Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA

doi:10.1016/j.apenergy.2017.09.122

Title: Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA

Full Record
Other Related Research

Authors:: Shi, Wenjing; Ou, Yang; Smith, Steven J.; Ledna, Catherine M.; Nolte, Christopher G.; Loughlin, Daniel H.

Publication Date:: 2017-12-01

Sponsoring Org.:: USDOE

OSTI Identifier:: 1549367

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Applied Energy

Additional Journal Information:: Journal Name: Applied Energy Journal Volume: 208 Journal Issue: C; Journal ID: ISSN 0306-2619

Publisher:: Elsevier

Country of Publication:: United Kingdom

Language:: English

Citation Formats


                    Shi, Wenjing, Ou, Yang, Smith, Steven J., Ledna, Catherine M., Nolte, Christopher G., and Loughlin, Daniel H. Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA.  United Kingdom: N. p., 2017. 
        Web.  doi:10.1016/j.apenergy.2017.09.122.

Copy to clipboard


                    Shi, Wenjing, Ou, Yang, Smith, Steven J., Ledna, Catherine M., Nolte, Christopher G., & Loughlin, Daniel H. Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA.  United Kingdom.  doi:10.1016/j.apenergy.2017.09.122.

Copy to clipboard


                    Shi, Wenjing, Ou, Yang, Smith, Steven J., Ledna, Catherine M., Nolte, Christopher G., and Loughlin, Daniel H. Fri .  
        "Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA".  United Kingdom.  doi:10.1016/j.apenergy.2017.09.122.

Copy to clipboard


                    
@article{osti_1549367,

  title        = {Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA},

  author       = {Shi, Wenjing and Ou, Yang and Smith, Steven J. and Ledna, Catherine M. and Nolte, Christopher G. and Loughlin, Daniel H.},

  abstractNote = {},

  doi          = {10.1016/j.apenergy.2017.09.122},

  journal      = {Applied Energy},

  number       = C,

  volume       = 208,

  place        = {United Kingdom},

  year         = {2017},

  month        = {12}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (Publisher)

Publisher's Version of Record
DOI: 10.1016/j.apenergy.2017.09.122

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 7 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution

Journal Article Ou, Yang ; Shi, Wenjing ; Smith, Steven J. ; ... - Applied Energy
DOI: 10.1016/j.apenergy.2018.02.122
Evaluation of integrated assessment model hindcast experiments: a case study of the GCAM 3.0 land use module

Journal Article Snyder, Abigail C. ; Link, Robert P. ; Calvin, Katherine V. - Geoscientific Model Development (Online)

Abstract. Hindcasting experiments (conducting a model forecast for a time period in which observational data are available) are being undertaken increasingly often by the integrated assessment model (IAM) community, across many scales of models. When they are undertaken, the results are often evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select a set of deviation-based measures that can be applied on different spatial scales (regional versus global) to make evaluating the large number of variable–region combinations in IAMs more tractable. We also identify performance benchmarks for these measures, based on the statistics of themore »« less
DOI: 10.5194/gmd-10-4307-2017
Projecting changes in annual hydropower generation using regional runoff data: An assessment of the United States federal hydropower plants

Journal Article Kao, Shih-Chieh ; Sale, Michael J. ; Ashfaq, Moetasim ; ... - Energy (Oxford)
Cited by 13
DOI: 10.1016/j.energy.2014.11.066
Evaluation of integrated assessment model hindcast experiments: a case study of the GCAM 3.0 land use module

Journal Article Snyder, Abigail C. ; Link, Robert P. ; Calvin, Katherine V. - Geoscientific Model Development (Online)

Hindcasting experiments (conducting a model forecast for a time period in which observational data are available) are being undertaken increasingly often by the integrated assessment model (IAM) community, across many scales of models. When they are undertaken, the results are often evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select a set of deviation-based measures that can be applied on different spatial scales (regional versus global) to make evaluating the large number of variable–region combinations in IAMs more tractable. We also identify performance benchmarks for these measures, based on the statistics of the observationalmore »« less
DOI: 10.5194/gmd-10-4307-2017

Full Text Available
Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution

Journal Article Ou, Yang ; Shi, Wenjing ; Smith, Steven J. ; ... - Applied Energy

There are many technological pathways that can lead to reduced carbon dioxide (CO ₂) emissions. However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessment model with state-level resolution of the U.S. energy system to compare environmental impacts of alternative low-carbon pathways. One set of pathways emphasizes nuclear energy and carbon capture and storage (NUC/CCS), while another set emphasizes renewable energy (RE). These are compared with pathways in which all technologies are available. Air pollutant emissions, mortality costs attributable to particulate matter less thanmore »« less
DOI: 10.1016/j.apenergy.2018.02.122

Similar Records