Comparing airfares instead of seat size fairer indicator of passenger carbon emissions

Allocating passenger aircraft emissions using airfares rather than travel class would give a more accurate idea of individual contributions, finds a study led by UCL.

Emissions calculators base their estimates on travel class, assuming that someone travelling in a higher class and therefore taking up more space on the plane is responsible for more emissions.

The study, published in Environmental Research Letters, describes how including airfares in calculations shows which passengers contribute the most revenue to the airline operating the aircraft, thereby allowing the plane to fly.

Although in general, premium (business) seats are more expensive than economy, the researchers found when looking at data that many late bookings in economy class, often made for business trips or by high income travellers, cost as much as, or more than, premium seats.

Lead author Dr Stijn van Ewijk (UCL Civil, Environmental & Geomatic Engineering) said: "The paper shows we should follow the money when calculating emissions of individual travellers, as it is revenue that decides whether an airline can operate a plane or not. Someone who has paid twice as much as a fellow traveller contributes twice as much to the revenue of the airline and should be allocated twice the emissions. The seat size of each travel class, which is currently used to allocate emissions, is only a rough approximation of how much passengers pay."

The researchers say that using airfares to calculate passenger emissions would benefit efforts to address climate change by encouraging people on all budgets to find alternative modes of transport where possible. It would also increase estimates of corporate emissions because it allocates more to expensive late bookings, which are often made for business purposes.

Implementing a tax that is proportionate to the price of the ticket could make the total costs of flying fairer. People buying the most expensive tickets would pay the highest tax, encouraging them to seek alternatives.

Whilst taxes differ between countries, typically the rates are the same across each travel class. Travellers buying expensive tickets, who are more likely to have higher incomes, pay a relatively low tax and are not currently discouraged from flying.

Dr Van Ewijk added: "An equitable approach to reducing airline emissions should not just deter travellers who can only afford the cheapest early bookings but also the big spenders who bankroll the airline. By assigning emissions based on ticket prices, and taxing those emissions, we can make sure everyone pays their fair share, and is equally encouraged to look for alternatives."

A ticket tax should also take into account the distance flown and the model and age of plane, which can indicate how polluting it is.

The authors used a dataset from the USA to test their fare-based allocation approach. They used the Airline Origin Survey database, which includes ticket fare data, origin and destination, travel class and fare per mile. From this, they calculated the distribution of ticket prices across all passengers on a typical flight.

Based on the price distribution, the authors allocated emissions to passengers, and compared the results with estimates from widely used emissions calculators. Since ticket prices vary strongly by time of booking, the emissions per passenger varied too, far more than on the basis of seat size and travel class.

Using an economic supply-demand model, the researchers estimated how a carbon tax on emissions would affect travellers, depending on whether the emissions the tax applied to were calculated from seat size and travel class, or the airfare. In all scenarios, a tax on emissions calculated from airfares had a more equitable effect because it reduced flying more evenly across income groups.

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Engineers uncover the secrets of fish fins

Peer into any fishbowl, and you'll see that pet goldfish and guppies have nimble fins. With a few flicks of these appendages, aquarium swimmers can turn in circles, dive deep down or even bob to the surface.

New research led by the University of Colorado Boulder has uncovered the engineering secrets behind what makes fish fins so strong yet flexible. The team's insights could one day lead to new designs for robotic surgical tools or even airplane wings that change their shape with the push of a button.

The researchers published their results Aug. 11 in the journal Science Robotics.

Francois Barthelat, senior author of the study, noted that fins are remarkable because they can achieve feats of dexterity even though they don't contain a single muscle. (Fish move these structures by twitching sets of muscles located at the base of the fins).

"If you look at a fin, you'll see that it's made of many stiff 'rays,'" said Barthelat, professor in the Paul M. Rady Department of Mechanical Engineering. "Each of those rays can be manipulated individually just like your fingers, but there are 20 or 30 of them in each fin."

In their latest research, Barthelat and his colleagues drew on a range of approaches, including computer simulations and 3D-printed materials, to dive deep into the biomechanics of these agile structures. They report that the key to fish fins may lie in their unique design. Each ray in a fin is made up of multiple segments of a hard material that stack on top of much softer collagen, making them the perfect balance between bouncy and stiff.

