As a postdoctoral researcher at UChicago’s Pritzker School of Molecular Engineering, Srinivasa Balivada found one of his biggest insights not in the lab, but while paddling a raft along a river in India, collecting water quality data along the way.
“When you're in the field, you get a real sense of how people treat water,” said Balivada, now a PME staff scientist. “One good example is when we went to the city of Varanasi in India to carry out measurements on the Ganga River. It is a religious place. So no one can touch the river water with their footwear. They leave their boots in the bank of the river and they go in barefoot.”
The 1,569-mile-long Ganga is one of India’s most important rivers and provides numerous communities the water used for bathing, washing clothes, watering crops and drinking. The team led by Balivada and Saba Mundlay of the UChicago Trust in India made measurements on the Ganga at various regions along its length over the past six years. Their data collected from boats and rafts showed how the river is heavily polluted in stretches.
The measurements were being taken for Water-to-Cloud, a mobile sensor platform based measurement and mapping technique developed by Pritzker Molecular Engineering Professor Supratik Guha and his team. Once inserted into the water, these GPS enabled sensors platforms are capable of collecting real-time geo-tagged data on water quality which can then be uploaded to the cloud, providing a significant advantage over the “grab sampling” that collects samples to send to labs for analysis.
The University of Chicago Trust and IBM recently announced their collaboration to scale the initiative through the IBM Sustainability Accelerator. Through a pilot program in the Indian state of Maharashtra, this partnership will pair the technology pioneered at PME with IBM’s expertise in data analytics, artificial intelligence and hybrid cloud technologies. This work builds upon measurements that the team have been carrying out since 2017 in India, and most recently, following the pandemic, through a grant from the pharmaceutical company, Windlas Biotech Limited in India for measurements on the Ganga in Uttarakhand.
“Climate change causes unpredictable weather patterns that, among other dangers, threaten water security in many places, including India,” said Premjit Balasundaram, who leads the collaboration on IBM’s end. “Therefore, effective management of water is extremely critical for a sustainable economy today and in the future. I am extremely thrilled to be part of an initiative delivering societal impact leveraging skills, technology and assets from IBM.”
This project also incorporates an artistic dimension, employing a distinctive data visualization scheme crafted by Mundlay, who has a background in both visual communication and data analytics. This innovative approach aims to present data to regulators, academics, NGOs and the general public in an informative, evocative manner that inspires meaningful change.
It starts with a conceptual shift: Don’t only look at the water.
“We’re focusing on visualizing water quality information by actually visualizing everything else around the water,” Mundlay said.
Painting the whole picture
Pollution issues in India are well recognized, with much of the water quality data monitored and available from government organizations like the Central Pollution Control Board of India. But there was no one place where people could get a comprehensive picture of the problem.
“A lot of data exists, and a significant amount of it exists with public access. But it's scattered. And a lot of it's in PDF form or other forms that are not machine readable,” Guha said.
For Mundlay, another problem was that it wasn’t contextualized. Pairing the data with maps and images of the areas not only got regulatory agencies to take note in a way page after page of chemical readouts did not, but it also started revealing sources of the pollution.
“I realized that when I would look at the data alongside a map of water infrastructure and land use in industrial areas that I would start to understand whether a certain chemical parameter was due to pollution or whether it was due to natural weathering from rocks, for example,” Mundlay said.
The more data the team layered over the information the Guha Lab’s sensors pulled from the water, the clearer the image they built of how these polluted waters both impacted and were impacted by daily life.
“Take water quality, you pull it against population, industry, rainfall and you can start seeing all kinds of trends,” Guha said. “Then, we had the idea that we can gather this data in some automated or semi-automated way and make it made machine readable.”
A new model for changing the world
Although Maharashtra is just one of India’s 28 states, it contains almost a fifth of the nation’s polluted stretches of river. This impact is part of why IBM and the UChicago Trust selected the state for the pilot program. They aim to have a Minimum Viable Product by the end of 2024.
“With nearly half of the global population vulnerable to significant environmental distress, new strategies to help create a sustainable future are essential,” said Justina Nixon-Saintil, IBM Vice President & Chief Impact Officer. “This means scaling solutions to help people immediately, while also cultivating a pipeline of future leaders at the intersection of technology and sustainability across industries.”
Guha hopes the project can help in building a model for how scientists and engineers can learn to work with regulators, the private sector and local communities, while at the same time bringing in new scientific approaches to the problem. Although this project started by looking at better sensor technologies, scientists and engineers can’t expect any new technology to change the world on its own.
“These are complex problems that intertwine the social and the physical sciences and it is naïve for a scientist to expect to walk into a room saying, ‘Hey, I’ve got this fantastic way of measuring a certain quantity in water’ and expect that the red carpet will be rolled out,” Guha said.