Six pollutants—benzene, toluene, ethylbenzene, xylenes, styrene, and 1,3-butadiene—are estimated daily across the U.S. Gulf States from 2011 through 2016 using Bayesian Maximum Entropy data fusion. The dataset was authored by Praful Dodda and harvested by the ODUM Dataverse. Its last update was recorded on May 25, 2026.
Use Cases
- Modeling spatiotemporal trends of hazardous air pollutants based on the daily estimates.
- Assessing long-term exposure risks for public health studies based on the six-year time series.
- Validating other air quality measurement or modeling techniques based on the Bayesian fusion methodology.
- Analyzing correlations between different volatile organic compound concentrations based on the six co-modeled pollutants.
Strengths
- Covers a six-year time period from 2011 to 2016.
- Includes estimates for six specific hazardous air pollutants.
- Uses a sophisticated Bayesian Maximum Entropy data fusion methodology.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Freshness should be verified as the last update timestamp is in the future (2026).
Provenance
- Source
- ODUM Harvested Dataverse
- Collection Method
- Bayesian Maximum Entropy (BME) data-fusion estimates
- Time Range
- 2011-2016
- Freshness
- Last updated 2026-05-25 03:10:37
- Geography
- U.S. Gulf States