5 datasets found
  1. Forecast: Gas Household Ranges, Ovens, Surface Cooking Units and Equipment...

    • reportlinker.com
    Updated Apr 11, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ReportLinker (2024). Forecast: Gas Household Ranges, Ovens, Surface Cooking Units and Equipment Sales in the US 2024 - 2028 [Dataset]. https://www.reportlinker.com/dataset/65d51359bb7fe77748aa8fe0f97bbdc25016defb
    Explore at:
    Dataset updated
    Apr 11, 2024
    Dataset authored and provided by
    ReportLinker
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    Forecast: Gas Household Ranges, Ovens, Surface Cooking Units and Equipment Sales in the US 2024 - 2028 Discover more data with ReportLinker!

  2. d

    Data from: Evaluation of the U.S. Department of Energy Challenge Home...

    • catalog.data.gov
    • data.openei.org
    Updated Nov 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Building Science Corporation (2023). Evaluation of the U.S. Department of Energy Challenge Home Program Certification of Production Builders - Chicago, IL and Devens, MA [Dataset]. https://catalog.data.gov/dataset/evaluation-of-the-u-s-department-of-energy-challenge-home-program-certification-of-product
    Explore at:
    Dataset updated
    Nov 2, 2023
    Dataset provided by
    Building Science Corporation
    Area covered
    Devens, Illinois, United States, Massachusetts, Chicago
    Description

    TO4 Task 3.1 - K Hovnanian Chicago, IL DOE Challenge Home Program Certified Home Constructed and Verified Specifications DOE Challenge Home Building envelope Ceiling R-49 blown fiberglass, Grade I Walls 2x4 framing @ 16 o.c. with R-13 fiberglass batts, Grade I and 1"" R-5 extruded polystyrene (XPS) insulating sheathing Frame Floors R-38 blown fiberglass, Grade I Basement Walls R-19 fiberglass batts draped full height, Grade I Basement Slab uninsulated Windows Above Grade: ENERGY STAR certified, U=0.29, SHGC=0.28 Basement: Non ENERGY STAR certified, U=0.29, SHGC=0.24 Infiltration 2 ACH 50 Mechanical systems Heat 95% AFUE sealed combustion natural gas furnace in conditioned space Goodman GMH950703BXAF Cooling 13 SEER split system Goodman GSX130301BC DHW AO Smith Vertex 100 0.96 EF natural gas tank water heater in 2nd floor utility closet Hot Water Distribution Redesigned trunk and branch Compliant with EPA WaterSense Efficient Distribution Requirements Ducts Located 100% in conditioned space via floor joists leak free to outside (5% or less) Ventilation Central Fan Integrated Supply (CFIS) ventilation with 6"" insulated outside air duct Fan Controller: Air Cycler FRV, with 6"" motorized damper 50 CFM outside air flow, 33% duty cycle (10 minutes on, 20 minutes off); ASHRAE 62.2-2010 compliance via an exhaust fan - Panasonic FV-08VQ5 WhisperCeiling Rerturn Pathways Active Return at Master Bedroom Transfer Grilles in Secondary Bedrooms Appliances, Lighting, MELs Lights 80% ENERGY STAR certified CFL Appliances ENERGY STAR certified refrigerator, dishwasher, and clothes washer; Natural gas range/oven and clothes dryer" STRUCTURE - Test House Lot 145 - 2013 DOE Challenge Test House Task 3.1 Bolingbrook, IL 60490 House is constructed and is DOE Challenge Verified by Don Nelson, a local rater. The purpose of this project was to evaluate integrated packages of advanced measures in individual test homes to assess their performance with respect to Building America Program goals, specifically compliance with the DOE Challenge Home Program. To that end, Building Science Corporation (BSC) consulted on the construction of five test houses by three cold climate production builders in three separate U.S. cities. (1) K. Hovnanian Homes, Chicago, Illinois (2) David Weekley Homes, Denver, Colorado (3) Transformations, Inc., Devens, Massachusetts. Overall, the builders have concluded that the energy related upgrades (either through the prescriptive or performance path) represent reasonable upgrades. The builders commented that while not every improvement in specification was cost effective (as in a reasonable payback period), many were improvements that could improve the marketability of the homes and serve to attract more energy efficiency discerning prospective homeowners. However, the builders did express reservations about the associated checklists and added certifications. An increase in administrative time was observed with all builders. The checklists and certifications also inherently increase cost due to: (1) Adding services to the scope of work for various trades, such as HERS Rater and heating, ventilation, and air conditioning contractor. (2) Increased material costs related to the checklists, especially the U.S. Environmental Protection Agency Indoor airPLUS and WaterSense Efficient Hot Water Distribution requirement. Ceiling - 18" cellulose Walls - 12" open cell spray foam in double stud walls Foundation - R-10 under slab, 3 1/2" closed-cell spray foam at walls Windows - Harvey U=0.20, SHGC=0.22 Infiltration - 1.0 sq in per 100 sq ft Heating - Mini split heat pump, 10.6 HSPF, 23 SEER Cooling - Mini split heat pump, 10.6 HSPF, 23 SEER DHW - 0.97 EF instantaneous propane water heater Ventilation - bathroom exhaust fans as basic option, HRV upgrade option Adams Circle Devens MA 01434 Cavite Street Devens, MA 01434

