A Supervisory Control and Data Acquisition System to Mitigate Fugitive Methane Emission in Landfills

Authors

  • Lavanya Natarajan Viera High School

DOI:

https://doi.org/10.47611/jsrhs.v11i3.2975

Keywords:

IoT, Methane, Sensors, Machine Learning, Landfills, Detection, Mitigation, Prediction

Abstract

Landfills are 3rd largest sources of anthropogenic methane (CH4) emissions.  Currently, as landfill gas (LFG) CH4 measurements are inconsistent and untimely, inadvertent fugitive emissions go undetected; problems are realized late.  So, there is an inherent need to monitor LFG CH4 continuously via “Smart” systems.  The goal is to design and develop a Supervisory Control and Data Acquisition (SCADA) system for real-time CH4 detection, prediction, and remote mitigation.  System includes (i) Fugitive Emissions Mitigator (FEM) with programmable WiFi microcontroller connected to gas, and environmental sensors; (ii) continuous wireless data transmission to interactive cloud through unified codes; (iii) descriptive and diagnostic analytics in cloud dashboard to inform historical events, (iv) predictive and prescriptive analytics via Machine Learning (ML) algorithms to forecast CH4 emissions, and (v) long-distance LFG mitigation.  To test SCADA system, two aspects, which influenced the magnitude of fugitive emissions in the real world were studied in lab, namely, CH4 Transport in Soil, and CH4 Generation conditions in waste.  Per results, CH4 transport rate was inversely proportional to soil moisture.  However, CH4 generation was directly proportional to moisture content in wastes.  To further explain the complex CH4-to-moisture relationship, a 5th-order Polynomial ML equation with 86% accuracy and greatest curve-fit was derived.  Finally, LFG mitigation was achieved via a separate component, which allowed for remote pump activation to extract CH4.  Overall, this cost effective IoT solution helps solve existing and emerging fugitive CH4 issues via real-time measurements, prediction, and mitigation to help US reduce 45% greenhouse gases by 2030.

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References or Bibliography

ATSDR - Landfill Gas Primer - Chapter 2: Landfill Gas Basics. (2001, November). Cdc.gov. https://www.atsdr.cdc.gov/HAC/landfill/html/ch2.html

Bruggers, J., Green, A., Mckenna, P., & Benincasa, R. (2021, July 13). Your Trash Is Emitting Methane In The Landfill. Here’s Why It Matters For The Climate. NPR.org. https://www.npr.org/2021/07/13/1012218119/epa-struggles-to-track-methane-from-landfills-heres-why-it-matters-for-the-clima

Guidelines for monitoring for landfill gas at and near former dumps. (2011). In Minnesota Pollution Control Agency. https://www.pca.state.mn.us/sites/default/files/c-rem3-04.pdf

Hahn, F., & Grande, G. (2020). Design of a methane monitoring system for landfill and duct emissions. Natural Resources, 11(11), 520–529. https://doi.org/10.4236/nr.2020.1111030

Kiernan, B., Beirne, S., Fay, C., & Diamond, D. (2007). Monitoring of Gas Emissions at Landfill Sites Using Autonomous Gas Sensors.

Ramirez, B. R. (2021, August 11). Scientists say this invisible gas could seal our fate on climate change. CNN. https://www.cnn.com/2021/08/11/us/methane-climate-change/index.html

Tian, Y. (2019, January). Haokai Zhao: Methane Emissions from Landfills. Global WtERT Council | Waste-To-Energy Research and Technology Council. https://gwcouncil.org/m-s-thesis-methane-emissions-from-landfills/

Published

08-31-2022

How to Cite

Natarajan, L. (2022). A Supervisory Control and Data Acquisition System to Mitigate Fugitive Methane Emission in Landfills. Journal of Student Research, 11(3). https://doi.org/10.47611/jsrhs.v11i3.2975

Issue

Section

HS Research Projects