Articles | Volume 17, issue 1
Model description paper
16 Jan 2024
Model description paper |  | 16 Jan 2024

A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3

Sean Raffuse, Susan O'Neill, and Rebecca Schmidt


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1031', Anonymous Referee #1, 21 Aug 2023
  • RC2: 'Comment on egusphere-2023-1031', Anonymous Referee #2, 01 Sep 2023
  • AC1: 'Author response to Comments on egusphere-2023-1031', Sean Raffuse, 27 Sep 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Sean Raffuse on behalf of the Authors (17 Oct 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (19 Dec 2023) by Samuel Remy
AR by Sean Raffuse on behalf of the Authors (20 Dec 2023)  Manuscript 
Short summary
Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.