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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Projected income data under different shared socioeconomic pathways for Washington state

Abstract High-resolution income projections under different Shared Socioeconomic Pathways (SSPs) are essential for the climate change research communities to devise climate change adaptation and mitigation strategies. To generate income projections for Washington state, we obtain state-level GDP per capita projections and convert them into projected annual household income. The resulting state-level income projections are subsequently downscaled to the census block-level based on the Longitudinal Origin-Destination Employment Statistics (LODES) dataset. For accuracy assessment, we downscale historical income data from state- level to block- and block group-level and compare the downscaled results against the actual income data from LODES. County-level accuracy assessment is also conducted based on American Community Survey. The results demonstrate a good agreement (Average R 2 of 0.67, 0.8, and 0.99 for block-, block group-, and county-level, respectively) between the downscaled income data and the reference data, thereby validating the methodology employed. Our approach is applicable to other states for income projections, which can be utilized by a broader audience, including those involved in demographic analysis, economic research, and urban planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Low-Income Energy Affordability Data - LEAD Tool - 2022 Update

The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11. The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below. For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.

AMI↗
DOE OSTI2022

Implications of different income distributions for future residential energy demand in the U.S.

Abstract Future income distribution will affect energy demand and its interactions with various societal priorities. Most future model simulations assume a single average consumer and thus miss this important demand determinant. We quantify long-term implications of alternative future income distributions for state-level residential energy demand, investment, greenhouse gas, and pollutant emission patterns in the United States (U.S.) by incorporating income quintiles into the residential energy sector of the Global Change Analysis Model with 50-state disaggregation. We find that if the income distribution within each U.S. state becomes more egalitarian than present, what means that the difference on income between the richest and poorest decreases over time, residential energy demand could be 10% (4%–14% across states) higher in 2100. This increase of residential energy demand will directly reduce energy poverty, with a very modest increment on economywide CO 2 emissions (1%–2%). On the other hand, if U.S. states transition to a less equitable income distribution than present, with the difference between richest and poorest increasing over time, residential energy demand could be 19% (12%–26% across states) lower. While this study focuses on a single sector, we conclude that to improve understanding of synergies and tradeoffs across multiple societal goals such as energy access, emissions, and investments, future model simulations should explicitly consider subregional income distribution impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Equity implications of net-zero emissions: A multi-model analysis of energy expenditures across income classes under economy-wide deep decarbonization policies

With companies, states, and countries targeting net-zero emissions around midcentury, there are questions about how these targets alter household welfare and finances, including distributional effects across income groups. This paper examines the distributional dimensions of technology transitions and net-zero policies with a focus on welfare impacts across household incomes. The analysis uses a model intercomparison with a range of energy-economy models using harmonized policy scenarios reaching economy-wide, net-zero CO 2 emissions across the United States in 2050. Here we employ a novel linking approach that connects output from detailed energy system models with survey microdata on energy expenditures across income classes to provide distributional analysis of net-zero policies. Although there are differences in model structure and input assumptions, we find broad agreement in qualitative trends in policy incidence and energy burdens across income groups. Models generally agree that direct energy expenditures for many households will likely decline over time with reference and net-zero policies. However, there is variation in the extent of changes relative to current levels, energy burdens relative to reference levels, and electricity expenditures. Policy design, primarily how climate policy revenues are used, has first-order impacts on distributional outcomes. Net-zero policy costs, in both absolute and relative terms, are unevenly distributed across households, and relative increases in energy expenditures are higher for lowest-income households. However, we also find that recycled revenues from climate policies have countervailing effects when rebated on a per-capita basis, offsetting higher energy burdens and potentially even leading to net progressive outcomes. Model results also show carbon Laffer curves, where revenues from net-zero policies increase but then decline with higher stringencies, which can diminish the progressive effects of climate policies. We also illustrate how using annual income deciles for distributional analysis instead of expenditure deciles can overstate the progressivity of emissions policies by overweighting revenue impacts on the lowest-income deciles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Rooftop Energy Potential of Low Income Communities in America REPLICA

