# Class 1 - EDGAR Atmospheric Acid Gas Burden (`EDGAR_AcidGas_Burden_2020_2022_mean_1km`) — EDIS AI Agent Dataset View

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## 1. Dataset Metadata
- **Raster Name**: Class 1 - EDGAR Atmospheric Acid Gas Burden
- **Slug**: `EDGAR_AcidGas_Burden_2020_2022_mean_1km`
- **Units**: `Acid Gas Burden Index (0-1)`
- **Spatial Extent**: UL(83.8671659, -179.9999948) to LR(-89.9838547, 179.9999871)
- **Summary**: This dataset represents the global EDGAR Acid Gas Atmospheric Burden, a normalized indicator of long-term anthropogenic acid gas influence derived from the Emissions Database for Global Atmospheric Research (EDGAR) v8 emissions inventory for the period 2020–2022.
- **Included in Flagship Map Package**: `Global_ISO9223_2020_2024_LE_V4` (`GET https://secure.engineeringdirector.com/api/bundles/Global_ISO9223_2020_2024_LE_V4/point_query`)

### Color Table & Value Breaks
- `(0.0, (34.0, 139.0, 34.0))`
- `(0.002, (35.6, 145.6, 35.6))`
- `(0.004, (37.2, 152.2, 37.2))`
- `(0.006, (38.8, 158.8, 38.8))`
- `(0.008, (40.4, 165.4, 40.4))`
- `(0.01, (42.0, 172.0, 42.0))`
- `(0.012, (43.6, 178.6, 43.6))`
- `(0.014, (45.2, 185.2, 45.2))`
- `(0.016, (46.8, 191.8, 46.8))`
- `(0.018000000000000002, (48.4, 198.4, 48.4))`
- `(0.02, (50.0, 205.0, 50.0))`
- `(0.02, (50.0, 205.0, 50.0))`

# EDGAR Acid Gas Atmospheric Burden (2020–2022)

## Overview

This dataset represents the global **EDGAR Acid Gas Atmospheric Burden**, a normalized indicator of long-term anthropogenic acid gas 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 acidification potential 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:

- Sulfur Dioxide (SO₂)
- Nitrogen Oxides (NOₓ)

to estimate persistent atmospheric acid gas burden associated with industrial, transportation, power generation, and combustion-related activities.

The dataset is expressed as a continuous normalized index ranging from **0.00 to 1.00**, where higher values indicate greater long-term anthropogenic acid gas influence.

**Units:**

- Normalized Acid Gas Burden Index (0–1)

---

## Background

Anthropogenic acid gas emissions can significantly influence atmospheric chemistry and environmental corrosivity.

Acid gas burden is commonly associated with:

- Fossil fuel combustion
- Power generation
- Refinery operations
- Industrial manufacturing
- Transportation corridors
- Petrochemical facilities
- Smelting operations
- Urban atmospheric pollution

Persistent acid gas emissions may contribute to:

- Atmospheric acidity
- Sulfate formation
- Nitrate formation
- Acid deposition
- Electrochemical corrosion acceleration
- Environmental degradation processes

Unlike real-time air quality measurements, this dataset is intended to represent long-term atmospheric burden conditions rather than transient pollution events.

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 Acid Gas Burden framework incorporates anthropogenic emissions data derived from the EDGAR v8 global atmospheric emissions inventory.

Primary pollutants include:

- Sulfur Dioxide (SO₂)
- Nitrogen Oxides (NOₓ)

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**.

---

## Interpretation Guidelines

| Acid Gas Burden | Interpretation |
|---|---|
| 0.00–0.10 | Minimal Burden |
| >0.10–0.25 | Low Burden |
| >0.25–0.45 | Moderate Burden |
| >0.45–0.65 | High Burden |
| >0.65–1.00 | Very High Burden |

Higher values generally indicate greater long-term atmospheric influence from combustion-related emissions sources.

---

## Spatial Resolution

| Property | Value |
|---|---|
| Coverage | Global |
| Resolution | ~1 km |
| Coordinate System | WGS 84 |
| EPSG Code | 4326 |
| Temporal Coverage | 2020–2022 |

---

## Data Sources

Primary environmental inputs include:

- [EDGAR v8 Global Air Pollutant Emissions Database](https://edgar.jrc.ec.europa.eu/)
- [NASA MERRA-2 Atmospheric Reanalysis](https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/)
- [ERA5 Reanalysis Dataset](https://cds.climate.copernicus.eu/)

Primary pollutants incorporated:

- Sulfur Dioxide (SO₂)
- Nitrogen Oxides (NOₓ)

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
- Localized emissions modeling
- GIS visualization
- Environmental screening
- Infrastructure risk assessment
- Enterprise API workflows

---

## Related Datasets

### EDGAR Atmospheric Burden Layers

- [EDGAR Total Burden](https://secure.engineeringdirector.com/public/map/EDGAR_Total_Burden_2020_2022_mean_1km)
- [EDGAR Acid Gas Burden](https://secure.engineeringdirector.com/public/map/EDGAR_AcidGas_Burden_2020_2022_mean_1km)
- [EDGAR Particulate Burden](https://secure.engineeringdirector.com/public/map/EDGAR_Particulate_Burden_2020_2022_mean_1km)
- [EDGAR Chemistry Burden](https://secure.engineeringdirector.com/public/map/EDGAR_Chemistry_Burden_2020_2022_mean_1km)

### Dominant Component Layer

- [EDGAR Dominant Component](https://secure.engineeringdirector.com/public/map/EDGAR_Dominant_Component_V4_2020_2022_1km)

### LE Corrosion Layers

- [ISO 9223 Steel LE](https://secure.engineeringdirector.com/public/map/steel_ISO9223_LE_V4_Enhanced_2020_2024_1km)
- [ISO 9223 Zinc LE](https://secure.engineeringdirector.com/public/map/zinc_ISO9223_LE_V4_Enhanced_2020_2024_1km)
- [ISO 9223 Aluminum LE](https://secure.engineeringdirector.com/public/map/aluminum_ISO9223_LE_V4_Enhanced_2020_2024_1km)
- [ISO 9223 Copper LE](https://secure.engineeringdirector.com/public/map/copper_ISO9223_LE_V4_Enhanced_2020_2024_1km)


---

## 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:

| Metal | LOO R² | LOO MAE (µm/year) | LOO RMSE (µm/year) |
|---|---:|---:|---:|
| Steel | 0.864 | 12.72 | 27.99 |
| Zinc | 0.839 | 0.42 | 0.92 |
| Aluminum | 0.897 | 0.26 | 0.39 |
| Copper | 0.900 | 0.34 | 0.50 |

These results supported incorporation of EDGAR-derived atmospheric burden analytics into the Localized Emissions corrosion framework.

---

## Attribution

**Joseph Mazzella**  
AtmosphericIQ LLC  
Engineering Director, Inc.

---

## Dataset Citation

> Mazzella, J. (2026). *EDGAR Acid Gas 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

| Property | Value |
|---|---|
| Dataset Name | EDGAR Acid Gas Atmospheric Burden |
| Dataset Version | 1.0 |
| Publication Year | 2026 |
| Author | Joseph Mazzella |
| Organization | AtmosphericIQ LLC / Engineering Director, Inc. |
| Temporal Coverage | 2020–2022 |
| Resolution | ~1 km |
| Coordinate System | WGS 84 (EPSG:4326) |
| Units | Normalized Index (0–1) |
| Data Type | Continuous Raster |
| Primary Pollutants | SO₂, NOₓ |
| Source Dataset | EDGAR v8 |

---

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