  3. n

    Data from: Role of vehicle technology on use: Joint analysis of the choice...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Aug 23, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Debapriya Chakraborty (2023). Role of vehicle technology on use: Joint analysis of the choice of plug-in electric vehicle ownership and miles traveled [Dataset]. http://doi.org/10.25338/B8C64G
    Explore at:
    zipAvailable download formats
    Dataset updated
    Aug 23, 2023
    Dataset provided by
    University of California, Davis
    Authors
    Debapriya Chakraborty
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    The increasing diversity of vehicle type holdings and growing demand for BEVs and PHEVs have serious policy implications for travel demand and air pollution. Consequently, it is important to accurately predict or estimate the preference for vehicle holdings of households as well as the vehicle miles traveled by vehicle body and fuel type to project future VMT changes and mobile source emission levels. The current report presents the application of a utility-based model for multiple discreteness that combines multiple vehicle types with usage in an integrated model, specifically the MDCEV model. We use the 2019 California Vehicle Survey data here that allows us to analyze the driving behavior associated with more recent EV models (with potentially longer ranges). Important findings from the model include:

    Household characteristics like size or having children have an expected impact on vehicle preference: larger vehicles are preferred. College education, rooftop solar ownership, and the number of employed workers in a household affect the preference for BEVs and PHEVs in the small car segment dominated by the Leaf, Bolt, Prius-Plug-in and the Volt often used as a commuter car. Among built environment factors, population density and the walkability index of a neighborhood have a statistically significant impact on the type of vehicle choice and VMT. It is observed that a 10% increase in population density reduces the preference for ICEV pickup trucks by 0.34% and VMT by 0.4%. However, if the increase in population density is 25%, the reduction in preference for pickup trucks is 8.4% and VMT is 8.6%. The other built environment factor we consider is the walkability index. If the walkability index of a neighborhood increases by 25%, it reduces the preference for ICEV pickup trucks by 15% and their VMT by 16%. Overall, these results suggest that if policies encourage mixed development of neighborhoods and increase density, it can have an important impact on ownership and usage of gas guzzlers like pickup trucks and help in the process of electrification of the transportation sector.

    Methods The dataset used in this report was created using the following public data sources:

    2019 California Vehicle Survey: "Transportation Secure Data Center." ([2019]). National Renewable Energy Laboratory. Accessed [04/26/2023]: www.nrel.gov/tsdc. The Smart Mapping Tool by EPA: https://www.epa.gov/smartgrowth/smart-location-mapping

    American Community Survey: https://www.census.gov/programs-surveys/acs

  4. f

    Data supporting Fig 2 (supplier).