The Rooftop Energy Potential of Low Income Communities in America REPLICA data set provides estimates of residential rooftop solar technical potential at the tract-level with emphasis on estimates for Low and Moderate Income LMI populations. In addition to technical potential REPLICA is comprised of 10 additional datasets at the tract-level to provide socio-demographic and market context. The model year vintage of REPLICA is 2015. The LMI solar potential estimates are made at the tract level grouped by Area Median Income AMI income tenure and building type. These estimates are based off of LiDAR data of 128 metropolitan areas statistical modeling and ACS 2011-2015 demographic data. The remaining datasets are supplemental datasets that can be used in conjunction with the technical potential data for general LMI solar analysis planning and policy making. The core dataset is a wide-format CSV file seeds_ii_replica.csv that can be tagged to a tract geometry using the GEOID or GISJOIN fields. In addition users can download geographic shapefiles for the main or supplemental datasets. This dataset was generated as part of the larger NREL-led SEEDSII Solar Energy Evolution and Diffusion Studies project and specifically for the NREL technical report titled Rooftop Solar Technical Potential for Low-to-Moderate Income Households in the United States by Sigrin and Mooney 2018. This dataset is intended to give researchers planners advocates and policy-makers access to credible data to analyze low-income solar issues and potentially perform cost-benefit analysis for program design. To explore the data in an interactive web mapping environment use the NREL SolarForAll app.

14 SOLAR ENERGY↗
DOE OSTI2023

Non-parametric projections of national income distribution consistent with the Shared Socioeconomic Pathways

Understanding and projecting income distributions within countries and regions is important to understanding consumption trends and the distributional consequences of climate impacts and responses. Several global, country-level projections of income distribution are available but most project only the Gini coefficient (a summary statistic of the distribution) or utilize the Gini along with the assumption of a lognormal distribution. We test the lognormal assumption and find that it typically underestimates income in the highest deciles and over-estimates it in others. We find that a new model based on two principal components of national time series data for income distribution provides a better fit to the data for all deciles, especially for the highest and lowest. We also construct a projection model in which the first principal component is driven by the Gini coefficient and the second captures deviations from this relationship. We use the model to project income distribution by decile for all countries for the five shared socioeconomic pathways. We find that inequality is consistently higher than projections based on the Gini and the lognormal functional form, with some countries reaching ratios of the highest to lowest income deciles that are almost three times their value using the lognormal assumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Activating Opportunity Zones for Rapid Solar+Storage Deployment in Low Income Communities (Final Report)

Millions of Texans choose their own power provider, giving them the option to have low-cost and even renewable energy delivered through their retail electric plan. However, Texans with less disposable income often pay more for electricity and have limited access to green energy and emergency backup power even though the costs of solar and wind power are at record lows and continue to decline. The Powered for Good initiative aimed to help deliver clean, affordable, 100% renewable electricity to low-income households in Texas’s Competitive Retail Areas, where households can choose their electricity provider. Objectives: The primary goal of this project was to develop and validate one or more affordable solar+storage products (i.e., priced less than of $0.14/kWh) that Retail Electricity Providers (REP) can offer to LI households. The team achieved three objectives: 1. Investigate how to best reduce electricity costs and increase availability of emergency power for LI customers; 2. Build momentum for, and facilitate an approach to, a Texas-based pilot deployment of such solar+storage products, with a goal of greatly expanding this approach to a large segment of the LI population in Texas; 3. Provide the structural framework, finance model, and roadmap to potentially increase investment of solar+storage projects in LI communities across U.S. states when modified to meet their state-specific laws and regulations. The team evaluated the market of viable solutions for low-income Texans through interviews and focus groups with professionals and residents with lived experience. The team then piloted a low-cost retail electric product. Following the pilot, the team developed educational materials, including fact sheets, a Go Green Save Green interactive guide, and an Electricity Bill Analysis Tool. The team is now working to increase power resilience and reduce energy insecurity with micro solar and storage in partnership with local entities in the Harris County area. Key Findings: Informed by Powered for Good research, including the experiences on Texas residents and electricity system experts, the Powered for Good team developed a pilot that was implemented by Energy Well Texas, a new company formed in late 2020. The pilot featured a combination of a 100% clean residential energy offering delivered through the electrical grid plus a selection of batteries, lights and a solar panel that provided participants with varying levels of backup power. For the 8 customers who submitted previous bills, the Energy Well Texas pilot reduced energy bills by about 30%. In Houston, residents earning less than 30% of Area median Income (AMI) spend an average 13% of their income on energy or about $1,555 per year. Repeating the pilot results for these residents could yield $466 in savings per customer or about 4% of their income. While this will not end energy poverty, it is a big step toward that goal. The Powered for Good and Energy Well Texas teams are currently planning their post-pilot phase of service offerings.

