Week 9: From Collection to Analysis

This week, I ran into another limitation. Only, this time it was not equipment, it was materials. After my most recent round of sampling, I realized that I only have three testing kits left, which is enough for just one final full sample set. I decided to save that last set for next Wednesday, right after a few days of rain, since precipitation is one of the environmental factors most likely to influence PFAS concentrations. That means my data collection phase is starting to come to a close, and my focus is shifting much more heavily toward analysis.

Looking back at my results so far, some patterns are starting to feel consistent rather than random. Across multiple trials, surface water tends to have the highest PFAS concentrations, while middle-depth samples are often slightly lower. For example, in one dataset the surface reached around 39 ppt while the middle depth dropped closer to 31–33 ppt. That repeated “dip” in the middle is something I did not expect at the beginning of this project, and it suggests that PFAS distribution is being influenced by more than just simple vertical mixing.

Now, I am working on organizing all of my data into a structured dataset so I can analyze it computationally. I have started using graphs to visualize trends, especially depth profiles that show how concentrations change from surface to bottom. I am also beginning to explore statistical methods like correlation and regression to see which variables, such as depth, temperature, or weather conditions, actually have the strongest relationship with PFAS levels.

With sampling almost complete, the project is starting to shift from collecting numbers to understanding what those numbers actually mean.