <h3>Scenario Descriptions</h3> <table> <tbody><tr> <th>#</th> <th>Name</th> <th>Description</th> </tr> </tbody><tbody> <tr> <td>1</td> <td>bau</td> <td> <ul> <li>This scenario does not include any long-term federal policies requiring decarbonization.</li> <li>It does not include the IRA incentives.</li> <li>It assumes that CCS technologies are unavailable.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>No climate impacts are considered.</li> </ul> </td> </tr> <tr> <td>2</td> <td>bau_climate</td> <td> <ul> <li>This scenario does not include any long-term federal policies requiring decarbonization.</li> <li>It does not include the IRA incentives.</li> <li>It assumes that CCS technologies are unavailable.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>This scenario includes future climate impacts on heating and cooling degree days based on an RCP8.5 pathway.</li> </ul> </td> </tr> <tr> <td>3</td> <td>bau_ccs</td> <td> <ul> <li>This scenario does not include any long-term federal policies requiring decarbonization.</li> <li>It does not include the IRA incentives.</li> <li>It assumes that CCS technologies are available.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>No climate impacts are considered.</li> </ul> </td> </tr> <tr> <td>4</td> <td>bau_ccs_climate</td> <td> <ul> <li>This scenario does not include any long-term federal policies requiring decarbonization.</li> <li>It does not include the IRA incentives.</li> <li>It assumes that CCS technologies are available.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>This scenario includes future climate impacts on heating and cooling degree days based on an RCP8.5 pathway.</li> </ul> </td> </tr> <tr> <td>5</td> <td>bau_ira_ccs</td> <td> <ul> <li>This scenario does not include any long-term federal policies requiring decarbonization.</li> <li>It does include the IRA incentives.</li> <li>It assumes that CCS technologies are available.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>No climate impacts are considered.</li> </ul> </td> </tr> <tr> <td>6</td> <td>bau_ira_ccs_climate</td> <td> <ul> <li>This scenario does not include any long-term federal policies requiring decarbonization.</li> <li>It does include the IRA incentives.</li> <li>It assumes that CCS technologies are available.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>This scenario includes future climate impacts on heating and cooling degree days based on an RCP8.5 pathway.</li> </ul> </td> </tr> <tr> <td>7</td> <td>nz</td> <td> <ul> <li>This scenario includes a clean electricity grid in the U.S. by 2035 and a net-zero economy by 2050.</li> <li>It does not include the IRA incentives.</li> <li>It assumes that CCS technologies are unavailable.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>No climate impacts are considered.</li> </ul> </td> </tr> <tr> <td>8</td> <td>nz_climate</td> <td> <ul> <li>This scenario includes a clean electricity grid in the U.S. by 2035 and a net-zero economy by 2050.</li> <li>It does not include the IRA incentives.</li> <li>It assumes that CCS technologies are unavailable.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>This scenario includes future climate impacts on heating and cooling degree days based on an RCP8.5 pathway.</li> </ul> </td> </tr> <tr> <td>9</td> <td>nz_ccs</td> <td> <ul> <li>This scenario includes a clean electricity grid in the U.S. by 2035 and a net-zero economy by 2050.</li> <li>It does not include the IRA incentives.</li> <li>It assumes that CCS technologies are available.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>No climate impacts are considered.</li> </ul> </td> </tr> <tr> <td>10</td> <td>nz_ccs_climate</td> <td> <ul> <li>This scenario includes a clean electricity grid in the U.S. by 2035 and a net-zero economy by 2050.</li> <li>It does not include the IRA incentives.</li> <li>It assumes that CCS technologies are available.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>This scenario includes future climate impacts on heating and cooling degree days based on an RCP8.5 pathway.</li> </ul> </td> </tr> <tr> <td>11</td> <td>nz_ira_ccs</td> <td> <ul> <li>This scenario includes a clean electricity grid in the U.S. by 2035 and a net-zero economy by 2050.</li> <li>It does include the IRA incentives.</li> <li>It assumes that CCS technologies are available.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>No climate impacts are considered.</li> </ul> </td> </tr> <tr> <td>12</td> <td>nz_ira_ccs_climate</td> <td> <ul> <li>This scenario includes a clean electricity grid in the U.S. by 2035 and a net-zero economy by 2050.</li> <li>It does include the IRA incentives.</li> <li>It assumes that CCS technologies are available.</li> <li>The socioeconomic change assumptions are consistent with SSP2.</li> <li>This scenario includes future climate impacts on heating and cooling degree days based on an RCP8.5 pathway.</li> </ul> </td> </tr> </tbody> </table> <h3>Acknowledgement</h3> <p>This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL).</p> <p>PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.</p>
