CO2DIGO| What Is Our Carbon Footprint?

What Is Our Carbon Footprint?

Your challenge is to identify local sources of carbon emissions and/or estimate amounts of carbon emissions for different human activities to aid scientists in mapping carbon sources and sinks. How can you inform decisions to adapt to the consequences of a changing world and aid policy makers in making plans for the future?

Carbon Compound Concentration Map in Colombia

Summary

Build visualizations for the concentration of carbon compounds in the atmosphere of certain high profile areas of Colombia. Then, find emission data to relate the concentration to certain human activities that might be causing it. Finally, deploy the visualization to a website where users can take a look at their regions and what activities are mostly impacting emissions.

How We Addressed This Challenge

First, we search for important variable to consider the footprint, We choose, xco2 from OCO-3 and CO for local dataset, we integrated those data with the idea to visualize how this parameters looks in differents Colombia's Cities, whith this approach (and maybe including more variables in a future) we can identifyng emision sources and also understand what locations at what time could be emit more contaminants to the atmosphere.

How We Developed This Project

First, we searched for an important variable to consider the footprint. We chose xco2 from OCO-3 and CO for the local dataset, we integrated the data with the idea to visualize how these parameters look in different cities of Colombia. With this approach (and maybe including more variables in a future) we can identify emission sources and also understand what locations at what time could be emitting more contaminants to the atmosphere.

How We Used Space Agency Data in This Project

We used data from OCO-3 and focused on the data from our country, selecting the latitude and longitude in the range of Colombia. We chose the xco2 variable which indicates the Column-averaged CO2 dry air mole fraction, and then extracted the uncertainty associated with xco2. The visualizations made show the xco2 values whose magnitude is above a certain threshold.

In this part of the project it’s difficult to associate particular sources of emissions to the CO2 concentration, but we came up with some hypothesis for some points. For example, we note high concentrations in the south of Colombia, above the Amazonas department, (a region with a large amount of forested area), whereby, we suspect that this data could be due to air routes, we note that in general there is a lack of data in many regions and we think the resolution of sensors could be a possible explanation for it.


We think in the future, we could go deeper, understanding the physics behind this variable in order to associate the xco2 measurements with different kinds of sources in this location.

Finally, we used local datasets from IDEAM (Instituto de Hidrología, Meteorología y Estudios Ambientales), SIATA (Sistema de Alerta temprana del Valle de Aburra), where the measurements of CO for the biggest cities in Colombia selected, and their historical monthly averages were plotted and integrated to the application.

Project Demo

http://64.227.2.40:4200/

Project Code
Data & Resources
  1. OCO-3 https://disc.gsfc.nasa.gov/datasets/OCO3_L2_Standard_Early/summary?keywords=oco-3
  2. air quality data in Colombia 2011-2018 : https://www.datos.gov.co/Ambiente-y-Desarrollo-Sostenible/DATOS-DE-CALIDAD-DEL-AIRE-EN-COLOMBIA-2011-2018/ysq6-ri4e
  3. Meteorological variables SIATA: https://datosabiertos.metropol.gov.co/dataset/variables-meteorol%C3%B3gicas
Tags
#carbonfootprint #OCO-3 #SIATA #COLOMBIA #IDEAM
Judging
This project was submitted for consideration during the Space Apps Judging process.