Events

January 28, 2021: IRES Professional Development Seminar with Zia Mehrabi

What makes a good researcher?

A few months back, I led a short workshop at the Land Use and Global Environment Laboratory on this topic. One of the PhD students thought that other Masters/PhD students at IRES would benefit from me running the same workshop for the wider grad student body. So here you are. Come along to explore what makes a good researcher.

Jan 26, 2021: The Time is Now: Canadian and Global Recognition of the Right to a Healthy Environment

Virtual Lecture: Join Dr. David Boyd’s discussion of the human right to a healthy environment, which is currently not recognized by national law in Canada. Introductory comments by Dr. David Suzuki & Canadian Greens leader Annamie Paul!

January 21, 2021: IRES Faculty Seminar with Fausto Sarmiento

As archetypes of the meta-geography of the vertical dimension, mountain metaphors remain at the core of animistic belief systems, religious cults, military strategies, economic potential and scientific innovation. Dr. Sarmiento argue that transdisciplinary science and geocritical tropes, incorporating physical, human, and technical geography with humanities and arts, are the best approaches to understand the complexity of mountain systems.

January 14, 2021: IRES Student Seminar with Sandeep Pai and Ian Theaker (First Seminar in Term 2)

December 3, 2020: IRES Faculty Seminar with Inês Azevedo (Last Seminar in Term 1)

In this talk I will cover three related recent papers: 1) Comparing the Health Damages from Air Pollution to the Value Added in the U.S. Economy (PNAS, 2019). 2) Fine Particulate Air Pollution from Electricity Generation in the US: Health Impacts by Race, Income, and Geography (ES&T, 2019). 3) What are the best combinations of fuel-vehicle technologies to mitigate climate change and air pollution effects across the United States? (ERL, 2020).

November 26, 2020: IRES Professional Development Seminar with Cicely Blain

November 19, 2020: IRES Faculty Seminar with Felix Pretis

Using machine learning and econometric model selection, we construct an empirically-derived climate damage function allowing for the potential impact of climate extremes and accounting for possible adaptation pathways. The damage function can be disaggregated to a country level as a function of global mean surface temperature and is independent of any specific emission scenario