Transportation Emissions in Mexico City – How Big Data is Driving Change
Mexico City is one of the most congested cities in the world, and it’s taking a toll on the health of its citizens and the environment. Sergio Castellanos, a postdoctoral scholar with Energy and Resources Group, along with Dan Kammen and other researchers from UC Berkeley and the National Institute of Ecology and Climate Change in Mexico, have been working to address this problem. The team researched approaches to reducing transportation emissions in Mexico City through the use of data, and it earned them the Data for Climate Action Challenge Grand Prize last November. This week, Sergio also wrote about the project in Data Makes Possible.
“The Data for Climate Action Challenge invites data scientists, researchers, and innovators to use the world’s rapidly amassing data to address climate change. Global Pulse, the United Nations initiative for big data and data science, announced the Data for Climate Action Challenge winners during the COP23 UN climate change conference. The Grand Prize was awarded to “Electro-mobility: Cleaning Mexico City’s Air with Transformational Climate Policies Through Big Data Pattern Analysis in Traffic & Social Mobility.”
The team quantified the number of traffic jams at different times and locations throughout Mexico City, and then used the MOVES-Mexico model to estimate emissions from the transportation sector. The team also used data from Google’s ‘Popular Times’ to understand population movement patterns in Mexico City. Based on this information, the team evaluated different potential locations for electric vehicle charging stations, along with three different policies and their impact in terms of avoided emissions: (i) electrification of the entire taxi fleet in Mexico City; (ii) electrification of Mexico City’s public transit buses; (iii) electrification of all light-duty vehicles in Mexico City.”
Photo: Smog hanging over Mexico City. Credit: Santiago Arau