Impact of different on-road vehicle emissions inventories on downstream air quality, exposure, health, and equity assessments
- 1Northwestern University
- 2University of Illinois at Urbana-Champaign
Abstract
Emissions from on-road vehicles are a pervasive source of air pollution, contributing to inequitable pollutant exposure and adverse health outcomes. Numerical air quality models are used to characterize traffic-related pollutant concentrations and impacts. However, model outputs rely on underlying emissions inventories whose formulations can differ substantially. Here, we leverage the widely used Intervention Model for Air Pollution (InMAP) to examine how four different on-road emissions inventories used at three different spatial resolutions (1, 1.3, and 4 km) influence simulated fine particulate matter (PM2.5) population exposure, health impacts, and equity outcomes in a freight-heavy urban setting – the Greater Chicago Region. We find that population-weighted exposure and attributable mortality differ up to 72% and 69% across inventories, compared to only 15–17% across resolutions. While all inventories result in higher estimated PM2.5 exposure and mortality among Black, Hispanic, and Asian populations compared to non-Hispanic White populations, the magnitude and relative ordering of disparities across racial groups vary with both inventory choice and spatial resolution. Furthermore, we demonstrate that characterizing exposure inequities using emissions colocation can yield substantially different disparity estimates (up to 20%) from pollutant concentration-based estimates due to atmospheric transport and chemistry; a divergence that likely represents a lower bound given InMAP’s reduced-complexity parameterizations. This work builds on recent studies showing that model resolution influences air quality, health, and equity assessments by demonstrating that on-road emissions inventory choice introduces even greater differences than spatial resolution.
Versions
Related
- Cumulative obesity exposure and hepato-pancreato-biliary cancer risk following different weight-loss interventions: retrospective cohort study
- Bidirectional modification effects of non-optimal temperature and short-term exposure to fine particulate matter on cardiovascular mortality and their different subtypes: a time-stratified case-crossover study in multiple cities
- Metabolic Abnormalities Among Youths Receiving Antipsychotics Across Different Exposure Periods
- Effects of manganese dioxide on macrophages under different exposure schemes
- State violence, protest suppression, and trauma outcomes: a scoping review of cumulative exposure across different political contexts.
BibTeX
@article{shlipak2026impact,
title = {{Impact of different on-road vehicle emissions inventories on downstream air quality, exposure, health, and equity assessments}},
author = {Kyan Kuo Shlipak and Victoria Lang and Martha Santiago and Christopher W Tessum and Daniel E Horton},
journal = {Environmental Research Letters},
year = {2026},
month = oct,
doi = {10.1088/1748-9326/aeba01},
url = {https://iopscience.iop.org/article/10.1088/1748-9326/aeba01},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Impact of different on-road vehicle emissions inventories on downstream air quality, exposure, health, and equity assessments
AU - Kyan Kuo Shlipak
AU - Victoria Lang
AU - Martha Santiago
AU - Christopher W Tessum
AU - Daniel E Horton
PY - 2026
DA - 2026/10/27
JO - Environmental Research Letters
DO - 10.1088/1748-9326/aeba01
UR - https://iopscience.iop.org/article/10.1088/1748-9326/aeba01
AB - Emissions from on-road vehicles are a pervasive source of air pollution, contributing to inequitable pollutant exposure and adverse health outcomes. Numerical air quality models are used to characterize traffic-related pollutant concentrations and impacts. However, model outputs rely on underlying emissions inventories whose formulations can differ substantially. Here, we leverage the widely used Intervention Model for Air Pollution (InMAP) to examine how four different on-road emissions inventories used at three different spatial resolutions (1, 1.3, and 4 km) influence simulated fine particulate matter (PM2.5) population exposure, health impacts, and equity outcomes in a freight-heavy urban setting – the Greater Chicago Region. We find that population-weighted exposure and attributable mortality differ up to 72% and 69% across inventories, compared to only 15–17% across resolutions. While all inventories result in higher estimated PM2.5 exposure and mortality among Black, Hispanic, and Asian populations compared to non-Hispanic White populations, the magnitude and relative ordering of disparities across racial groups vary with both inventory choice and spatial resolution. Furthermore, we demonstrate that characterizing exposure inequities using emissions colocation can yield substantially different disparity estimates (up to 20%) from pollutant concentration-based estimates due to atmospheric transport and chemistry; a divergence that likely represents a lower bound given InMAP’s reduced-complexity parameterizations. This work builds on recent studies showing that model resolution influences air quality, health, and equity assessments by demonstrating that on-road emissions inventory choice introduces even greater differences than spatial resolution.
SN - 1748-9326
ER -