Articles | Volume 13, issue 6
Earth Syst. Sci. Data, 13, 3013–3033, 2021

Special issue: Benchmark datasets and machine learning algorithms for Earth...

Earth Syst. Sci. Data, 13, 3013–3033, 2021

Data description paper 24 Jun 2021

Data description paper | 24 Jun 2021

AQ-Bench: a benchmark dataset for machine learning on global air quality metrics

Clara Betancourt et al.


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2020-380', Anonymous Referee #1, 04 Feb 2021
  • RC2: 'Comment on essd-2020-380', Anonymous Referee #2, 09 Mar 2021
  • AC1: 'Reply to RC1', Clara Betancourt, 09 Apr 2021
  • AC2: 'Reply to RC2', Clara Betancourt, 09 Apr 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Clara Betancourt on behalf of the Authors (09 Apr 2021)  Author's response    Author's tracked changes
ED: Referee Nomination & Report Request started (13 Apr 2021) by David Carlson
ED: Publish as is (20 May 2021) by David Carlson
Short summary
With the AQ-Bench dataset, we contribute to shared data usage and machine learning methods in the field of environmental science. The AQ-Bench dataset contains air quality data and metadata from more than 5500 air quality observation stations all over the world. The dataset offers a low-threshold entrance to machine learning on a real-world environmental dataset. AQ-Bench thus provides a blueprint for environmental benchmark datasets.