Is Your City Right for Electro-mobility?
When faced with an enormous challenge, it’s incredibly gratifying to make inroads towards solving it. This is why we’re over the moon following the award presentations for the Data for Climate Action Challenge (D4CA). Climate change is an issue that affects every human being in every country. It’s also a challenge that no one person, or even a single country, can address alone: collaboration and partnership are essential to rise to the climate challenge.
The grand prize-winning submission Electro-mobility: Cleaning Mexico City’s Air with Big Data and Climate Policy is an impressive example of how collaboration, together with data science and innovation, can enable a solution that could be used to tackle a major city’s pollution problem.
A team of researchers from the University of California, Berkeley and the Instituto Nacional de Ecología y Cambio Climático (INECC) looked into Mexico City’s traffic congestion problems by combining data from Waze, EPA MOVES-Mexico, and Google Places’ Popular Times. They evaluated different transportation electrification policies to evaluate which would most reduce air pollution and greenhouse gas emissions.
Alarmed by the very real consequences of heavy pollution in Mexico City – millions of premature deaths linked to air quality levels – the team developed a data-driven approach to strategically deploy electric bus fleet routes and electric vehicle charging architecture to clean the air in the city.
One of the most exciting dimensions of their project is that their findings are potentially scalable, and suggest ways to reduce pollution in other cities around the world.
A Potentially Scalable Solution – Electro-Mobility
The proposed solution from the Berkeley and INECC researchers received high marks in the Data for Climate Action challenge. Now, the challenge is to move the project into implementation: how can these solutions inform real change and help Mexico to meet its pollution reduction goals? What are the implications for Mexico City and other cities suffering from high traffic congestion and pollution levels?
The model created by this grand prize-winning team could potentially be replicated in other cities as well. If it were applied in London, could the smog that hangs above the city due to local geography and massive traffic be reduced? Would applying the model to Beijing show that adopting an electric bus fleet would reduce emissions significantly, and affordably as well? How many lives could be saved from premature deaths due to hazardous air? Can this transformation in the transportation sector be fast-paced and inclusive at the same time?
When we consider that there are perhaps a dozen major world cities with a mix of high pollution levels, traffic congestion and a significantly sized bus rapid transit system, and a high volume of vehicles on the road, imagine the benefits that could be derived from this single concept if it were scaled globally.
Harnessing Data Science for the SDGs
The innovative solutions devised by the teams participating in the Data for Climate Action challenge are inspirational and potentially game-changing. In both the public and private sectors, there is an increasing recognition of the power of big data and data science to advance the public good around the world. As we recognize this potential, we can also look to the future and imagine all of the new ways that data could help to create a cleaner, safer planet for everyone.
Data Makes Possible will be following the Grand Prize winners as they work to implement their solutions and bring real change to our world. Check out the solutions and interviews from all the winning teams.
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