The Management of Waste and Reduction of Hydrocarbon Emissions

Team: 13

School: Taos High

Area of Science: Clean Energy and Computer Science


Interim: Problem Definition:

How can we limit fossil fuel production at a local level while reducing the amount of waste that is created? During lunchtime at our school, our team realized the majority of students discarded around half the food items on their trays. We proposed an idea to prevent food waste by converting food loss into biofuels. We realized that not all the waste produced could be processed into biofuels.. Therefore, we also needed an efficient way to separate the food waste from undesirable elements of lunch.

Problem Solution:

Our team's best solution for food waste was to create a sustainable biofuel generated through waste. Our team approached biofuels already understanding the limits posed by the chemical process of producing the fuel. For example, citrus, meat, heavily processed food, styrofoam, plastic utensils, and plastic wrap all would not work in the chemical transformation. This meant that our biofuel system could not process a certain amount of the food waste and resources produced by the cafeteria. However, we found that by sorting the garbage produced into, processable and not, we still had enough biomass due to the sheer amount of waste the cafeteria created. Using our programs, we can simulate the chemical reaction of the combustion of methane, the product of our process, and the data collected to calculate the amount of waste prevented and the methane produced by our process.

Progress to Date:

To date we have completed a total of three models, two in Python and one in Alice,

The Model predicts methane production rate/amount for varying slurry volume, slurry content (acidity, C/N), and time. Code can be viewed on Github:
https://github.com/carlos-miller-466/nm-stem-challenge-2021

A simulation on the collection process that shows separating usable biofuel material from the unusable trash. Animated using code on Alice. The last program was coded in Processing using Python, full code can be viewed at:
https://github.com/Flynn-B/Methane-Combustion-Simulation.
The model simulates the molecular chemistry happening in the combustion of methane gas, the product of the project. The reactants are Methane and Oxygen and the products are CO2 and Water. Everything is programmed from scratch using Python, including collision detection and collision physics. The green circles represent methane, yellow represent oxygen, the orange represent CO2, and the blue represent water. All values such as density, mass, volume are based on real world numbers with the collision engine using all of these in its calculations. Code can also simulate hundreds of molecule collisions at once:




Expected Results:

From our data we collected we found that we collected 16.42 kgs viable food waste for biofuels collected and 26.67 kgs of unusable trash collected over a two day period. Our prototype showed on average a production of 1670 mL of methane gas per 1000 mL of food waste used
Using our models and other data collected, we found that our cafeterias food waste for a year would be able to approximately produce a total of 2184 Liters of methane. The biofuels that we have created are expected to lower the amount of food waste in our school while also creating a sustainable energy that will be utilized instead of being released as a greenhouse gas into the atmosphere.



Team Members: Chris Rivera, Flynn Basehart, Isaiah Gonzales, and Brian Hoang


Team Members:

  Brian Hoang
  Flynn Basehart
  Chris Rivera
  Izaiah Gonzales

Sponsoring Teacher: Tracy Galligan

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