August of 2001 U.S. air travel was already in decline as a sluggish economy had dampened passenger demand. Then the events of September 11, 2001, like none before in aviation history, dramatically decreased air traffic activity in the weeks that followed. The sharp post-9/11 decline and the reasons for it were obvious and generally well understood. But what about long-term structural changes to patterns in National Airspace System (NAS) traffic flows? What were the post-9/11 changes and to what extent did the NAS return to pre-9/11 operation levels in the following six months? Employing a variety of data sources, we found a 15% drop in air carrier airport operations (arrivals and departures) due to 9/11 through February 2002. We also found a 4% drop in air taxi operations, a 7% drop in general aviation operations, and a 9% drop in total operations. Air Route Traffic Control Center operations dropped 6% due to a 14% drop in air carrier operations. These reduction numbers have been discounted for both seasonal variations in traffic as well as the softening economy in 2001 prior to 9/11. Three initial observed responses in scheduled airport operations were elimination of the last bank, fewer operations throughout the day, and removal or shifting of banks throughout the day. Where the last bank was eliminated, March 2002 data indicated these were returning. Arrival delays initially fell to 30% of October 2000 levels and remained below half of the previous year's rates through February 2002. There was also a significant reduction in both airborne and taxi times due to fewer flights and less airspace congestion. This study serves as a snapshot of the effects of 9/11 on U.S. aviation six months afterwards.
INTRODUCTION: In-flight medical emergencies (IFMEs) average 1 of every 604 flights and are expected to increase as the population ages and air travel increases. Flight diversions, or the rerouting of a flight to an alternate destination, occur in 2 to 13% of IFME cases, but may or may not be necessary as determined after the fact. Estimating the effect of IFME diversions compared to nonmedical diversions can be expected to improve our understanding of their impact and allow for more appropriate decision making during IFMEs.METHODS: The current study matched multiple disparate datasets, including medical data, flight plan and track data, passenger statistics, and financial data. Chi-squared analysis and independent samples t-tests compared diversion delays and costs metrics between flights diverted for medical vs. nonmedical reasons. Data were restricted to domestic flights between 1/1/2018 and 6/30/2019.RESULTS: Over 70% of diverted flights recover (continue on to their intended destination after diverting); however, flights diverted due to IFMEs recover more often and more quickly than do flights diverted for nonmedical reasons. IFME diversions introduce less delay overall and cost less in terms of direct operating costs and passenger value of time (averaging around 38,000) than do flights diverted for nonmedical reasons.DISCUSSION: Flights diverted due to IFMEs appear to have less impact overall than do flights diverted for nonmedical reasons. However, the lack of information related to costs for nonrecovered flights and the decision factors involved during nonmedical diversions hinders our ability to offer further insights.Lewis BA, Gawron VJ, Esmaeilzadeh E, Mayer RH, Moreno-Hines F, Nerwich N, Alves PM. Data-driven estimation of the impact of diversions due to in-flight medical emergencies on flight delay and aircraft operating costs. Aerosp Med Hum Perform. 2021; 92(2):99105.
Very Light Jets (VLJs), the first of which entered service in 2007, offer improved priceperformance characteristics over existing turbinepowered models; yet the aviation industry remains divided about their commercial viability. This paper presents an analysis of the market potential for air taxi services planning to operate VLJs, since this business model is considered by many to be the cornerstone of future VLJ demand. The methodology employs a spreadsheet-based mode choice model that compares travel by VLJ air taxi, car, and scheduled airline. A Monte Carlo simulation analysis suggests that individuals from high income households traveling short distances (about 300 miles) are most likely to select the air taxi option. The probabilistic results are applied to a base of annual person trips to obtain a VLJ air taxi forecast of 15.6 million person trips in 2016. The approach is extended to estimate a median fleet size of 3,820 VLJs required to serve this demand. These results suggest that the most aggressive VLJ forecasts are least likely to materialize.
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