Mapping Biogas from Municipal Waste as Potential Clean Energy Areas in Central Mexico, Using Geographic Information Systems

• Published in: GIS LATAM Vol. 1276; pp. 106 - 124
• Main Authors: Carranco S., Karen L., Turpin-Marion, Sylvie J., Castro-Frontana, Diana G.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2020; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Biogas; GIS; Municipalities
• ISBN: 3030598713; 9783030598716
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-030-59872-3_8

Waste-to-energy (WtE) plants are management facilities that burn waste to produce electricity. Biogas plants are one form of WtE options. A prospective model to estimate biogas from solid waste was developed, combining two methodologies: Tchobanoglous and collaborators and the EPA-1996s equation. The first one uses urban solid waste composition to estimate biogas, while the later one converts biogas flow data into energy units (Mega-watts, MW). The resulting model is capable of estimating biogas from waste composition within any municipality in the study area (Mexico City, State of Mexico, Morelos, Puebla, and Querétaro) and it is also able to translate the potential biogas flow (in thousands of m3/day) into megawatts (MW). A GIS was used to create choropleth maps representing the biogas volume that can be potentially produced in each region. The results obtained show that the Iztapalapa delegation in Mexico City could generate 62.63 MW. The Chimalhuacán region could reach 46 MW as well as some areas in Morelos. The use of solid waste in the Sierra Norte de Puebla was estimated in an energy capacity of 49.41 MW and finally, the Bajío Queretano obtained 37.83 MW. The GIS-location model was conceived for its use in prospective studies to locate potential WtE projects. The calculated energy from urban solid waste is presented in the form of graphs and maps, thus reflecting which region has a better potentiality for using this type of clean energy. This information is an important foundation for further spatial analyses using GIS and decision making.