"You get this dual capability where fins can morph, and yet they're still quite stiff when they push water," he said.

Armor and airplanes

Barthelat is no stranger to looking into aquariums. He previously studied how fish scales can help engineers to design better body armor for humans, and how seashells might inspire tougher glasses.

Fins may be just as useful. When it comes to engineering, Barthelat explained, materials that are both stiff and flexible are a hot commodity. Airplane designers, for example, have long been interested in developing wings that can morph on command, giving planes more ability to maneuver while still keeping them in the air.

"Airplanes do this now, to some extent, when they drop their flaps," Barthelat said. "But that's in a rigid way. A wing made out of morphing materials, in contrast, could change its shape more radically and in a continuous manner, much like a bird."

To understand how ordinary run-of-the-mill goldfish achieve similar feats every day, take a close look at these structures under the microscope. Each of the rays in a fin has a layered structure, a bit like a bakery éclair: The spikes include two layers of stiff and mineralized materials called hemitrichs that surround an inner layer of spongy collagen.

But, Barthelat said, those layers of hemitrichs aren't solid. They're divided into segments, as if someone had cut up the éclair into bite-sized pieces.

"Until recently, the function of those segments hadn't been clear," he said.

Swimming, flying and walking

The engineer and his team decided to use computer simulations to examine the mechanical properties of fins. They discovered that those segments can make all the difference.

Pretend for a moment, Barthelat explained, that fish fins are made up entirely of collagen. They could bend easily, but wouldn't give fish much traction in the water because hydrodynamic forces would collapse them. Rays made up of solid, non-segmented hemitrichs, in contrast, would have the opposite problem -- they'd be way too stiff.

"All of the segments, essentially, create these tiny hinges along the ray," Barthelat said. "When you try to compress or pull on those bony layers, they have a very high stiffness. This is critical for the ray to resist and produce hydrodynamic forces that push on water. But if you try to bend individual bony layers, they're very compliant, and that part is critical for the rays to deform easily from the base muscles."

The researchers further tested the theory by using a 3D printer to produce model fish fins made from plastic, some with those hinges built in and some without. The idea panned out: The team found that the segmented design provided better combinations of stiffness and morphing capabilities.

Barthelat added that he and his colleagues have only scratched the surface of the wide diversity of fins in the fish world. Flying fish, for example, deploy their fins to glide above the water, while mudskippers use their fins like legs to walk on land.

"We like to pick up where the biologists and zoologists have left off, using our background in the mechanics of materials to further our understanding of the amazing properties of the natural world," Barthelat said.

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How at risk are you of getting a virus on an airplane?

Fair or not, airplanes have a reputation for germs. However, there are ways to minimize the risks.

Historic research based on group movements of humans and animals suggest three simple rules:

• move away from those that are too close.
• move toward those that are far away.
• match the direction of the movement of their neighbors.

This research is especially used for air travel where there is an increased risk for contagious infection or disease, such as the recent worldwide outbreak of the coronavirus, which causes COVID-19 disease.

"Airlines use several zones in boarding," said Ashok Srinivasan, a professor in the Department of Computer Science University of West Florida. "When boarding a plane, people are blocked and forced to stand near the person putting luggage in the bin -- people are very close to each other. This problem is exacerbated when many zones are used. Deplaning is much smoother and quicker -- there isn't as much time to get infected."

Srinivasan is the principal investigator of new research on pedestrian dynamics models that has recently been used in the analysis of procedures to reduce the risk of disease spread in airplanes. The research was published in the journal PLOS ONE in March 2020.

For many years scientists have relied on the SPED (Self Propelled Entity Dynamics) model, a social force model that treats each individual as a point particle, analogous to an atom in molecular dynamics simulations. In such simulations, the attractive and repulsive forces between atoms govern the movement of atoms. The SPED model modifies the code and replaces atoms with humans.

"[The SPED model] changes the values of the parameters that govern interactions between atoms so that they reflect interactions between humans, while keeping the functional form the same," Srinivasan said.

