Please also see an article on my research in the UNC Daily Tarheel, click here.

Using high performance computers and three dimensional models to simulate the atmosphere, I am working to improve our understanding of the formation of atmospheric air pollution. These computer models improve our understanding of the extremely complex chemical and physical processes that occur in the atmosphere. A better understanding of the atmosphere gives us the knowledge to improve the tools and methods that policy makers use to make effective control strategies to clean the air above our dirtiest cities.

What excites me most about my research is that I am doing something that makes a real impact on society. Millions of people in the world breathe danerously polluted air. Through my work, I am able to provide scientific advice to policy makers who make the decisions that can improve our quality of life.

CURRENT PROJECTS

"Methods to explain origins of health effects and plan effective remediation" VIDEO

The aims of this project are to provide health researchers new methods to measure and predict the health effects of harmful fresh and aged gas and particle mixtures. Both are needed to explain how city air harms and ultimately kills people. For information please see this video and link. This project involves collaboration with Dr. Harvey Jeffries and the UNC outdoor smog chamber and the UNC School of Medicine. Here are some photos of our outdoor smog chamber used int his project. This project is funded by the Gillings Innovation Labs. Please see this article in Carolina Public Health magazine for more information about this project.

"Assessment of environmental risk in the United Arab Emirates"

The United Arab Emirates (U.A.E.) has signed a contract with researchers from the University of North Carolina School of Public Health to lead an assessment of health risks due to environmental factors in the country, one of the fastest developing nations in the world. My involvement is with the outdoor air quality team whose aims are to improve our understanding of the sources of pollutants, their chemical transformation and transport, and the exposure and possible health effects to the public. Please view some photos of my recent trips to that country and some press releases.

“Technical Support for the attainment of ambient ozone standard in Houston, TX”

This project entails technical analysis in support of the Texas Commission on Environmental Quality (TCEQ) State Implementation Plan (SIP) for the US Environmental Protection Agency (EPA). The SIP is the strategy the state of Texas will adopt to achieve attainment of the 8-hour National Ambient Air Quality Standards (NAAQS) for ozone. All SIP strategies are based on predictions by air quality models. Our role at UNC is to provide the necessary tools and expertise to systematically evaluate and diagnose the complex relationships found in these air quality models. We also provide third party objectivity and meaningful scientific analysis to assist state regulatory agencies to make effective control strategies. This project includes collaborators from University of Houston, Texas A&M University, Houston Advanced Research Center (HARC), and Alpine Geophysics LLC.

“Technical Support for the attainment of ambient ozone standard in Baton Rouge, LA ”

This project entails technical analysis in support of the Louisiana Department of Environmental Quaity (LDEQ) and their development of a State Implementation Plan (SIP) for the US Environmental Protection Agency (EPA). The SIP is the strategy the state of Louisiana will adopt to achieve attainment of the 8-hour National Ambient Air Quality Standards (NAAQS) for ozone. All SIP strategies are based on predictions by air quality models. Our role at UNC is to provide the necessary tools and expertise to systematically evaluate and diagnose the complex relationships found in these air quality models. We also provide third party objectivity and meaningful scientific analysis to assist state regulatory agencies to make effective control strategies. This project includes collaborators from Alpine Geophysics LLC.

“Air Quality Model diagnostic and model performance tool development”

Air quality models determine air pollutant concentrations by calculating rates of atmospheric processes. Many models output only the spatial and temporal distribution of species concentrations, and rates of the individual processes that lead to these changes are not recorded.  With only concentration fields, it is often difficult to infer why air pollutant concentrations change.  A more detailed evaluation of modeled processes led to the development of a process analysis tool called pyPA (Process Analysis in python). The pyPA tool can quantitatively track physical and chemical processes that contribute to changing pollutant concentrations. The pyPA tool already has been utilized to explain model phenomena in California and Houston, Texas. The tool, however, was only able to analyze a fixed part of the modeling domain.   This method offers insights to the key variables for that region, but has previously been limited when analyzing a moving feature such as a large petrochemical release or the transport of an urban plume.  This project involves modifications of our pyPA tool to aggregate data for a moving, resizing, and reshaping domain. 

The Python-based Performance Analysis Support System (pyPASS) was recently developed at UNC-Chapel Hill as a modeling diagnostic tool to assist in the implementation of the Protocol for Regulatory Ozone Modeling Performance Tests (PROMPT). In contrast to traditional statistical measures of model performance, PROMPT provides regulatory modelers the framework to achieve a more holistic and systematic approach to assess model reliability. At the inception of PROMPT, however, model diagnostic tools did not possess the sophistication needed to implement its guidelines. This need led to the creation of the pyPASS diagnostic tool, which has significant computational and interfacial advantages over traditional support tools, such as Package for Analysis and Visualization for Environmental (PAVE) Data. These improvements in conjunction with the guidance provided by PROMPT, enables a more comprehensive model performance evaluation for photochemical air quality models.

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