Faculty spotlight: Mitchell J. Small
Mitchell J. Small is jointly appointed as the Anderson Family Visiting Professor in Energy and the Environment at the Andlinger Center for Energy and the Environment in Princeton University and Visiting Senior Research Scholar in civil and environmental engineering.
Small is visiting from Carnegie Mellon University, where he is the H. John Heinz III Professor of Environmental Engineering. Among his many appointments, he chaired the National Research Council Committee on Risk Management and Governance Issues in Shale Gas Extraction, sat on the EPA Science Advisory Board, was associate editor for “Environmental Science & Technology,” and is currently serving as a fellow for the Society for Risk Analysis.
He conducts research in environmental statistics, mathematical modeling of environmental systems, risk assessment, and decision support tools.
For the fall semester at Princeton, he taught the course CEE 490/ENE 490: Mathematical Modeling of Energy and Environmental Systems.
In this interview, Small talks about his research and work at Princeton.
Tell me about your research:
I focus on the mathematical modeling of pollution and its effects on environmental systems, including how pollutants are generated, how they move about in the environment, how people and ecosystems are exposed to them, and how pollutants may be most effectively controlled.
I also do broader work on developing decision support tools for water, energy, and ecosystem management. Decision support tools are computer methods and applications that help people and organizations make decisions on fast-moving problems or complicated issues that have a lot of uncertainty surrounding them.
Social and behavioral factors affect how scientific decision support tools and results are developed, packaged, and received. My research considers how individuals and groups perceive risks and how they view scientific studies that are conducted to reduce risk uncertainty. I apply methods from statistics, law, psychology, and the human behavioral sciences to study how conflict between groups is manifested as well as in arguments over the validity of scientific studies. Not surprisingly, studies designed with broad stakeholder participation and conducted with independent third-party review are more likely (though not assured) to lead to consensus on preferred management options on environmental issues.
My most recent research at Carnegie Mellon has involved risk assessment for subsurface fluid injection of carbon dioxide for greenhouse gas mitigation, and the fracking of natural gas from shale formations.
Carbon dioxide, a greenhouse gas, is pressurized into a liquid form and injected deep underground. My initial efforts involved the design of leak detection monitoring networks at proposed carbon dioxide injection sites. This is to ensure that the captured gas does not return to the atmosphere and contribute to climate change.
Recent studies also address air monitoring near fracking sites and seismic risk detection in areas affected by oil and gas wastewater injection, which are processes used in the oil and gas industry. Better understanding and management of these risks is critical to continued shale gas and related energy development.
Could you detail the work you have been doing at Princeton University and the Andlinger Center?
Since arriving at Princeton, I have begun focusing on broader issues of energy and climate. My course in the fall looked at how we interface with and use energy as we shift from fossil fuels to renewable energy resources. Important factors we addressed included global population, economic growth, technological innovation, and local and global environmental impacts.
I have also started collaborating with Ning Lin, assistant professor of civil and environmental engineering, and Siyuan (Henry) Xian, a doctoral student in civil and environmental engineering, on the effects of hurricanes, how they interact with climate, and looking at decisions to build flood protection for infrastructure and buildings in coastal areas. When decisions are based on rare and extreme events such as Hurricane Sandy, it is apparent that very different, future scenarios of coastal development could unfold – depending on the timing and magnitude of such events. Outcomes are further complicated by the likelihood of sea-level rise over the next century, but with highly uncertain magnitude and timing. I have initiated a collaboration with Michael Oppenheimer of the Woodrow Wilson School of Public and International Affairs to better consider how these uncertainties might be reduced.
In another new project, I am both learning more about energy decision making and providing advice to Wei Peng, doctoral student at the Woodrow Wilson School, and Denise Mauzerall, professor of civil and environmental engineering and public and international affairs. We are looking at China and analyzing the tradeoffs between continued reliance on rail-transported coal vs. renewable energy and long-distance electricity transmission through proposed new power lines. The country is looking at how they are going to generate electricity in the future that meets growing demand and is also considerate of the environment and with constraints on greenhouse gas emissions.
What kind of methods or tools do you use in your work?
I develop and use a number of computer models for human-environmental systems, and a lot of statistical methods. These tools can serve as a repository for scientific knowledge regarding these systems, and help to support management decisions with proper recognition of the uncertainty surrounding an issue. Many of the tools that I have developed take detailed models for individual systems and derive a statistical characterization for a large population of these systems. Examples include models for the acidification of a set of 10,000 lakes in a region, models for the regional distribution of indoor radon concentration for homes in a region, and statistical models for the effects of leakage at carbon dioxide injection sites or seismic events related to wastewater injection that occur randomly in time and space.
How do you hope your research impacts people?
I hope it will give both scientists and non-scientists a different perspective on problems, and a better appreciation for how a multi-disciplinary approach is needed to address many of the most important problems that we now face. With this, I hope my research gives people information from a broader view and maybe from a different angle so we can better understand how changes in human-environmental systems occur and not be so surprised when unexpected things do pop up.