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

Permeable Pavement Infiltration testing and Clogging Prediction Set 1 Date Ranges 12/11/209 to 8/17/12 and4 /27/217 to 3/12/20

Metadata Updated: January 14, 2023

This is a data set gather from a permeable pavement parking lot at Edison Environmental Center.. Data presented is surface infiltration rates for permeable interlocking concrete pavers. Data collected using ASTM C1701.

This dataset is associated with the following publication: OConnor, T., and M. Borst. Predicting Location and Evaluating Progression of Clogging in a Permeable Pavement Parking Lot. Journal of Green Building. College Publishing, Glen Allen, VA, USA, 17(4): 3-18, (2022).

Access & Use Information

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

Downloads & Resources



Metadata Created Date January 14, 2023
Metadata Updated Date January 14, 2023

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date January 14, 2023
Metadata Updated Date January 14, 2023
Publisher U.S. EPA Office of Research and Development (ORD)
Data Last Modified 2021-03-04
Public Access Level public
Bureau Code 020:00
Schema Version
Harvest Object Id d2dd1742-7596-4a4b-855e-bdd7dd5b3696
Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
Harvest Source Title EPA ScienceHub
Program Code 020:096
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents
Source Datajson Identifier True
Source Hash 4b2abaeae55c161fa03a89fbc19495bf74c330c0
Source Schema Version 1.1

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