Srinivasan and his colleagues used the SPED model to analyze the risk of an Ebola outbreak in 2015, which was widely covered in news outlets around the world. However, one limitation of the SPED model is that it is slow -- which makes it difficult to make timely decisions. Answers are needed fast in situations such as an outbreak like COVID-19.

The researchers decided there was a need for a model that could simulate the same applications as SPED, while being much faster. They proposed the CALM model (for constrained linear movement of individuals in a crowd). CALM produces similar results to SPED, but is not based on MD code. In other words, CALM was designed to run fast.

Like SPED, CALM was designed to simulate movement in narrow, linear passageways. The results of their research shows that CALM performs almost 60 times faster than the SPED model. Apart from the performance gain, the researchers also modeled additional pedestrian behaviors.

"The CALM model overcame the limitations of SPED where real time decisions are required," Srinivasan said.

Computational Work Using Frontera

The scientists designed the CALM model from scratch so it could run efficiently on computers, especially on GPUs (graphic processing units.

For their research, Srinivasan and colleagues used Frontera, the #5 most powerful supercomputer in the world and fastest academic supercomputer, according to the November 2019 rankings of the Top500 organization. Frontera is located at the Texas Advanced Computing Center and supported by National Science Foundation.

"Once Blue Waters started being phased out, Frontera was the natural choice, given that it was the new NSF-funded flagship machine," Srinivasan said. "One question you have is whether you have generated a sufficient number of scenarios to cover the range of possibilities. We check this by generating histograms of quantities of interest and seeing if the histogram converges. Using Frontera, we were able to perform sufficiently large simulations that we now know what a precise answer looks like."

In practice, it isn't feasible to make precise predictions due to inherent uncertainties, especially at the early stages of an epidemic -- this is what makes the computational aspect of this research challenging.

"We needed to generate a large number of possible scenarios to cover the range of possibilities. This makes it computationally intensive," Srinivasan said.

The team validated their results by examining disembarkation times on three different types of airplanes. Since a single simulation doesn't capture the variety of human movement patterns, they performed simulations with 1,000 different combinations of values and compared it to the empirical data.

Using Frontera's GPU subsystem, the researchers were able to get the computation time down to 1.5 minutes. "Using the GPUs turned out to be a fortunate choice because we were able to deploy these simulations in the COVID-19 emergency. The GPUs on Frontera are a means of generating answers fast."

But Wait -- Models Don't Capture Extreme Events? In terms of general preparation, Srinivasan wants people to understand that scientific models often don't capture extreme events accurately.

Though there have been thorough empirical studies on several flights to understand human behavior and cleanliness of the surfaces and air, a major infection outbreak is an extreme event -- data from typical situations may not capture it.

There are about 100,000 flights on an average day. A very low probability event could lead to frequent infection outbreaks just because the number of flights is so large. Although models have predicted infection transmission in planes as unlikely, there have been several known outbreaks.

Srinivasan offers an example.

"It's generally believed that infection spread in planes happens two rows in front and back of the index patient," he said. "During the SARS outbreak in 2002, on the few flights with infection spread, this was mostly true. However, a single outbreak accounted for more than half the cases, and half of the infected were seated farther than two rows away on that flight. One might be tempted to look at this outbreak as an outlier. But the 'outlier' had the most impact, and so people farther than two rows away accounted for a significant number of people infected with SARS on flights."

Currently, with regard to COVID-19, the typical infected person is believed to sicken 2.5 others. However, there have been communities were a single 'super-spreader' infected a large number of people and played the driving role in an outbreak. The impact of such extreme events, and the difficulty in modeling them accurately, makes prediction difficult, according to Srinivasan.

"In our approach, we don't aim to accurately predict the actual number of cases," Srinivasan said. "Rather, we try to identify vulnerabilities in different policy or procedural options, such as different boarding procedures on a plane. We generate a large number of possible scenarios that could occur and examine whether one option is consistently better than the other. If it is, then it can be considered more robust. In a decision-making setting, one may wish to choose the more robust option, rather than rely on expected values from predictions."

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