Radars may mitigate environmental impact on Rio's Guanabara bay

Scientists from the Institute of Alberto Luiz Coimbra Post-Graduate Studies and Research in Engineering of the Federal University of Rio de Janeiro (UFRJ) and the Federal Fluminense University (UFF) Wednesday (Oct. 10) unveiled a joint developed system to help reduce the environmental impact on Guanabara bay, in Rio de Janeiro.

The system uses data collected through a sea radar with X band frequency, the frequency utilized in large ships. “This mathematical model may make it possible for researchers to get physical and environmental parameters both from the surface of the sea and the detection of trash, in addition to a number of other bits of information,” said research coordinator and meteorologist Fábio Hochleitner, with the Laboratory of Computing Methods in Engineering. 

Pilot project

Researchers from both universities will focus the pilot project on Guanabara bay in a bid to gain experience and gauge the demand for solutions to local problems regarding logistics, transport, pollution, and water contamination.

“We decided to create this pilot project looking at the bay, aiming to gain knowledge about the region, not to mention an integrated system capable of generating information to serve as base for a number of uses,” said Hochleitner.

Among them, Hochleitner mentioned the monitoring of sea traffic, the routes and accumulation of garbage, calculations on waves and currents, the spread of oil leaks, and the direction of the tide. Another use may be energy generation. “It can serve as the base for wind energy generation plants installed on the bay itself or even for equipment making energy through the waves.”

Hochleitner said that the X band radar system may help the Guanabara Bay Decontamination Program further mitigate the impact of garbage dumping.

Warnings

The coordinator said that the system may be given yet another use—the detection of heavy rains, for issuing early warnings for the population. “We can make short-notice predictions of extreme events, like major storms, and warn the population hours in advance.”

Features are also believed to enable the construction of a radar network to help monitor data.