Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

RLINE model algrotihms to account for NO2 near-road chemistry data set - RLINE_N02

Metadata Updated: November 12, 2020

This data set is associated with the results found in the journal article: Valencia et al, 2018. Development and evaluation of the R-LINE model algorithms to account for chemical transformation in the near-road environment. Transportation Research Part D, https://doi.org/10.1016/j.trd.2018.01.028. To address the need to estimate near-road NO2 concentrations, we implemented three different approaches in order of increasing degrees of complexity and barrier to implementation from simplest to more complex. The first is an empirical approach based upon fitting a 4th order polynomial to existing near-road observations across the continental U.S., the second involves a simplified Two-reaction chemical scheme, and the third involves a more detailed set of chemical reactions based upon the Generic Reaction Set (GRS) mechanism. All models were able to estimate more than 75% of concentrations within a factor of two of the near-road monitoring data and produced comparable performance statistics. These results indicate that the performance of the new R-LINE chemistry algorithms for predicting NO2 is comparable to other models (i.e. ADMS-Roads with GRS), both showing less than±15% fractional bias and less than 45% normalized mean square error.

This dataset is associated with the following publication: Valencia, A., A. Venkatram, D. Heist, D. Carruthers , and S. Arunachalam. Development and evaluation of the R-LINE model algorithms to account for chemical transformation in the near-road environment. Transportation Research Part D: Transport and Environment. Elsevier BV, AMSTERDAM, NETHERLANDS, 59: 464-477, (2018).

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

Downloads & Resources

References

https://doi.org/10.1016/j.trd.2018.01.028

Dates

Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Publisher U.S. EPA Office of Research and Development (ORD)
Maintainer
Identifier https://doi.org/10.23719/1433507
Data Last Modified 2017-11-15
Public Access Level public
Bureau Code 020:00
Schema Version https://project-open-data.cio.gov/v1.1/schema
Data Dictionary https://pasteur.epa.gov/uploads/10.23719/1433507/documents/HeistDavid_A-z099_DataDictionary_RLINE_NO2.pdf
Data Dictionary Type application/pdf
Harvest Object Id fb96bd9b-1a0f-4b0c-95b0-15cb85e8bac2
Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
Harvest Source Title EPA ScienceHub
License https://pasteur.epa.gov/license/sciencehub-license.html
Program Code 020:094
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents https://doi.org/10.1016/j.trd.2018.01.028
Source Datajson Identifier True
Source Hash ef54ac4d2a5df977e31296c1ed1fa9bebc6bf3ae
Source Schema Version 1.1

Didn't find what you're looking for? Suggest a dataset here.