Abstract
Empirical models aim to predict spatial variability in concentrations of outdoor air pollution. For year-2010 concentrations of PM2.5 in the US, we intercompared six national-scale empirical models, each generated by a different research group. Despite differences in methods and independent variables for the models, we find a relatively high degree of agreement among model predictions (e.g., correlations of 0.84 to 0.92, RMSD (root-mean-square-difference; units: μg/m3) of 0.8 to 1.4, or on average ~12% of the average concentration; many best-fit lines are near the 1:1 line).
| Original language | English |
|---|---|
| Journal | Transport Findings |
| Volume | 2023 |
| DOIs | |
| State | Published - 2023 |
Bibliographical note
Publisher Copyright:© 2023, Findings Press. All rights reserved.
Funding
We gratefully acknowledge the funders. This publication was developed as part of the Center for Air, Climate, and Energy Solutions (CACES), which was supported under Assistance Agreement No. R835873 awarded by the U.S. Environmental Protection Agency (EPA) for an Air, Climate, and Energy (ACE) center. Additional funding was from the EPA for the SEARCH ACE Center (RD83587101) and the Harvard-MIT ACE center (RD83479801). This manuscript has not been formally reviewed by EPA. The views expressed here are solely those of authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication.
| Funders | Funder number |
|---|---|
| Center for Indoor Air Research | |
| EPA Cephalosporin Fund | |
| Texas Air Research Center | R835873 |
| U.S. Environmental Protection Agency | RD83479801, RD83587101 |
Keywords
- Land use regression
- air pollution
- air quality models
- empirical model comparison
- environment
- environmental findings
- exposure assessment
- gridded models
- particulate matter
- point-based models
ASJC Scopus subject areas
- Civil and Structural Engineering
- Transportation
