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What is a carbon footprint? Is it a useful concept? What are the scientific, social and economic implications of measuring environmental impacts through the billion dollar industry of sustainability accounting? In seeking to answer these questions, this course uses the concept of the carbon footprint as a lens through which to understand and critically assess scientific, economic practices and social discourses around sustainability as it is practiced across American and global society today.

Archaeology offers the opportunity to examine social-ecological systems over long time scales. This course explores different ways of conceptualizing these systems and considers major topics such as: decreasing biodiversity, traditional ecological knowledge, human-environment interactions related to food production, social responses to natural disasters and climate change, and resilience and collapse of past societies. We’ll engage with discussions on sustainability and our ecological impact on the environment.

This interdisciplinary seminar examines environmental justice as a movement and concept. We interrogate and discuss the historical role of racism, heteropatriarchy, colonialism and globalization in (re)producing and justifying place-based environmental contamination and toxicity. Through close analysis of case studies in the US and the Global South, students analyze and present on how disenfranchised groups have made political demands, scaled up, forged solidarities, asserted climate justice, challenged state and corporate projects and conducted citizen science in rural and urban settings.

What should humanity’s relationship with the environment look like, and why? Explores theoretical and practical debates surrounding the environmental challenges of our time. Key topics and controversies in the history of environmental political thought will be discussed. Students will be encouraged to develop their own vision of the proper relationship between human society and the environment in the 21st century.

This course will focus on the application of statistical programming for big data associated with ongoing environmental issues. Students will gain experience in statistical programming throughout the entire data life cycle including data management and provenance, analysis, visualization, and communication. Students will learn the fundamentals of applying statistical modelling and machine learning for making predictions and inferences for environmental data. Students will also learn considerations of data science that are unique to environmental data including spatial, temporal, ethical, and justice concerns. Environmental topics will include climate change, pollution, natural disasters, and agricultural impacts.