Projecting Residential Energy Consumption across Multiple Income Groups under Decarbonization Scenarios using GCAM-USA
<p>Understanding the residential energy consumption patterns across multiple income groups under decarbonization scenarios is crucial for designing equitable and effective energy policies that address climate change while minimizing disparities. This dataset is developed using an integrated human-Earth system model, supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment at Pacific Northwest National Laboratory (PNNL).</p> <p>GCAM-USA operates within the Global Change Analysis Model, which represents the behavior of, and interactions between, different sectors or systems, including the energy system, the economy, agriculture and land use, water, and the climate. GCAM is one of only a few integrated global human-Earth system models, also known as Integrated Assessment Models (IAMs), which address key processes in inter-linked human and earth systems and provide insights into future global environmental change under alternative scenarios (IAMC, 2022).</p> <p>GCAM has global coverage with varying spatial disaggregation depending on the type of system being modeled. For energy and economy systems, 32 regions across the globe, including the USA as its own region, are modeled in GCAM. GCAM-USA advances with greater spatial detail in the USA region, which includes 50 States plus the District of Columbia (hereinafter “state”). The core operating principle for GCAM and GCAM-USA is market equilibrium. The model solves every market simultaneously at each time step where supply equals demand and prices are endogenous in the model. The official documentation of GCAM and GCAM-USA can be found at: <a href="https://jgcri.github.io/gcam-doc/toc.html">https://jgcri.github.io/gcam-doc/toc.html</a></p> <p>The dataset included in this repository is based on an improved version of GCAM-USA v6, where multiple consumer groups, differentiated by the average income level for 10 population deciles, are represented in the residential building energy sector. As of May 15, 2023, the latest officially released version of GCAM-USA has a single consumer (represented by average GDP <em>per capita</em>) in the residential sector and thus does not include this feature. This multiple-consumer feature is important because (1) demand for residential floorspace and energy are non-linear in income, so modeling more income groups improves the representation of total demand and (2) this feature allows us to explore the distributional effects of policies on these different income groups and the resulting disparity across the groups in terms of residential energy security. If you need more information, please contact the corresponding author.</p> <p>Here, we ran GCAM-USA with the multiple-consumer feature described above under four scenarios over 2015-2045 (Table 1), including two business-as-usual scenarios and two decarbonization scenarios (with and without the impacts of climate change on heating and cooling demand). This repository contains the key output variables related to the residential building energy sector under the four scenarios, including:</p> <ul> <li>income shares by consumer groups at each state over 2015-2045 (Casper et al. 2022)</li> <li>residential energy consumption <em>per capita</em> by service and fuel, by state and income group, 2015-2045</li> <li>residential energy service output (energy consumption * technology efficiency) <em>per capita</em> by service, fuel, and technology, by state and income group, 2015-2045</li> <li>estimated energy burden (Eq.1), by state and income group, 2015-2045</li> <li>residential heating service inequality (Eq.2), by state, 2015-2045</li> </ul> <p> </p> <p><strong>Table 1</strong></p> <table> <thead> <tr> <th scope="col">Scenarios</th> <th scope="col">Policies</th> <th scope="col">Climate Change Impacts</th> </tr> </thead> <tbody> <tr> <td>BAU (Business-as-usual)</td> <td>Existing state-level energy and emission policies</td> <td>Constant HDD/CDD (heating degree days / cooling degree days)</td> </tr> <tr> <td>BAU_climate</td> <td>Existing state-level energy and emission policies</td> <td>Projected state-level HDD/CDD through 2100 under RCP8.5</td> </tr> <tr> <td>NZnoCCS (Net-Zero by 2050 without CCS)</td> <td> <p>Two national targets:</p> <ul> <li>50% net-GHG emission reduction relative to 2005 level and net-zero GHG emissions by 2050</li> <li>US power grid achieves clean-grid by 2035</li> </ul> </td> <td>Constant HDD/CDD</td> </tr> <tr> <td>NZnoCCS_climate</td> <td> <p>Two national targets:</p> <ul> <li>50% net-GHG emission reduction relative to 2005 