Climate change is coming whether we like it or not. And carbon emissions are amplifying the problem. Every day, you and I release pounds of carbon into the atmosphere just by taking everyday actions like driving, eating, and using electricity. But how much carbon do I put into the atmosphere? How do I far relative to everyone else?
What it does
Carbon Emission Visualizer allows you to easily input your street address, and some information about your lifestyle, and your total carbon emissions on a daily basis will be calculated. From there, you can see your carbon emissions plotted on a map of the United States along with data from all of our other users. This lets you compare how your doing carbon emission wise compared to the rest of the world. And if you want to be more specific, and, say, see how yp fair against the city of Atlanta, or against just Georgia Tech, you can segment out those areas, and see a histogram of the emissions for all of the user data from the selected area. This is your chance to learn about your carbon impact, and earn bragging rights among your friends and coworkers about how low, or not, your carbon emissions are.
How I built it
Challenges I ran into
The ArcGIS API, as well as the Firebase API has some quirks, but nothing too major.
Accomplishments that I'm proud of
The ArcGIS map not only works but looks good, and loads quickly. Selection of points by drawing on the map is also a clean and efficient means of selecting groups of points to compare to.
What I learned
What's next for Carbon Emission Visualizer
We would like to eventually allow the user to be able to compare themselves in areas that are not just total carbon emissions, but the subcategories that go into defining that metric. This would be particularly useful for, say, area or regional directors who want to determine if their area's carbon emissions are higher than average, and why that it is, so auto effectively create and enforce new policies related to decreasing carbon emissions within the region. We would also potentially like to add a map layer for compressional district to draw conclusions between user data and politics. If the data exists publicly, we would also like to implement a means for users to compared themselves to nations, or large emitting units, and see what the world would be like if everyone lived that they do.