Intercomparison of Six National Empirical Models for PM2.5 Air Pollution in the Contiguous US

Matthew J. Bechle; Michelle L. Bell; Daniel L. Goldberg; Steve Hankey; Tianjun Lu; Albert A. Presto; Allen L. Robinson; Joel Schwartz; Liuhua Shi; Yang Zhang; Julian D. Marshall

doi:10.32866/001c.89423

Intercomparison of Six National Empirical Models for PM2.5 Air Pollution in the Contiguous US

Matthew J. Bechle
, Michelle L. Bell
, Daniel L. Goldberg
, Steve Hankey
, Tianjun Lu
, Albert A. Presto
, Allen L. Robinson
, Joel Schwartz
, Liuhua Shi
, Yang Zhang
, Julian D. Marshall

Producción científica: Article › revisión exhaustiva

4 Citas (Scopus)

Resumen

Empirical models aim to predict spatial variability in concentrations of outdoor air pollution. For year-2010 concentrations of PM_2.5 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).

Idioma original	English
Publicación	Transport Findings
Volumen	2023
DOI	https://doi.org/10.32866/001c.89423
Estado	Published - 2023

Nota bibliográfica

Publisher Copyright:
© 2023, Findings Press. All rights reserved.

Financiación

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.

Financiadores	Número del financiador
Center for Indoor Air Research	R835873
U.S. Environmental Protection Agency	RD83479801, RD83587101

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Life on land

ASJC Scopus subject areas

Civil and Structural Engineering
Transportation

Acceder al documento

10.32866/001c.89423

Otros archivos y enlaces

Citar esto

@article{b3e0b7af2c164ee8925a0cdc67ea81bd,

title = "Intercomparison of Six National Empirical Models for PM2.5 Air Pollution in the Contiguous US",

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 \textasciitilde{}12\% of the average concentration; many best-fit lines are near the 1:1 line).",

keywords = "Land use regression, air pollution, air quality models, empirical model comparison, environment, environmental findings, exposure assessment, gridded models, particulate matter, point-based models",

author = "Bechle, \{Matthew J.\} and Bell, \{Michelle L.\} and Goldberg, \{Daniel L.\} and Steve Hankey and Tianjun Lu and Presto, \{Albert A.\} and Robinson, \{Allen L.\} and Joel Schwartz and Liuhua Shi and Yang Zhang and Marshall, \{Julian D.\}",

year = "2023",

doi = "10.32866/001c.89423",

language = "English",

volume = "2023",

}

TY - JOUR

T1 - Intercomparison of Six National Empirical Models for PM2.5 Air Pollution in the Contiguous US

AU - Bechle, Matthew J.

AU - Bell, Michelle L.

AU - Goldberg, Daniel L.

AU - Hankey, Steve

AU - Lu, Tianjun

AU - Presto, Albert A.

AU - Robinson, Allen L.

AU - Schwartz, Joel

AU - Shi, Liuhua

AU - Zhang, Yang

AU - Marshall, Julian D.

PY - 2023

Y1 - 2023

N2 - 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).

AB - 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).

KW - Land use regression

KW - air pollution

KW - air quality models

KW - empirical model comparison

KW - environment

KW - environmental findings

KW - exposure assessment

KW - gridded models

KW - particulate matter

KW - point-based models

UR - https://www.scopus.com/pages/publications/85200673059

UR - https://www.scopus.com/pages/publications/85200673059#tab=citedBy

U2 - 10.32866/001c.89423

DO - 10.32866/001c.89423

M3 - Article

AN - SCOPUS:85200673059

VL - 2023

JO - Transport Findings

JF - Transport Findings

ER -

Intercomparison of Six National Empirical Models for PM2.5 Air Pollution in the Contiguous US

Resumen

Nota bibliográfica

Financiación

ODS de las Naciones Unidas

ASJC Scopus subject areas

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto