While it may seem obvious that information – its availability, collection, interpretation, among other aspects – is critical for the management of the environment, there are still many information gaps in our understanding of environmental challenges. Despite living in an age of information technology and socially-networked societies, this information revolution has not been integrated into environmental decision-making. My research demonstrates that there are still many information gaps and failures that hinder data-driven and information-based approaches to improve environmental policy and governance.

My research agenda addresses four fundamental questions: What information – and more broadly, knowledge – is needed to address pressing environmental issues, specifically climate change, air quality, and urbanization?  What knowledge gaps exist in our understanding, particularly in information-poor environments?  How can new information technologies, such as satellite remote sensing, aid in addressing these gaps?  Finally, what are the policy and governance implications?  Methodologically, I apply an interdisciplinary approach that draws upon both qualitative and quantitative methods, including remote sensing and statistical techniques. From a theoretical perspective, my research extends the environmental governance and policy sciences literatures, applying real-world data and case studies by which to examine the salience of theories on informational governance and data-driven approaches to decision-making.

Through the lens of indicators and composite indices, my doctoral dissertation demonstrated the strengths and limitations of applying data-driven approaches to environmental policy and decision-making. I accomplished this through two case studies: at the global scale, I used the Environmental Performance Index (EPI) to identify key information gaps in global environmental performance, and to analyze the role of a policy tool like the EPI to drive policy improvements. Turning to the case of China, considered an “information-poor” environment, largely due to political and economic restrictions on the free-flow of information, I applied similar methods to understand the challenges of implementing data-driven environmental policy in China. “Seeking truth from facts: The challenge of environmental indicator development in China” delves into the difficulty of the central government in China to develop a sub-national “China EPI” by which to track provincial environmental achievements and policy implementation. “Challenges and limitations of Provincial Environmental Protection Bureaus in China’s Environmental Monitoring, Reporting and Verification” relies on semi-structured interviews of Chinese environmental officials across China to better understand why data and information challenges exist in center-local relations in China’s governance system. Finally, the last paper explores the potential for satellite data to derive independent measures of air quality in China and globally, through the EPI. This research led to a special issue in Atmospheric Environment, “Toward the Next Generation of Air Quality Indicators.”

A Framework for Understanding Urban Sustainability

The growth of urban areas causes a range of stresses to the environment both within and beyond city limits. Through the conversion of land to built-up urban areas, biodiversity can be lost as habitats for species become fragmented (McKinney, 2008); local climates can change due to the creation of urban heat islands that modify temperatures (Oke, 1982); and natural resources and energy are consumed. The shift of dispersed human settlement to more dense urban concentrations of population and resources will also have environmental impacts that are not well understood (Miller and Small, 2003). The need for a solid scientific basis to better understand the linkages between urbanization and environment could not be more urgent. To do so requires a rigorous and comprehensive scientific underpinning for sustainable management and governance to address how urbanization impacts resource consumption and the environment within cities and its surroundings, particularly as they change over time. Whether urbanization as a process negatively impacts the environment, or whether cities can present possible solutions to environmental challenges is a puzzle.

The United Nations Sustainable Development Goal (SDG) working group has identified cities as a critical, cross-cutting issue for addressing a range of environmental problems, including waste management, air and water quality, poverty and vulnerability to climate change impacts (UN, 2012). However, how cities can achieve these targets, particularly while experiencing growth and expansion into peri- and exurban areas, necessitates new streams of knowledge and information by which to guide sustainable policy solutions and track progress. In assessing performance for the Millennium Development Goals (MDGs) — which the SDGs are meant to replace — sufficient, appropriate, and timely data collection and monitoring were particularly challenging. The measurement challenge is even more compounded when taking into consideration what Brenner and Schmidt (2013) call the “continued lack of agreement on what needs to be measured, and at what scale” for urbanization. Therefore, the convergence of multiple disciplines and actors to establish a clear scientific link between urbanization and environmental systems (e.g., climate, air, and water) is critical to create relevant knowledge and information to guide global sustainability goals in which cities are anticipated to play a crucial role.

I am currently developing a new research agenda applied at the urban scale to determine what knowledge is needed for urban sustainability. Is an ‘urban sustainability science’ required to understand the environmental impacts of urbanization, and the potential for cities to contribute to the global sustainability agenda? What information is needed to evaluate these challenges and potential? Can we develop typologies to characterize different modes and forms of urbanization that could lead to sustainable models of urban growth and development?