level and net-zero GHG emissions by 2050</li> <li>US power grid achieves clean-grid by 2035</li> </ul> </td> <td>Projected state-level HDD/CDD through 2100 under RCP8.5</td> </tr> </tbody> </table> <p> </p> <p><strong>Eq. 1</strong></p> <p><span class="math-tex">\(Energy\ burden_i = \dfrac{\sum_j (service\ output_{i,j} * service\ cost_j)}{GDP_i}\)</span></p> <p>for income group<em> i</em> and service <em>j</em></p> <p> </p> <p><strong>Eq. 2</strong></p> <p><strong><span class="math-tex">\(Residential\ heating\ service\ inequality = \dfrac{S_{d10}}{(S_{d1} +S_{d2} + S_{d3} + S_{d4})}\)</span></strong></p> <p>where <em>S</em> is the residential heating service output <em>per capita</em> of the highest income group (<em>d10</em>) divided by the sum of that of the lowest four income groups (<em>d1</em>, <em>d2</em>, <em>d3</em>, and <em>d4</em>), similar to the Palma ratio often used for measuring income inequality. A higher Palma ratio indicates a greater degree of inequality.</p> <p> </p> <p><strong>Reference</strong></p> <p>Casper, Kelly, Narayan, Kanishka B., O'Neill, Brian C., & Waldhoff, Stephanie. 2022. State level income distributions for net income deciles for the US for historical years (2011-2014) and projections for different SSP scenarios (2015-2100) (latest version obtained from the authors on April 6, 2023) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.7227128">https://doi.org/10.5281/zenodo.7227128</a></p> <p>IAMC. 2022. The common Integrated Assessment Model (IAM) documentation [Online]. Integrated Assessment Consortium. Available: https://www.iamcdocumentation.eu/index.php/IAMC_wiki [Accessed May 2023].</p> <p> </p> <p>This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL).</p> <p>PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.</p> <p> </p>
Updated Projections of Residential Energy Consumption across Multiple Income Groups under Decarbonization Scenarios using GCAM-USA
<p>Understanding the residential energy consumption patterns across multiple income groups under decarbonization scenarios is crucial for designing equitable and effective energy policies that address climate change while minimizing disparities. This dataset is developed using an integrated human-Earth system model, supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment at Pacific Northwest National Laboratory (PNNL). Compared to the first version of the dataset (<a href="https://zenodo.org/record/79880387">https://zenodo.org/record/79880387</a>), this updated dataset is based on model runs where the Inflation Reduction Act (IRA) are implemented in the model scenarios. In addition to the queried and post-processed key output variables related to residential energy sector in .csv tables, we also upload the full model output databases in this repository, so that users can query their desired model outputs.</p> <p>GCAM-USA operates within the Global Change Analysis Model (GCAM), which represents the behavior of, and interactions between, different sectors or systems, including the energy system, the economy, agriculture and land use, water, and the climate. GCAM is one of only a few integrated global human-Earth system models, also known as Integrated Assessment Models (IAMs), which address key processes in inter-linked human and earth systems and provide insights into future global environmental change under alternative scenarios (IAMC, 2022).</p> <p>GCAM has global coverage with varying spatial disaggregation depending on the type of system being modeled. For energy and economy systems, 32 regions across the globe, including the USA as its own region, are modeled in GCAM. GCAM-USA advances with greater spatial detail in the USA region, which includes 50 States plus the District of Columbia (hereinafter “state”). The core operating principle for GCAM and GCAM-USA is market equilibrium. The model solves every market simultaneously at each time step where supply equals demand and prices are endogenous in the model. The official documentation of GCAM and GCAM-USA can be found at: <a href="https://jgcri.github.io/gcam-doc/toc.html">https://jgcri.github.io/gcam-doc/toc.html</a>.</p> <p>The dataset included in this repository is based on an improved version of GCAM-USA v6, where multiple consumer groups, differentiated by the average income level for 10 population deciles, are represented in the residential building energy sector. As of September 24, 2023, the latest officially released version of GCAM-USA has a single consumer (represented by average GDP <em>per capita</em>) in the residential sector and thus does not include this feature. This multiple-consumer feature is important because (1) demand for residential floorspace and energy are non-linear in income, so modeling more income groups improves the representation of total demand and (2) this feature allows us to explore the distributional effects of policies on these different income groups and the resulting disparity across the groups in terms of residential energy security. If you need more information, please contact the corresponding author.