The group received the award during an event at the COP23 climate conference in Bonn, Germany.
The team’s winning analysis explored air pollution’s impact on consumer spending, visualizing its results in a series of interactive maps and case studies.
Team members John Brandt
’19 M.E.Sc., Matthew Moroney
’18 M.E.M., and Sophie Janaskie
’18 M.E.M., joined Angel Hsu
, Assistant Professor at F&ES and Yale-NUS College and Director of Data-Driven Yale, to accept the award during a ceremony
on Nov. 12.
“Air pollution affects 90 percent of the global pollution and causes 7 million premature deaths,” said Hsu. “While studies exist to quantify these health impacts and the public health costs of air pollution, little data exist to estimate short-term impacts on people’s daily activities and behavior — what I call ‘micro-migrations.’”
The Yale Data-Driven Environmental Solutions Group
(Data-Driven Yale) is an interdisciplinary and international group of researchers, scientists, programmers, and visual designers based at F&ES and Yale-NUS College, Singapore. The group uses innovative data analytics to distill signals from large-scale and unconventional datasets and develop policy solutions to contemporary environmental problems.
For their project, the Data-Driven Yale team combined data tracking daily spending habits, air pollution and climate data for 12 Spanish provinces, to understand how poor air quality, exacerbated by climate change, might drive consumer spending.
“We wanted to see if poor air quality makes people more likely to stay indoors, avoiding restaurants, shops and recreational spaces,” said Janaskie. “Using data science and statistical tools like R, Python, and ArcGIS, we were able to hack together some novel datasets to reveal some impactful trends between air pollution and consumer spending.”
In total, their analysis found that Spanish consumers spend €25 to €41 million ($29 to $48 million) less on days when ozone pollution is 10 percent worse than usual, and that spending falls by €20 to €30 million ($23 to $35 million) on days when particulate matter pollution is 10 percent worse than usual. Just a 10 percent reduction in ozone and particulate matter 2.5 in Spain could increase consumer spending between €16 and 26 billion ($19 to 30 billion) annually. Worsened air pollution risks lowering spending further.
“Our results show that urban citizens’ spending habits are four times more affected by air pollution than rural citizens’,” said Brandt. “This result affirms the economic need for cities to further incentivize air pollution reduction.”
The contest connected the researchers with retail financial group BBVA
and weather data network EarthNetworks
, who provided the large data sets that underpin the team’s analysis. UN Global Pulse
and Western Digital
, which launched the contest, aim to foster collaboration between governments, innovators, data scientists and climate experts, to generate data innovations that can help the world meet Sustainable Development Goal 13
’s climate action targets.
In total, 97 semi-finalist teams developed projects using donated datasets from 11 companies. Six teams received recognition for topics ranging from the use of real-time traffic data to determine ideal electromobility routes in Mexico City to the application of cell phone data to understand displacement from floods in Senegal at the Nov. 12 event in Bonn.
“Data philanthropy is a crucial component to combating climate change and creating a just world,” said Moroney. “Society wins when businesses leverage their expertise by allowing access to their data for open-sourced innovation.”