14 SOLAR ENERGY↗
DOE OSTI2016

Imaging analysis of nuclear antiviral factors through direct detection of incoming adenovirus genome complexes

Recent studies involving several viral systems have highlighted the importance of cellular intrinsic defense mechanisms through nuclear antiviral proteins that restrict viral propagation. These factors include among others components of PML nuclear bodies, the nuclear DNA sensor IFI16, and a potential restriction factor PHF13/SPOC1. For several nuclear replicating DNA viruses, it was shown that these factors sense and target viral genomes immediately upon nuclear import. In contrast to the anticipated view, we recently found that incoming adenoviral genomes are not targeted by PML nuclear bodies. Here we further explored cellular responses against adenoviral infection by focusing on specific conditions as well as additional nuclear antiviral factors. In line with our previous findings, we show that neither interferon treatment nor the use of specific isoforms of PML nuclear body components results in co-localization between incoming adenoviral genomes and the subnuclear domains. Furthermore, our imaging analyses indicated that neither IFI16 nor PHF13/SPOC1 are likely to target incoming adenoviral genomes. Thus our findings suggest that incoming adenoviral genomes may be able to escape from a large repertoire of nuclear antiviral mechanisms, providing a rationale for the efficient initiation of lytic replication cycle. - Highlights: • Host nuclear antiviral factors were analyzed upon adenovirus genome delivery. • Interferon treatments fail to permit PML nuclear bodies to target adenoviral genomes. • Neither Sp100A nor B targets adenoviral genomes despite potentially opposite roles. • The nuclear DNA sensor IFI16 does not target incoming adenoviral genomes. • PHF13/SPOC1 targets neither incoming adenoviral genomes nor genome-bound protein VII.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Travel patterns and characteristics of low-income subpopulation in New York state

Studies have shown that people residing in poverty face more mobility challenges in their daily travels as compared to those living in higher income households. In many cities, the lack of a public transportation systems and investments in low-income areas are making it difficult for those living in poverty to access jobs, goods, and services (schools, groceries, health cares, etc. In this study, Oak Ridge National Laboratory was tasked by the New York State (NYS) Department of Transportation to conduct a detailed examination of the travel behaviors and identify patterns and trends of the low-income residents within NYS. The 2009 National Household Travel Survey data was used as the primary information source to analyze subjects associated with poverty and mobility, as well as to address questions such as are there differences in traveler demographics between the low-income population and those of others who live in various NYS regions (e.g., New York City, other urban areas of NYS)? How do they compare with the population at large (e.g., rest of the country) or with findings from previous years (i.e., trend)? Are there any regional differences (e.g., urban versus rural)? Do any unique travel characteristics or patterns exist within the low-income group? Through this study, various key findings on low-income population sizes, household characteristics, travel patterns, and mobility limitations were identified and summarized in this report.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Rooftop Solar Technical Potential for Low-to-Moderate Income Households in the United States

