Data from: Spatially refined analysis of emission burdens and equity from light-, medium-, and heavy-duty vehicle traffic in the United States
Data files
Sep 30, 2026 version files 3.10 GB
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README.md
10.98 KB
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us_all_blocks_rural_urban_census_code.csv
178.93 MB
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us_census_block_hdv_emissions_density.csv
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us_census_block_ldv_emissions_density.csv
966.86 MB
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us_census_block_mdv_emissions_density.csv
968.59 MB
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us_county_level_emissions_density_slr_results.csv
7.37 MB
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us_county_mean_emissions_density.csv
11.97 MB
Abstract
We estimate block-level emission intensities of nitrogen oxides (NOX) and fine particulate matter (PM2.5) from on-road vehicle traffic for every census block in the United States, combining MOVES-based emission factors with street level traffic data. We use this spatially refined, computationally efficient, and policy-sensitive metric to evaluate emissions burden. Despite comprising less than 11% of vehicle kilometers traveled, we find that medium- and heavy-duty trucks account for 46% of NOX and 50% of PM2.5 emission burden nationally — with PM2.5 burden from trucks dominated by exhaust emissions while tire and brake wear constitute nearly half of light-duty vehicle PM2.5 burden. People of color face emission burdens averaging 40% above the national mean, with Asian populations exceeding 60%, and lower-income populations face 20–25% higher burdens. Statistically significant racial-ethnic or income disparities are present in 85–89% of US counties. Critically, these disparities are not confined to large metropolitan areas. They are widespread across both urban and rural counties nationwide. We also show that spatial aggregation substantially attenuates estimated disparities and can reverse the relative ranking of burdened groups, underscoring the importance of spatially refined analysis.
This dataset provides annual average daily vehicle emission density estimates (g/km²-day) for NOx and PM2.5 across the United States, at both the Census block and county level, along with county-level regression results relating emission density to demographic indicators.
General Information
Title of Dataset:
Near-Road Vehicle Emission Density Estimates by U.S. Census Block and County, with County-Level Regression Results
Principal Investigator / Author(s):
- Name: Brittany Antonczak
- Institution: Department of Civil and Environmental Engineering, University of Vermont, Burlington, VT, 05405, USA
- Email: Brittany.Antonczak@uvm.edu
- Name: Clare Nelson
- Institution: Department of Civil and Environmental Engineering, University of Vermont, Burlington, VT, 05405, USA
- Email: Clare.Nelson@uvm.edu
- Name: Tammy M. Thompson
- Institution: Environmental Defense Fund, Boulder, CO, 80302, USA
- Email: tthompson@edf.org
- Name: Mindi W. DePaola
- Institution: Environmental Defense Fund, Boulder, CO, 80302, USA
- Email: mdepaola@edf.org
- Name: Gregory Rowangould
- Institution: Department of Civil and Environmental Engineering, University of Vermont, Burlington, VT, 05405, USA
- Email: Gregory.Rowangould@uvm.edu
Geographic location of data collection: United States (all 50 states and the District of Columbia)
Funding sources: This work was supported by the Environmental Defense Fund, whose work is supported by gifts from Signe Ostby, Scott Cook, and Valhalla Foundation.
Description of the Data and File Structure
1. Census block-level emission density files
Files:
us_census_block_ldv_emissions_density.csvus_census_block_mdv_emissions_density.csvus_census_block_hdv_emissions_density.csv
Description: Annual average daily emission density estimates (g/km²-day) at the Census block level for two pollutants — NOx and PM2.5. Estimates are reported separately for three vehicle traffic types: Light-Duty Vehicles (LDV), Medium-Duty Vehicles (MDV), and Heavy-Duty Vehicles (HDV) — one file per vehicle class.
Variables:
| Field name | Description |
|---|---|
GEOID |
2020 Census block geographic identifier (15-digit GEOID). |
STATEFP |
State Federal Information Processing Standard (FIPS) code (1 to 2 digits). |
COUNTYFP |
County Federal Information Processing Standard (FIPS) code (1 to 3 digits). |
COUNTYNAME |
County name. |
STATENAME |
State name. |
VEHCLASS |
Vehicle class: LDV, MDV, or HDV (see definitions below). |
NOX |
Emission density for oxides of nitrogen (NOx) emissions (g/km²-day). |
PM25_EXHAUST_TOTAL |
Emission density for primary PM2.5 exhaust emissions (g/km²-day). |
PM25_BRAKEWEAR |
Emission density for primary PM2.5 brakewear particulate (g/km²-day). |
PM25_TIREWEAR |
Emission density for primary PM2.5 tirewear particulate (g/km²-day). |
PM25_COMBINED |
Emission density for combined primary PM2.5 (includes exhaust, brakewear, and tirewear) (g/km²-day). |
Vehicle class definitions (VEHCLASS):
- LDV: Light-Duty Vehicles
- MDV: Medium-Duty Vehicles
- HDV: Heavy-Duty Vehicles
2. County-level mean emission density file
File: us_county_mean_emissions_density.csv
Description: County-level average annual daily vehicle emission density estimates (g/km²-day) for NOx and PM2.5, disaggregated by vehicle class (LDV, MDV, HDV, and TOTAL = all vehicles combined). Values are population-weighted means of the census block-level emission density data, aggregated to the county level, covering all U.S. counties across the 50 states and the District of Columbia.
