Articles | Volume 17, issue 6
https://doi.org/10.5194/amt-17-1651-2024
https://doi.org/10.5194/amt-17-1651-2024
Research article
 | 
19 Mar 2024
Research article |  | 19 Mar 2024

Hybrid instrument network optimization for air quality monitoring

Nishant Ajnoti, Hemant Gehlot, and Sachchida Nand Tripathi

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-173', Anonymous Referee #1, 20 Sep 2023
    • AC1: 'Reply on RC1', Hemant Gehlot, 16 Nov 2023
  • RC2: 'Comment on amt-2023-173', Anonymous Referee #2, 09 Oct 2023
    • AC2: 'Reply on RC2', Hemant Gehlot, 16 Nov 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Hemant Gehlot on behalf of the Authors (16 Nov 2023)  Author's response   Author's tracked changes 
EF by Polina Shvedko (17 Nov 2023)  Manuscript 
ED: Referee Nomination & Report Request started (05 Dec 2023) by Francis Pope
RR by Anonymous Referee #1 (08 Dec 2023)
ED: Publish subject to minor revisions (review by editor) (20 Dec 2023) by Francis Pope
AR by Hemant Gehlot on behalf of the Authors (30 Dec 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (31 Jan 2024) by Francis Pope
AR by Hemant Gehlot on behalf of the Authors (01 Feb 2024)
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Short summary
This research focuses on the optimal placement of hybrid instruments (sensors and monitors) to maximize satisfaction function considering population, PM2.5 concentration, budget, and other factors. Two algorithms are developed in this study: a genetic algorithm and a greedy algorithm. We tested these algorithms on various regions. The insights of this work aid in quantitative placement of air quality monitoring instruments in large cities, moving away from ad hoc approaches.