EDGAR Particulate Atmospheric Burden (2020–2022)

Overview

This dataset represents the global EDGAR Particulate Atmospheric Burden, a normalized indicator of long-term anthropogenic particulate influence derived from the Emissions Database for Global Atmospheric Research (EDGAR) v8 emissions inventory for the period 2020–2022.

The raster was developed to characterize persistent atmospheric particulate loading associated with human activities and is intended to support:

• Atmospheric corrosion assessment
• Industrial environmental exposure analysis
• Atmospheric chemistry interpretation
• Environmental severity mapping
• Localized Emissions (LE) modeling
• GIS-based environmental screening

The framework integrates emissions associated with:

• PM10
• PM2.5
• Black Carbon (BC)
• Organic Carbon (OC)

to estimate persistent atmospheric particulate burden associated with industrial activity, transportation, urban development, combustion processes, and manufacturing environments. :contentReference[oaicite:0]{index=0}

The dataset is expressed as a continuous normalized index ranging from 0.00 to 1.00, where higher values indicate greater long-term anthropogenic particulate influence. :contentReference[oaicite:1]{index=1}

Units:

• Normalized Particulate Burden Index (0–1)

Background

Anthropogenic particulate emissions can significantly influence atmospheric chemistry, deposition behavior, and environmental corrosivity.

Particulate burden is commonly associated with:

• Combustion-heavy environments
• Transportation corridors
• Industrial activity
• Refinery districts
• Manufacturing facilities
• Urban atmospheric pollution
• Atmospheric aerosol loading

Persistent particulate emissions may contribute to:

• Surface contamination
• Atmospheric deposition
• Moisture retention
• Aerosol transport
• Environmental degradation processes
• Atmospheric corrosion acceleration

Unlike real-time air quality measurements, this dataset is intended to represent long-term atmospheric burden conditions rather than transient pollution events. :contentReference[oaicite:2]{index=2}

The EDGAR framework consists of four atmospheric burden layers:

• Total Burden
• Acid Gas Burden
• Particulate Burden
• Chemistry Burden

and one interpretation layer:

• Dominant Component

The Dominant Component layer identifies which atmospheric burden category contributes the greatest normalized influence at each location, allowing rapid interpretation of the primary emissions driver affecting environmental exposure conditions.

Modeling Methodology

The Particulate Burden framework incorporates anthropogenic emissions data derived from the EDGAR v8 global atmospheric emissions inventory.

Primary pollutants include:

• PM10
• PM2.5
• Black Carbon (BC)
• Organic Carbon (OC)

The modeling framework incorporates:

Emissions Integration

• Multi-pollutant emissions aggregation
• Atmospheric burden normalization
• Pollutant weighting methodologies
• Long-term emissions characterization

Atmospheric Burden Scaling

• Logarithmic burden normalization
• Continuous scaling workflows
• Relative burden interpretation
• Global consistency adjustments

Environmental Integration

The resulting burden framework supports:

• Atmospheric corrosion modeling
• Localized emissions enhancement workflows
• Environmental severity assessment
• Industrial exposure characterization

The final raster is normalized to a continuous scale ranging from 0.00 to 1.00. :contentReference[oaicite:3]{index=3}

Interpretation Guidelines

Higher values generally indicate greater long-term atmospheric influence from particulate-producing emissions sources. :contentReference[oaicite:4]{index=4}

Spatial Resolution

Data Sources

Primary environmental inputs include:

• EDGAR v8 Global Air Pollutant Emissions Database
• NASA MERRA-2 Atmospheric Reanalysis
• ERA5 Reanalysis Dataset

Primary pollutants incorporated:

• PM10
• PM2.5
• Black Carbon (BC)
• Organic Carbon (OC)

Derived environmental layers supported by this dataset include:

• Localized Emissions (LE) Modeling
• Environmental Severity Mapping
• Atmospheric Corrosion Modeling
• Industrial Exposure Analysis

Intended Applications

This dataset may be used for:

• Atmospheric corrosion assessment
• Industrial exposure analysis
• Environmental severity mapping
• Atmospheric chemistry studies
• Aerosol burden interpretation
• Localized emissions modeling
• GIS visualization
• Environmental screening
• Infrastructure risk assessment
• Enterprise API workflows

Related Datasets

EDGAR Atmospheric Burden Layers

• EDGAR Total Burden
• EDGAR Acid Gas Burden
• EDGAR Particulate Burden
• EDGAR Chemistry Burden

Dominant Component Layer

• EDGAR Dominant Component

LE Corrosion Layers

• ISO 9223 Steel LE
• ISO 9223 Zinc LE
• ISO 9223 Aluminum LE
• ISO 9223 Copper LE

Validation

The Localized Emissions enhancement framework was evaluated using:

• CORRAG atmospheric corrosion datasets
• MICAT atmospheric exposure datasets
• ASTM STP1239 atmospheric corrosion datasets
• Historical emissions reconstruction analytics

Representative Leave-One-Out (LOO) model performance from the ISO Classic + EDGAR Random Forest framework: :contentReference[oaicite:5]{index=5}

These results supported incorporation of EDGAR-derived atmospheric burden analytics into the Localized Emissions corrosion framework. :contentReference[oaicite:6]{index=6}

Attribution

Joseph Mazzella
AtmosphericIQ LLC
Engineering Director, Inc.

Dataset Citation

Mazzella, J. (2026). EDGAR Particulate Atmospheric Burden (2020–2022). AtmosphericIQ LLC / Engineering Director, Inc.

Supporting Dataset Citations

EDGAR v8

Crippa, M., Guizzardi, D., Solazzo, E., et al. EDGAR v8 Global Air Pollutant Emissions Database. European Commission Joint Research Centre (JRC).
https://edgar.jrc.ec.europa.eu/

NASA MERRA-2

NASA Global Modeling and Assimilation Office (GMAO). MERRA-2 Atmospheric Reanalysis Dataset.
https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/

ERA5 Reanalysis

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999–2049.
https://doi.org/10.1002/qj.3803

Version Information