Samples

Here, I show some of my teaching samples through my co-teaching experience in CHEE/ATMO 469B/569B (Air Pollution II: Aerosols) with Professor Sylvia Sullivan in Spring of 2026.

A meme to explain the aerosol "Faustian" bargain

Transitioning through Topics

Narrative Building

Interactive Simulator on Solar Geo-engineering

Aerosol Size Distribution Tool

Bloomifying Assessments

Final Term Project

Slido Quizzes and Word Clouds

Here I show three instances of incorporating Slido quizzes and word clouds within the class presentations. The lectures are on Geo-engineering and Aerosol Representation in Models.

The quizzes point toward some of the complexities observed in geo-engineering governance, as well as how most physical phenomena are nonlinear. The word cloud was an interesting exercise. It pointed toward the broader question of how we model any physical system, serving as an entry into climate modeling. The idea was to ask students if they could model the time taken to boil an egg, and to see where the collective intuition of the class stood.

A meme to explain the aerosol "Faustian" bargain

Here I show a satire I made for the lecture on climate effects of aerosols. The base image is Eugène Delacroix's 1828 lithograph of Mephistopheles tempting Faust, which I repurposed to illustrate the aerosol Faustian bargain, a framing first introduced by James Hansen in 1990 and revisited again in the last couple of years. Mephistopheles is relabeled as the short-lived cooling agents like aerosols, Faust as industrial humanity from 1850 to the present, and the fine print fixes the deal at roughly around 1 W/m² of effective radiative forcing, non-refundable upon emission reduction.

The piece points towards the asymmetry at the heart of the bargain (an immediate cooling benefit weighed against a delayed and larger warming cost), and sets up the question the geoengineering session returns to: if air quality regulations are removing the "natural" aerosol mask, what should we deliberately do about it?

On a broader note, the satire also points to how certain archetypes recur across nature and history. The Faustian bargain happens to be one that maps remarkably well onto the current climate system.

Transitioning through Topics

This was one of the last slides in the lecture mentioned above on the climate effects of aerosols. After introducing the aerosol Faustian bargain, this hook question leads us into the next lecture on Geo-engineering.

Along with that, I provide some book recommendations for students to read further and enrich their thinking. The book on the right (the "Moral Case" one) is something of an anomaly and is heavily criticized in the climate community, but I include it deliberately for critical thinking. As someone who spent a quarter of his life in a developing country, I found it an interesting read.

Narrative Building

Here I show two slides from the climate effects of aerosols lecture. On the first, students compute Earth's Energy Imbalance (EEI) for themselves from the Top-of-Atmosphere and Surface energy budgets, arriving at roughly +0.6 W/m² at both boundaries (which doubles as a consistency check on the budget itself). The second slide then unpacks what that small number actually does. It is the heat the Earth is accumulating, and effective radiative forcing is the decomposition that tells us which agents contribute how much. The aerosol piece on the right introduces the distinction the course returns to repeatedly, namely that absorbing aerosols (soot) have positive RF while scattering aerosols (sulfate, sea salt) have negative RF.

Most students had expressed interest in the climate effects of aerosols on the pre-course survey, so I felt a calculation-first entry into radiative forcing was the strongest way to bring them into this material without overwhelming them.

Interactive Simulator on Solar Geo-engineering

Here I show a screenshot of the SAI (stratospheric aerosol injection) simulator. Rather than explaining the logistics and impacts of SAI through papers, text, or figures on slides, I felt it was better to engage students with the topic through an in-class simulator (thanks to Reflective!). The simulator exposes the tradeoffs that make SAI such a contested topic. In real time, students see how injection latitude, injection rate, and aerosol choice each shift the temperature, precipitation, and ozone response, often in counter-intuitive ways. I run the simulator live and pose "what if" questions to the class (e.g., exploring different warming and emission scenarios), which explores the multi-scale dynamics and termination-shock concerns more viscerally than a static figure or paper excerpt could.

Aerosol Size Distribution Tool

Here I show an interactive aerosol size distribution tool I built for students during the early lectures on aerosol number size distributions.

The tool was built with the assistance of an AI coding assistant, which allowed me to go from concepts to in-class deployment in a fraction of the time it would have taken otherwise.

The tool has four tabs, moving students from data entry through normalization and plotting, to statistical moments, to surface and volume distributions.

Students can enter their own bin data, toggle between linear and log normalization, and watch the distribution and mean diameters update in real time. The formulas behind each calculation are visible and togglable, so the tool is not a black box but a computational demonstration of the equations students have just seen on the board. This kind of in-class interactive tool is my preferred alternative to static figures for introducing concepts where the visual transformation itself is the lesson. In addition, students who might be averse to the complexities of programming or Excel can find this useful, as the technical overhead is much less in this tool.

Bloomifying Assessments

The CIRTL materials on Bloom’s taxonomy were a significant concept for me. They pushed me to stop writing vague 'explain' prompts and start crafting questions with specific goals and clear answer boundaries. This can be applied to not only lesson plans/objectives but also assessments as well. This gives less space for students to wander off in their answers and makes grading easier as well.
Here I show two questions from HW 5, comparing the older version with my redesign.

The original Q1 asked students to state, for each aerosol transport mechanism, whether smaller or larger particles move faster, and to write a supporting equation. My version keeps that core but adds a second part: "Your grandparent claims smaller particles always move faster. Is this correct?" Students must identify gravitational settling as the counterexample, an evaluative move the original question never demanded.

The original Q7 asked a single calculation, "how long does a 2 um water droplet take to reach 25% of terminal velocity?" My version scaffolds the same calculation across 6 sub-parts, opening with a binary (will it accelerate forever?), moving through a force balance and an order-of-magnitude estimate, and closing by asking students to compute the ratio of a black carbon particle's atmospheric lifetime to that relaxation time. The answer is roughly 90 billion. Solving for this number it makes the separation of timescales more visceral rather than abstract for the students.

Here is the entire HW5:

CHEE_ATMO_469B_HW5.pdf

Final Term Project

Here I show the final term project at the end of the course. Five years ago, I took this course as a student (a different professor LOL) and completed a similar capstone project myself. That experience exposed some of the issues faced by a lot of us then. Students spent half their effort wrestling with Linux access and namelist files, and the other half analyzing results. The analysis itself was a bit open-ended, with broad questions. The version I now teach reflects what I learned from that struggle, especially how we can bloomify assessments. Rather than having students run the box model themselves, I provide pre-computed output from 21 carefully designed experiments. The project is now organized around two systematic dimensions: process sensitivity (a factorial matrix of coagulation, condensation, and nucleation ON/OFF combinations, with and without emissions) and environmental archetypes (Tucson, Delhi, Helsinki, Mauna Loa, each labeled with its distinctive physics). Students received structured data packages (size distributions, total number time series, PM time series) plus a starter template and metadata table. Questions are tightly scaffolded from baseline characterization through process attribution to policy application. This design shift from "run the model" to "analyze the output" lets students spend their cognitive effort on causal reasoning of which processes matter most, and why does environment change the outcome?

ATMO-CHEE469B-Term-Project-2026.pdf

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