Today: Nov 23, 2024

12 Injured Due to Turbulence on Qatar Airways Flight to Ireland

qatar-airways-turbulence-injuries-dublin

At least 12 passengers on a Qatar Airways flight from Doha to Ireland sustained injuries due to severe turbulence, according to Dublin Airport officials. The affected flight, QR017, a Boeing 787 Dreamliner, landed shortly before 1 p.m. local time.

Upon landing, the aircraft was met by emergency services, including Airport Police and the Fire and Rescue department. “Six passengers and six crew members reported injuries after the aircraft experienced turbulence while airborne over Turkey,” Dublin Airport stated.

This incident occurred just five days after a Singapore Airlines flight from London to Singapore was forced to land in Bangkok due to severe turbulence. That flight experienced a 6,000-foot drop in just five minutes, resulting in the death of a 73-year-old British man and leaving 20 others in intensive care. According to an AP report, at least 22 passengers on the Singapore Airlines flight suffered spinal cord injuries, while six others, including a two-year-old, sustained brain and skull injuries. As of Saturday, 43 passengers from that flight remained hospitalized in Bangkok.

John Goglia, an aviation safety expert, emphasized the increased public concern about turbulence-related incidents. “There is reason for the public to be concerned but I think the concern is elevated because of the real focus that some news stations have given,” he told Bloomberg.

Turbulence-related incidents are the most common type of airline accidents, according to a 2021 study by the U.S. National Transportation Safety Board (NTSB). From 2009 through 2018, the NTSB found that turbulence accounted for more than a third of reported airline accidents. These incidents often resulted in serious injuries but typically did not cause damage to the aircraft.

The recent surge in turbulence-related injuries highlights the importance of adhering to safety protocols and the ongoing need for research and improvements in turbulence prediction and management.

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