Over the past week in ENVS, we had a hosted webinar “Paths to Decarbonization,” and started data collection for our projects. The webinar featured Melissa Powers, from the Green Institute, and Jessica Lovering, from the Breakthrough Institute, and was hosted by Chris Joyce, senior NPR science correspondent. It focused on the nature of our energy alternatives to coal and the necessary structural adjustments and political changes which will need to occur. Jessica and Melissa disagreed rather strongly in terms of their opinions of natural gas, with Jessica emphasizing how much cleaner it is than coal, while Melissa focused on how gas could undermine the long term viability of renewables. One major thing I learned about the functioning of our energy system was how dependent renewables are on the presence of fossil fuels in our current energy grid; since both solar and wind are intermittent sources of energy, with immediate levels of output uncontrollable, we need some base load, flexible sources of energy to respond to demand hikes, absent more sophisticated energy storage and distribution systems. This is a vital element of the functioning of our energy system, and must be factored into any future plans about greener energy.
The other part of this past week has consisted of prowling U.S. Census data for information related to housing and land prices in the Portland metro area, and importing this data into GIS. The preceding sentence hides the protracted technical difficulties our lab team faced; creating a GIS map from raw data, not already pruned by a professor to import seamlessly, required knowledge about attributes in ArcGIS that I had not prior knowledge of. It turns out that whether data is categorized as a “String” “Number” or “Double” makes a huge difference in the underlying function, and converting one type of data to another requires a host of intermediate steps that took me about 4 hours to figure out. Though I have learned about the importance of the data fields matching, altering them is still a pretty ad hoc, trial-and-error process for me. We still need to do quite a bit of extensive analysis. We plan to do several more maps to relate home price to the size of the land parcel or the size of the home, to explore further spatial relationships between the urban growth boundary and land values. Additionally, we will do some so far undetermined statistical analysis of this relationship, categorizing each census tract as either inside or outside the UGB (perhaps excluding those evenly split), and analyzing these groups to quantify the information. Lastly, we need to conduct a more thorough investigation of existing literature on this subject, to reconcile and compare our findings with prior work.