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A dataset of Bayesian Maximum Entropy (BME) data fusion estimates of daily air concentrations of benzene, toluene, ethylbenzene, xylenes, styrene and 1,3-butadiene across the U.S. Gulf States, 2011-2016

Year: 2026

Type: dataset

Abstract: This dataset contains daily Bayesian Maximum Entropy (BME) data-fusion estimates of ambient concentrations of six pollutants over the U.S. Gulf States for calendar years 2011 through 2016. The six pollutants are: styrene, benzene, toluene, ethylbenzene, xylenes. and 1,3-butadiene

Source: UNC Dataverse

DOI: 10.15139/s3/lrybjv

Authors: Dodda, Praful, Abbott, Nora, Wang, Chi-Tsan, Engel, Lawrence S, Baek, Bok Haeng, Vizuete, William, Serre, Marc L

Institutions: University of North Carolina at Chapel Hill, George Mason University

Language: English

Topic: Air Quality Monitoring and Forecasting

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7161688987

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