CoolClimate, an environmentalist network at the University of California, Berkley, has created a series of ongoing projects that emphasize a reduction of carbon emissions on various scales. Their site focuses on visual appeal and features polished, immersive interfaces for users to experiment with. Site visitors can compare their individual/household emissions, toy around with the site’s interactive maps, and ultimately educate themselves about how the US is contributing to climate change.
While exploring the site I discovered CoolClimate’s Interactive Carbon Footprint Map. It allows the user to see how many metric tons of CO2 an average household emits per year for any given US county. Users can pair this data with their individual carbon footprint results to see if they emit more or less carbon than average.
I found this visualization to be extremely effective. Zooming, panning and comparing colored map pieces was much more entertaining than reading a list of figures; it also gave me a better image of the damage we are doing to our atmosphere. The areas with less emissions show up green, the areas with more appear red. We as viewers can immediately notice which areas of the US are controlling their emissions and which areas need to reduce them. All we need to do is use the colors.
Although this data has been carefully collected by county and assembled in a user-friendly way, there is still room for improvement on this map. Users can’t search for counties, they can only zoom in and float their cursor over them to observe the data. White areas on the map represent counties CoolClimate does not yet have data for (western states like Utah are missing a lot of data).
Despite these negative aspects, we can consider the map a mostly-complete work in progress. It allows users to easily observe carbon footprints by county and compare their own footprints. Not only did I leave the site more educated on the magnitude of US carbon emissions, but I also left with a desire to reduce my own footprint. This was CoolClimate’s purpose for using data visualization and, at least for me, it proved effective.