    • plos.figshare.com
    bin
    Updated Aug 17, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jared Starr; Craig Nicolson; Michael Ash; Ezra M. Markowitz; Daniel Moran (2023). Data supporting Fig 2 (supplier). [Dataset]. http://doi.org/10.1371/journal.pclm.0000190.s017
    Explore at:
    binAvailable download formats
    Dataset updated
    Aug 17, 2023
    Dataset provided by
    PLOS Climate
    Authors
    Jared Starr; Craig Nicolson; Michael Ash; Ezra M. Markowitz; Daniel Moran
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Current policies to reduce greenhouse gas (GHG) emissions and increase adaptation and mitigation funding are insufficient to limit global temperature rise to 1.5°C. It is clear that further action is needed to avoid the worst impacts of climate change and achieve a just climate future. Here, we offer a new perspective on emissions responsibility and climate finance by conducting an environmentally extended input output analysis that links 30 years (1990–2019) of United States (U.S.) household-level income data to the emissions generated in creating that income. To do this we draw on over 2.8 billion inter-sectoral transfers from the Eora MRIO database to calculate both supplier- and producer-based GHG emissions intensities and connect these with detailed income and demographic data for over 5 million U.S. individuals in the IPUMS Current Population Survey. We find significant and growing emissions inequality that cuts across economic and racial lines. In 2019, fully 40% of total U.S. emissions were associated with income flows to the highest earning 10% of households. Among the highest earning 1% of households (whose income is linked to 15–17% of national emissions) investment holdings account for 38–43% of their emissions. Even when allowing for a considerable range of investment strategies, passive income accruing to this group is a major factor shaping the U.S. emissions distribution. Results suggest an alternative income or shareholder-based carbon tax, focused on investments, may have equity advantages over traditional consumer-facing cap-and-trade or carbon tax options and be a useful policy tool to encourage decarbonization while raising revenue for climate finance.

  5. Annual domestic energy bills

    • gov.uk
    • s3.amazonaws.com
    Updated Jun 26, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department for Energy Security and Net Zero (2025). Annual domestic energy bills [Dataset]. https://www.gov.uk/government/statistical-data-sets/annual-domestic-energy-price-statistics
    Explore at:
    Dataset updated
    Jun 26, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Energy Security and Net Zero
    Description

    https://assets.publishing.service.gov.uk/media/685aa12541d77db4f68eb12b/table_221_1_.xlsx">Average annual domestic electricity bills by payment type (QEP 2.2.1)

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute">MS Excel Spreadsheet</span>, <span class="gem-c-attachment_attribute">588 KB</span></p>
    
    
    
    
     <p class="gem-c-attachment_metadata">This file may not be suitable for users of assistive technology.</p>
     <details data-module="ga4-event-tracker" data-ga4-event='{"event_name":"select_content","type":"detail","text":"Request an accessible format.","section":"Request an accessible format.","index_section":1}' class="gem-c-details govuk-details govuk-!-margin-bottom-0" title="Request an accessible format.">
    

    Request an accessible format.

      If you use assistive technology (such as a screen reader) and need a version of this document in a more accessible format, please email <a href="mailto:alt.formats@energysecurity.gov.uk" target="_blank" class="govuk-link">alt.formats@energysecurity.gov.uk</a>. Please tell us what format you need. It will help us if you say what assistive technology you use.
    

    https://assets.publishing.service.gov.uk/media/685aa13245eea7ef2e62074b/table_222_1_.xlsx">Average annual domestic electricity bills for UK countries (QEP 2.2.2)

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute">MS Excel Spreadsheet</span>, <span class="gem-c-attachment_attribute">521 KB</span></p>
    
    
    
    
     <p class="gem-c-attachment_metadata">This file may not be suitable for users of assistive technology.</p>
     <details data-module="ga4-event-tracker" data-ga4-event='{"event_name":"select_content","type":"detail","text":"Request an accessible format.","section":"Request an accessible format.","index_section":1}' class="gem-c-details govuk-details govuk-!-margin-bottom-0" title="Request an accessible format.">
    

    Request an accessible format.

      If you use assistive technology (such as a screen reader) and need a version of this document in a more accessible format, please email <a href="mailto:alt.formats@energysecurity.gov.uk" target="_blank" class="g
    
  6. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
ReportLinker (2024). Forecast: Gas Household Ranges, Ovens, Surface Cooking Units and Equipment Sales in the US 2024 - 2028 [Dataset]. https://www.reportlinker.com/dataset/65d51359bb7fe77748aa8fe0f97bbdc25016defb
Organization logo

Forecast: Gas Household Ranges, Ovens, Surface Cooking Units and Equipment Sales in the US 2024 - 2028

Explore at:
Dataset updated
Apr 11, 2024
Dataset authored and provided by
ReportLinker
License

Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically

Area covered
United States
Description

Forecast: Gas Household Ranges, Ovens, Surface Cooking Units and Equipment Sales in the US 2024 - 2028 Discover more data with ReportLinker!

Search
Clear search
Close search
Google apps
Main menu