One exciting thing from over the holidays is that the Int'l Civil Aviation Organization (@ICAO) and aircraft engine manufacturers for the first time publicly released quantitative emissions indices for particle # and mass emitted per unit fuel burn! 🧵 1/

https://t.co/zXuFN66SWe

Up until now, certification data for aircraft engine particle emissions have been reported in terms of a "smoke number", which is derived from the change in reflectance of a Whatman 4 filter after collecting 16.2 kg/m² exhaust. 2/

https://t.co/6fa9Kkdupr
One challenge with the smoke number measurement is that the filter doesn't capture all of the particles -- especially small ones. Is the decrease in smoke number over time because we are trading a few large soot particles for many more smaller soot particles? 3/
While smoke numbers are not particularly helpful for quantitatively assessing particle emissions impacts on air quality & upper tropospheric composition, they have been a huge success in motivating the reduction of unsightly exhaust plumes! 4/

Photo credit: flickr/dsleeter_2000
The new EI data are much more useful for #AirQuality and #Climate modeling efforts seeking to understand the environmental impacts of aviation. Since they're collected at ground conditions, the data are most relevant to AQ, but maybe can be extrapolated to cruise conditions? 5/
Of course, we still need to understand how well the certification EIs capture real world, near-surface emissions impacted by fuels, engine maintenance, and human behavior (e.g., reduced thrust takeoffs). 6/

Leipzig/Halle: https://t.co/ITMszAGSej

LAX: https://t.co/fSADIkoXEw
We also know that "spreading contrails and the cirrus clouds that evolve from them -- collectively known as contrail cirrus -- have a greater radiative forcing today than all aviation CO2 emissions since the first powered airplane flight" - B. Kärcher 7/

https://t.co/zLXnWyDCwc
If we can reduce engine soot particle emissions at cruise enough to fall below the soot-rich emissions regime (threshold ~ 10¹³ to 10¹⁴ per kg fuel) then that would translate into a reduction in climate-altering, aviation-induced cloudiness. 8/

https://t.co/Pi22W6Gw4Y
There are a number of promising approaches for meeting these targets in the short term including the use of sustainable, bio-based jet fuels as well as introduction of lean-burning combustion technologies. 9/

https://t.co/FSZWr27Tmg
Models of contrail formation and persistence provide the key to targeting these efforts when the economics might not make sense for widespread adoption of advanced (& expensive) biofuels. We can focus on large "contrail outbreaks" to have big impact! 10/

https://t.co/j3SmQwl0yy
The new ICAO aircraft engine particle emissions data released on Dec. 23rd are fertile ground for understanding how changes in engine technology (particularly advanced, lean-burning combustors) will impact the environment both near the ground and high above! 11/11
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Hard agree. And if this is useful, let me share something that often gets omitted (not by @kakape).

Variants always emerge, & are not good or bad, but expected. The challenge is figuring out which variants are bad, and that can't be done with sequence alone.


You can't just look at a sequence and say, "Aha! A mutation in spike. This must be more transmissible or can evade antibody neutralization." Sure, we can use computational models to try and predict the functional consequence of a given mutation, but models are often wrong.

The virus acquires mutations randomly every time it replicates. Many mutations don't change the virus at all. Others may change it in a way that have no consequences for human transmission or disease. But you can't tell just looking at sequence alone.

In order to determine the functional impact of a mutation, you need to actually do experiments. You can look at some effects in cell culture, but to address questions relating to transmission or disease, you have to use animal models.

The reason people were concerned initially about B.1.1.7 is because of epidemiological evidence showing that it rapidly became dominant in one area. More rapidly that could be explained unless it had some kind of advantage that allowed it to outcompete other circulating variants.
JUST ONE PERSON—UK 🇬🇧 scientists think one immunocompromised person who cleared virus slowly & only partially wiped out an infection, leaving behind genetically-hardier viruses that rebound & learn how to survive better. That’s likely how #B117 started. 🧵 https://t.co/bMMjM8Hiuz


2) The leading hypothesis is that the new variant evolved within just one person, chronically infected with the virus for so long it was able to evolve into a new, more infectious form.

same thing happened in Boston in another immunocompromised person that was sick for 155 days.

3) What happened in Boston with one 45 year old man who was highly infectious for 155 days straight before he died... is exactly what scientists think happened in Kent, England that gave rise to #B117.


4) Doctors were shocked to find virus has evolved many different forms inside of this one immunocompromised man. 20 new mutations in one virus, akin to the #B117. This is possibly how #B1351 in South Africa 🇿🇦 and #P1 in Brazil 🇧🇷 also evolved.


5) “On its own, the appearance of a new variant in genomic databases doesn’t tell us much. “That’s just one genome amongst thousands every week. It wouldn’t necessarily stick out,” says Oliver Pybus, a professor of evolution and infectious disease at Oxford.

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