This report presents a first-of-kind assessment of the technical potential of rooftop solar for low and moderate-income households, as well as providing insight on the distribution of solar potential by tenure, income, and other building characteristics. We find that a substantial fraction of the national rooftop solar potential is located on LMI buildings and, for all incomes, a substantial fraction on multi-family and renter-occupied buildings. We also find that rooftop solar can significantly contribute to long-term penetration targets established by the U.S. DOE, though to do so requires deployment on multi-family and renter-occupied buildings. Traditional deployment models have insufficiently enabled access to solar for these income groups and building types. Without innovation either in regulatory, market, or policy factors, a large fraction of the U.S. potential is unlikely to be addressed, as well as leading to inequalities in solar access. Ironically, potential electric bill savings from rooftop solar would have the greatest material impact on the lives of low-income households as compared to their high-income counterparts.

14 SOLAR ENERGY↗
DOE OSTI2018

Rooftop Solar Technical Potential for Low-to-Moderate Income (LMI) Households

This report presents a first-of-kind assessment of the technical potential of rooftop solar for low and moderate-income households, as well as providing insight on the distribution of solar potential by tenure, income, and other building characteristics. We find that a substantial fraction of the national rooftop solar potential is located on LMI buildings and, for all incomes, a substantial fraction on multi-family and renter-occupied buildings. We also find that rooftop solar can significantly contribute to long-term penetration targets established by the U.S. DOE, though to do so requires deployment on multi-family and renter-occupied buildings. Traditional deployment models have insufficiently enabled access to solar for these income groups and building types. Without innovation either in regulatory, market, or policy factors, a large fraction of the U.S. potential is unlikely to be addressed, as well as leading to inequalities in solar access. Ironically, potential electric bill savings from rooftop solar would have the greatest material impact on the lives of low-income households as compared to their high-income counterparts.

14 SOLAR ENERGY↗
DOE OSTI2022

Residential Solar-Adopter Income and Demographic Trends: 2021 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on data for roughly 1.9 million residential rooftop solar systems installed through 2019, representing 82% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: Solar adopters generally skew towards higher incomes, though that trend continues to diminish over time. Solar adopter incomes vary considerably and encompass many low-to-moderate income (LMI) households. Solar-adopter incomes are consistently higher for systems paired with battery storage, for host-owned systems, and for systems installed on single-family homes. Solar adopters differ from the broader U.S. population in terms of a variety of other demographic and socioeconomic measures. State-level comparisons indicate that solar-adopters tend to live in neighborhoods with relatively high non-Hispanic White and Asian populations, and with relatively low Hispanic and Black populations. In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households.

14 SOLAR ENERGY↗
NASA NTRS2010

Why Income Comparison is Rational

A major factor affecting a person s happiness is the gap between their income and their neighbors , independent of their own income. This effect is strongest when the neighbor has moderately higher income. In addition a person s lifetime happiness often follows a "U" shape. Previous models have explained subsets of these phenomena, typically assuming the person has limited ability to assess their own (hedonic) utility. Here I present a model that explains all the phenomena, without such assumptions. In this model greater income of your neighbor is statistical data that, if carefully analyzed, would recommend that you explore for a new income-generating strategy. This explains unhappiness that your neighbor has greater income, as an emotional "prod" that induces you to explore, in accord with careful statistical analysis. It explains the "U" shape of happiness similarly. Another benefit of this model is that it makes many falsifiable predictions.

Wolpert, David H.↗
DOE OSTI2019

Evaluating energy efficiency potential in low-income households: A flexible and granular approach

This study presents a new approach to evaluating energy efficiency potential that provides a more accurate, granular, and flexible estimate of the cost-effective energy efficiency potential in households of various income ranges. Results from this work estimate that in U.S. single-family households with income less than 200% of the federal poverty level, energy efficiency packages tailored to maximize net present value could result in an estimated $13 billion per year in energy cost savings, or $670 per year for an average household, corresponding to about 1 EJ (0.9 quads) of annual primary energy savings. These types of metrics can be estimated for other geographies (regions, states, and counties) and for other ranges of household income. These results can be used by policymakers and program designers to improve the cost-effectiveness of income-qualified programs and to improve the equity of non-income-qualified programs. The results can also be used to understand how energy efficiency opportunities differ between urban and rural areas, as well as how energy efficiency can spur economic development in areas that have had high poverty rates for decades.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Children, Income, and the Impact of Home Delivery on Household Shopping Trips

