We developed an estimation model to predict countrywise CO2 emissions. It takes GDP, trade as a percentage of GDP, population and rural population as a percentage of total population as inputs and estimates CO2 emissions. With the help of this, we wanted to show how these factors affect our carbon footprint .
This issue being one of the serious problems in the world has inspired us. As a team, we were curious about this and we wanted to observe it. It was also our first competition as a team that we quickly coordinated and tried to develop our project. We analyzed it by looking at its worldwide distribution to develop the project. The tools we use are Jupyter Notebook, Python, Google Drive and Tableu. Our team has made a new start with this competition. We believe this will give us more inspiration and energy.
We wanted to use NASA OCO2 Level 2 observation data, however, it was highly scientific and h5 file format is a format we have never worked with. We were unable to parse it into arrays. So we had to go with other open source data.
https://drive.google.com/file/d/15HoDX9r2r9alhSMGWQcLVLmJn9XTX_VX/view?usp=sharing
References are at the last page of the report: https://docs.google.com/document/d/1QVxMKmwER56KR4eSxw0T7j2qJjDyEUxd1eHVHh69SZo/edit