</p> <p>Here, we ran GCAM-USA with the multiple-consumer feature described above under four scenarios over 2015-2050 (Table 1), including two business-as-usual scenarios and two decarbonization scenarios (with and without the impacts of climate change on heating and cooling demand). This repository contains the full model output databases and key output variables related to the residential energy sector under the four scenarios, including:</p> <ul> <li>income shares by consumer groups at each state over 2015-2050 (Casper et al., 2023)</li> <li>residential energy consumption <em>per capita</em> by service, fuel, state, and income group, 2015-2050</li> <li>residential energy service output (energy consumption * technology efficiency) <em>per capita </em>by service, fuel, state, and income group, 2015-2050</li> <li>estimated energy burden (Eq.1), by state and income group, 2015-2050</li> <li>estimated satiation gap (Eq.2), by service, state, and income group, 2015-2050</li> <li>residential heating service inequality (Eq.3), by state, 2015-2050</li> </ul> <p> </p> <p><strong>Table 1</strong></p> <table> <thead> <tr> <th scope="col">Scenarios</th> <th scope="col">Policies</th> <th scope="col">Climate Change Impacts</th> </tr> </thead> <tbody> <tr> <td>BAU (Business-as-usual)</td> <td>Existing state-level energy and emission policies (including IRA)</td> <td>Constant HDD/CDD (heating degree days / cooling degree days)</td> </tr> <tr> <td>BAU_climate</td> <td>Existing state-level energy and emission policies (including IRA)</td> <td>Projected state-level HDD/CDD through 2100 under RCP8.5</td> </tr> <tr> <td>NZ (Net-Zero by 2050)</td> <td> <p>In addition to BAU, two national targets:</p> <ul> <li>50% net-GHG emission reduction relative to 2005 level and net-zero GHG emissions by 2050</li> <li>US power grid achieves clean-grid by 2035</li> </ul> </td> <td>Constant HDD/CDD</td> </tr> <tr> <td>NZ_climate</td> <td> <p>In addition to BAU, two national targets:</p> <ul> <li>50% net-GHG emission reduction relative to 2005 level and net-zero GHG emissions by 2050</li> <li>US power grid achieves clean-grid by 2035</li> </ul> </td> <td>Projected state-level HDD/CDD through 2100 under RCP8.5</td> </tr> </tbody> </table> <p> </p> <p><strong>Eq. 1</strong></p> <p><span class="math-tex">\(Energy\ burden_{i,k} = \dfrac{\sum_j (service\ output_{i,j,k} * service\ cost_{j,k})}{GDP_{i,k}}\)</span></p> <p>for income group <em>i </em>and state <em>k</em>, that sums over all residential energy services <em>j</em>.</p> <p> </p> <p><strong>Eq. 2</strong></p> <p><span class="math-tex">\(Satiation\ Gap_{i,j,k} = \dfrac{satiation\ level_{j,k} - service\ output_{i,j,k}} {satiation\ level_{j,k}}\)</span></p> <p>for service <em>j</em>, income group <em>i</em>, and state <em>k</em>. Note that the satiation level and service output are per unit of floorspace.</p> <p> </p> <p><strong>Eq. 3</strong></p> <p><strong><span class="math-tex">\(Residential\ heating\ service\ inequality_j = \dfrac{S_j^{d10}}{(S_j^{d1} +S_j^{d2} + S_j^{d3} + S_j^{d4})}\)</span></strong></p> <p>for service <em>j </em>where <em>S</em> is the residential heating service output <em>per capita</em> of the highest income group (<em>d10</em>) divided by the sum of that of the lowest four income groups (<em>d1</em>, <em>d2</em>, <em>d3</em>, and <em>d4</em>), similar to the Palma ratio often used for measuring income inequality. A higher Palma ratio indicates a greater degree of inequality. Among the key output variables in this repository, we provide the residential <em>heating</em> service inequality output table as an example.</p> <p> </p> <p><strong>Reference</strong></p> <p>Casper, K. C., Narayan, K. B., O'Neill, B. C., Waldhoff, S. T., Zhang, Y., & Wejnert-Depue, C. (2023). Non-parametric projections of the net-income distribution for all U.S. states for the shared socioeconomic pathways. <em>Environmental Research Letters</em>. http://iopscience.iop.org/article/10.1088/1748-9326/acf9b8.</p> <p>IAMC. 2022. The common Integrated Assessment Model (IAM) documentation [Online]. Integrated Assessment Consortium. Available: https://www.iamcdocumentation.eu/index.php/IAMC_wiki [Accessed May 2023].</p> <p> </p> <p><strong>Acknowledgement</strong></p> <p>This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL).</p> <p>PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.</p>
GCAM-USA Raw Outputs for Khan et al. 2021 - Evolution of energy-water-agriculture interconnectivity across the U.S.
<p>GCAM-USA outputs for paper: Khan et al. 2021, Evolution of energy-water-agriculture interconnectivity across the U.S.</p>
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