Ctenophora - Space Apps Challenge

Ctenophora | 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?

CFCheck

Summary

I attempt to create a system in which hospitals will be able to recognise the addresses provided by people who come in for such checkups and using the same and the resources of Carbon Footprint calculator, I attempted to find out the CO2 emission rates of these areas. By reviewing the healthcare files of hospitals located in a particular area, we can single out the major local zones of increased CO2 emissions, which may not be possible to do with heavy machinery and satellite systems which, while helpful in tracking industrial CO2 emission rates, will not be able to single out the smaller, local causes of CO2 emissions, which affects everyday population.

How I Addressed This Challenge

Carbon emissions affect not just the environment, but also the individual health of individuals. Increased CO2 emissions have led to a massive increase in respiratory diseases and cancer, especially in highly populated areas such as Delhi, New York, etc.

In this project, using the resources provided, I decided to create a system to identify the CO2 increasing agents via the healthcare reports of a sector.

Companies in the industrial sector are required to have biannual checkup’s of its employees, which includes the basic blood tests and any further ailments being caused. Using the already available data, I attempted to pinpoint the cause of these diseases. In my attempt, I was able to pinpoint two major local sources of increased CO2 footprint after examining nearly 600 addresses of patients suffering from Asthama alone from the hospital I interned at. On searching the location with Google Location services, one was a heavily functioning industrial centre (A1) while the other was in the vicinity of a crowded Indian restaurant utilising open air cooking with charcoal for nearly the past two decades (A2). On calculating the carbon footprint of a hypothetical single person resides in the two areas, I found that while in A1 the CO2 footprint was substantially higher than A2, over a longer period of time, A2’s CO2 emission rates increased drastically. After interacting with a family from A2, I also found five out of seven members of the family suffering with respiratory disorders, including Asthma and Bronchitis.

I thus attempted to create a system in which hospitals will be able to recognise the addresses provided by people who come in for such checkups and using the same and the resources of Carbon Footprint calculator, I attempted to find out the CO2 emission rates of these areas.

For this, I will first require a list of all the patients who have been suffering from the commonly caused diseases associated with increased CO2 rates, mainly Ashthama, Bronchitis and Lung Cancer. Following this, a software to automatically single out the the most used areas in the list in decreasing order of occurance. This is followed by a locator to locate these areas and identify the nearby sources of contamination, which may or may not be extremely obvious. Finally, the carbon footprint near these areas may be calculated by using the calculator provided in the resources.

I attempted the same with the various archives of NASA and created a healthcare system to identify from the existing data the cause majorly responsible for the increased CO2 emissions in a local area. I believe that by reviewing the healthcare files of hospitals located in a particular area, we can single out the major local zones of increased CO2 emissions, which may not be possible to do with heavy machinery and satellite systems which, while helpful in tracking industrial CO2 emission rates, will not be able to single out the smaller causes of CO2 emissions.

I believe with this, we will be able to properly identify the local sources of CO2 emissions, which would help in curbing further respiratory diseases. Since the majority of the hospitals are already functioning in these areas, if the hospitals cooperate with this system, it would become easier to single out the causes for these diseases and prevent them from occurring in another section of society.

How I Developed This Project

Brought up in Mumbai, which is one of the major sources of CO2 emission rates in the country and having an average Carbon Footprint per individual nearly 1.4x the national average, I found this challenge to particularly hit home. It was during this challenge that I figured out how to calculate my own CO2 emissions and the grim realisation that the recent flooding of my city may have been due to the activities which release excessive CO2 emissions. I had severe trouble breathing as a child, but was never able to correlate it with the rising CO2 emission rates, now that I look around, I find others struggling with similar disorders.

I then thought of experimenting with my own area and accessed the excel file of patient name, diseases and contact from the hospital I intern at. This did not violate doctor patient confidentiality agreement as the information was accessed within reasonable limits by a staff that had permission to access it and was not revealed in detail to others.

Following this, I was able to implement my project and am currently developing a software to automatically identify the areas which occur over a certain number of times in patient information. The way I plan to make it work is that if an area name occurs in over 5% of the patients complaining of respiratory disorders, the area is singled out for review. I believe with this system, identifying local hotspots of CO2 emissions will be much easier to accomplish.

I did not have a team other than myself working on this project. The major problems I faced while implementing my idea is to contact the hospitals and accessing the files, which is difficult considering the current burden on the healthcare system and how hospitals have become COVID hotspots. Inspite of this, I was able to single out these areas and experiment with my idea due to the cooperation of the hospital I previously interned at, so I believe the whole experience was an enriching one and made me realise the effects of CO2 emissions and my own carbon footprints, which left me both enlightened and a bit embarrassed.

How I Used Space Agency Data in This Project

My interest in healthcare was what led me to visualise this particular idea. I thought it would be a nice idea to check the resources provided and from there, I backtracked and found the majority of the areas on the east coast having increased Methane emissions also to have the most cases of lung cancer and Asthma, with extreme severity. I was able to work on my idea from there and gain more information to experiment with the idea in my own country and local areas, leading to me devising this system. I also utilised tha CO2 footprint calculators provided as the resources to calculate my the Carbon Footprint of an individual residing in the highlighted areas of increased CO2 emissions. I was also able to gain insight on the effects of CO2 emission on climate and health, utilising the provided resources from NASA as well as Open Data from the CDC.