Variables:
| Field name | Description |
|---|---|
GEOID |
2020 Census county geographic identifier (5-digit GEOID). |
STATEFP |
State Federal Information Processing Standard (FIPS) code (1 to 2 digits). |
COUNTYFP |
County Federal Information Processing Standard (FIPS) code (1 to 3 digits). |
COUNTYNAME |
County name. |
STATENAME |
State name. |
POLLUTANT |
Pollutant name (see definitions below). |
VEHCLASS |
Vehicle class: LDV, MDV, HDV, or TOTAL (see definitions below). |
POP20 |
Emission density estimate for the total population. |
SHARE_W |
Emission density for population identifying as White alone. |
SHARE_NW |
Emission density for population identifying as not White alone. |
SHARE_B |
Emission density for population identifying as Black alone. |
SHARE_A |
Emission density for population identifying as Asian alone. |
SHARE_O |
Emission density for population identifying as Other race alone. |
SHARE_H |
Emission density for population identifying as Hispanic or Latino (of any race). |
SHARE_BELOWPOV |
Emission density for the population with income below the poverty level (based on ACS data). |
Pollutant definitions (POLLUTANT):
NOx_Emissions: Oxides of Nitrogen (NOx) emissionsPM25_Exhaust_Total: Primary PM2.5 exhaust emissionsPM25_Brakewear: Primary PM2.5 from brake wearPM25_Tirewear: Primary PM2.5 from tire wearPM25_Combined: Combined primary PM2.5 emissions from exhaust, brake wear, and tire wear
All values are in units of g/km²-day (grams per square kilometer per day).
Vehicle class definitions (VEHCLASS):
- LDV: Light-Duty Vehicles
- MDV: Medium-Duty Vehicles
- HDV: Heavy-Duty Vehicles
- TOTAL: All vehicle types combined
Additional notes:
- Population data by race and ethnicity, as well as total population, are based on the 2020 U.S. Census.
- Poverty-related emission burden estimates (
SHARE_BELOWPOV) are based on tract-level 2016–2020 ACS 5-year estimates. - All emission burden values reflect population-weighted means of emission density estimates aggregated from the census block level to the county level.
3. County-level regression results file
File: us_county_level_emissions_density_slr_results.csv
Description: Results from county-level ordinary least squares (OLS) regression models, each estimating the relationship between block-level vehicle emission density and two block-level demographic indicators: percentage of the population that is non-White (SHARE_NW) and median household income (MEDHHINCOME). Separate models are fit for each U.S. county (excluding a few counties with insufficient populated areas) for each vehicle type (LDV, MDV, HDV, TOTAL) and pollutant (NOx, PM2.5), for a total of 49,824 individual models.
Variables:
| Field name | Description |
|---|---|
GEOID |
2020 Census county geographic identifier (5-digit GEOID). |
STATENAME |
State name. |
COUNTYNAME |
County name. |
VEHCLASS |
Vehicle class: LDV, MDV, HDV, or TOTAL (see definitions below). |
EDVAR |
Emission density variable modeled as the response (NOx or PM25). |
PREDVAR |
Predictor variable used in the model (SHARE_NW or MEDHHINCOME). |
PREDDESC |
Descriptive label for the predictor variable. |
Slope |
Estimated slope coefficient — the change in emission density per unit increase in the predictor variable. |
Intercept |
Model intercept. |
R2 |
Coefficient of determination (R²). |
p |
P-value for the slope coefficient. Values ≤ 0.05 indicate statistical significance. |
n |
Number of census blocks used in the model for the county. |
Response variable definitions (EDVAR):
NOx: Emission density for oxides of nitrogen (NOx) emissions (g/km²-day)PM25: Emission density for combined primary PM2.5 (includes exhaust, brakewear, and tirewear) (g/km²-day)
Predictor variable descriptions (PREDVAR, PREDDESC):
SHARE_NW— Non-White Population Share: percent of the block-level population that is not "White alone" (based on 2020 U.S. Census)MEDHHINCOME— Median Household Income: median household income (in USD) from the 2020 U.S. Census
Vehicle class definitions (VEHCLASS):
- LDV: Light-Duty Vehicles
- MDV: Medium-Duty Vehicles
- HDV: Heavy-Duty Vehicles
- TOTAL: All vehicle types combined
4. Block-level rural-urban status
File: us_all_blocks_rural_urban_census_code.csv
Description: The rural/urban classifications used to determine emission density disparities across communities in the United States, directly pulled from the 2020 Census data.
Variables:
| Field name | Description |
|---|---|
GEOID |
2020 Census block geographic identifier (15-digit GEOID). |
CENSUS_RU |
2020 Census block rural/urban classification. |
Sharing/Access Information
License: CCO
Links to other publicly accessible locations of the data: None
Data was derived from the following sources:
- 2020 U.S. Census (population by race/ethnicity, total population, block/county geographic identifiers)
- 2016–2020 American Community Survey (ACS) 5-year estimates, tract level (poverty-related emission burden estimates)
- 2018 Highway Performance Monitoring System (HPMS) link-level average annual daily traffic counts for light-, medium-, and heavy-duty vehicle traffic
- Machine learning modeling to fill in gaps in the 2018 HPMS link-level data set
- EPA MOVES modeling in inventory mode for 701 representative counties to obtain emissions factors (total emissions in county / total activity in county for each HPMS vehicle class and road type)
Contact for Questions
Gregory Rowangould, Gregory.Rowangould@uvm.edu
Human subjects data
Human subjects data are limited to publicly available data from the 2020 US Census and US Census American Community Survey, and as such are de-identified and in the public domain.