Long-term criteria and toxic pollutants trends and community exposures over the Marcellus Shale in the U.S.
Bok Haeng Baek, Research Professor, George Mason University

This study aims to assess trends in air quality and community exposures in the Marcellus Shale region and whether any might be explained by changes in oil and gas development-related operations or governance from. The analysis will focus on local and regional exposures to criteria and hazardous air pollutants from 2002-2021, with special attention toward historically disadvantaged communities. The investigators are achieving their research aims with the following steps:

  1. Perform a long-term emissions trend analysis by integrating bottom-up oil and gas emissions and ambient measurements of criteria and select hazardous air pollutant concentrations.
  2. Conduct a long-term air quality trend analysis by applying a chemical transport model to simulate the criteria and select hazardous air pollutant concentrations over the region. 
  3. Use a more advanced chemical transport model that employs machine-learning to investigate sources of and control strategies for oil and gas emissions. 
  4. Apply a county-level community health vulnerability index approach to identify disproportionately exposed communities.

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Bok Haeng Baek, Research Professor, George Mason University

Project Updates

Baek Quarterly Update - September 2024

Long-term criteria and toxic pollutants trends and community exposures over the Marcellus Shale in the U.S.

Bok Haeng Baek, Research Professor, George Mason University

This study aims to assess trends in air quality and community exposures in the Marcellus Shale region and whether any might be explained by changes in oil and gas development-related operations or governance from. The analysis will focus on local and regional exposures to criteria and hazardous air pollutants from 2002-2021, with special attention toward historically disadvantaged communities. The investigators are achieving their research aims with the following steps:

  1. Perform a long-term emissions trend analysis by integrating bottom-up oil and gas emissions and ambient measurements of criteria and select hazardous air pollutant concentrations.
  2. Conduct a long-term air quality trend analysis by applying a chemical transport model to simulate the criteria and select hazardous air pollutant concentrations over the region. 
  3. Use a more advanced chemical transport model that employs machine-learning to investigate sources of and control strategies for oil and gas emissions. 
  4. Apply a county-level community health vulnerability index approach to identify disproportionately exposed communities.

What's Happened

  • Initiated the study with collaboration among researchers at George Mason University, Howard University, and Eastern Research Group.
  • Gathered unconventional oil and gas development (UOGD)-related emissions inventory and air quality monitoring datasets to assess air quality trends over the Marcellus Shale region.  
  • Started simulating concentrations of nitrogen dioxide, ozone, particulate matter (PM2.5), and selected air toxics including BTEX compounds, naphthalene, styrene, acrolein, and formaldehyde) for the period of 2002-2021. To start, they have completed simulations of hazardous air pollutants (HAPs) in the Marcellus Shale region for 2004, 2018, and 2019, which represent significant years in regulatory policy over UOGD sources.
  • Completed modeling the 2008 annual CAMx simulations for targeted air pollutants.

What's New

  • Reviewing and analyzing the 20-year UOGD-related emissions inventory and air quality monitoring datasets to understand long-term trends in air quality and associations with UOGD regulatory policy implementations.
  • Evaluating the performance of the 2008 CAMx air quality modeling simulations for ozone, PM2.5 and the listed air toxics by comparing them with air quality monitoring datasets gathered by the ERG team. 
  • Based on preliminary outputs from the CAMx model, implementing the DeepCTM, a chemical transport model using machine learning and artificial intelligence, to mimic the CAMx modeling performance and generate spatiotemporal air quality datasets over the Marcellus Shale region.

What's Next

  • Continue review of UOGD-related emissions inventory and monitoring datasets.
  • Conduct modeling simulations of air quality using CAMx for 2014 and 2019.
  • Using the CAMx model, analyze ozone and PM2.5 concentrations to understand potential UOGD-related sources and how they impacted local and regional air quality.