Expanding e-commerce and delivery benefit consumers through increased flexibility and convenience. However, there is a potential impact on vehicle miles traveled (VMT) by delivery and personal vehicles, and the resulting energy consumption, air quality, and congestion. Delivery trips could replace personal vehicle trips, but, if not a replacement, could add to (or supplement) shopping-related VMT for a given household. Here, we examined the benefits of e-commerce to consumers and the impact on personal shopping trips, and how these differed across item types, household child status, and income. We found that high-income households and households with children cared relatively more about time saving from deliveries. We found that, on average, deliveries substituted for 12% of vehicle shopping trips, but supplemented personal shopping trips for 9% of purchase deliveries. Underlying these averages were two main types of households: those for whom all deliveries substitute for trips (between 55% and 70% of households) and those for whom all deliveries supplement trips (between 20% and 35% of households). There was significant heterogeneity across households with and without children and with high or low incomes with respect to the use of delivery. Although time savings were more likely to motivate higher-income households and households with children to use delivery, this did not translate through to these households substituting for more of their trips; deliveries of prepared meals for both these categories of household were relatively more likely (15% for households with children, and 12% for higher-income households) to supplement, and not substitute for, personal trips.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Can Radiation Therapy Quality Assurance Improve Nasopharyngeal Cancer Outcomes in Low- and Middle-Income Countries: Reporting the First Phase of a Prospective International Atomic Energy Agency Study

Most new nasopharyngeal cancer cases occur in low-income and middle-income countries, and these patients experience poorer overall survival than that of new nasopharyngeal cancer cases in high-income countries. The goal of this research project is to determine whether the introduction of a radiation therapy quality assurance program can ultimately improve outcomes for nasopharyngeal cancer patients in lower-income and middle-income countries. This study reports the results of the first phase of the International Atomic Energy Agency Coordinated Research Project (325-E3-TM-47712).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Mapping Functional Substrate–Enzyme Interactions in the pol β Active Site through Chemical Biology: Structural Responses to Acidity Modification of Incoming dNTPs

We report high-resolution crystal structures of DNA polymerase (pol) β in ternary complex with a panel of incoming dNTPs carrying acidity-modified 5'-triphosphate groups. These novel dNTP analogues have a variety of halomethylene substitutions replacing the bridging oxygen between Pβ and Pγ of the incoming dNTP, whereas other analogues have alkaline substitutions at the bridging oxygen. Use of these analogues allows the first systematic comparison of effects of 5'-triphosphate acidity modification on active site structures and the rate constant of DNA synthesis. These ternary complex structures with incoming dATP, dTTP, and dCTP analogues reveal the enzyme’s active site is not grossly altered by the acidity modifications of the triphosphate group, yet with analogues of all three incoming dNTP bases, subtle structural differences are apparent in interactions around the nascent base pair and at the guanidinium groups of active site arginine residues. Lastly, these results are important for understanding how acidity modification of the incoming dNTP’s 5'-triphosphate can influence DNA polymerase activity and the significance of interactions at arginines 183 and 149 in the active site.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Structural reforms and income distribution: new evidence for OECD countries

Abstract This article examines the impact of labour market and product market reforms on income inequality for 25 OECD countries between 1970 and 2020, using the local projections approach and an updated narrative-based dataset of the reform indicators. Our results suggest that both types of (endogenized) market-oriented reforms increase income inequality, but the effects are small. Consistent with this finding is that counter-reforms lead to less income inequality. Our results also indicate that the inequality-increasing effect of market-oriented reforms is mostly a result of more income going to the top of the income distribution.

Wiese, Rasmus↗