- At the charging stations, daily concentrations of dangerous air particles, known as PM2.5, ranged from 7.3 to 39.0 micrograms per cubic meter.
- Urban sites without fast-charging stations had concentrations of PM2.5 ranging from only 3.6 to 12.4 micrograms per cubic meter.
- The tiny particles likely come from particle resuspension around Direct Current Fast Charging power cabinets. Cooling fans designed to prevent the electronics from overheating can also stir up dust and particles from internal surfaces.
Now do PM and VOC levels at petrol stations.
Then PM and VoC levels on roads entirely occupied by combustion vehicles, and entirely occupied by electric vehicles.
It’s like this is perfectly crafted to demonstrate a spurious correlation.
I get what you’re saying but I’m not seeing this as “electric cars suck” but more as “we found another place where we can improve”
This seems to me an issue that can be fixed with a few air filters which would require very infrequent replacements
2.5 takes some fairly serious filters.
Then make those serious filters obligatory
I too love a heavy dose of whataboutism with my science.
I think we all know petrol is worse by a huge margin. More knowledge about electric vehicles and their effects is just more good for engineers.
It means there is more room to improve and make things better.
It’s a thing called data bestie
- The tiny particles likely come from particle resuspension around Direct Current Fast Charging power cabinets. Cooling fans designed to prevent the electronics from overheating can also stir up dust and particles from internal surfaces.
a) that doesn’t really sound like the fault of EVs or the charging stations themselves. Any sort of very moderate air current would cause the same problem.
b) that sounds pretty easy to fix with some filters simple pleated filters, and that would leave the surrounding environment cleaner than they used to be.
a) that doesn’t really sound like the fault of EVs or the charging stations themselves. Any sort of very moderate air current would cause the same problem.
Excactly. The stations themselves don’t create particles but magnetic fields from the high voltage DC lines and cooling fans just pick them up from the ground and back to air. It’s quite misleading to claim this is “Fine particulate matter emissions from electric vehicle fast charging stations” as the stations just redistribute existing emissions.
Obviously this is not a good thing, but the underlying cause is something else than these stations, I’d bet considerable amount of it comes from combustion engines. And as you said, simple filters should fix the problem and clean up the pollution from environment as well.
From the people who think windmills cause cancer?
Also they’re likely in more densely populated areas which already have lower air quality.
This seems accounted for since the comparative samples are from “similarly urban areas”
Jesus they will release any study to try and smear electric. It’s the same argument as cigs vs vapes. Yes they’re both bad and not the best solution, but one is obviously better than the other. Plus how are they separating contamination of the charging stations from any other area where normal ass cars operate. There’s just as much of a chance if not more that those particles are from the gas vehicles driving around, and not something specific to the chargers.
They’re not separating data throughly. Researcher Yifang Zhu, over many publishings, mainly gathers and publishes raw findings. Such as… (summarizing) “Children are at risk due to immature respiratory systems and faster breathing rates… by traveling in diesel powered school buses in my South Texas study.”
Source- https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kvSIKM8AAAAJ&cstart=20&pagesize=80&citation_for_view=kvSIKM8AAAAJ%3A5nxA0vEk-isCDafuq.
This is the craziest reaction to knowledge
Knowing something new we didn’t before means… We know more now.
Stop trying to politicize this.
This just means there is room to improve, this is a good thing.
i don’t know if i would take this study as “knowledge”. that map of the us? it’s just a map of chargers, not of data from the study. reading the study, they were only measuring in one county. there’s no categorisation of the type of fast charger they measured, just “a variety”. the error bars overlap enough that this could all be errors. and why only measure at fast chargers and gas stations? why not at other high-power electrical systems like transformer yards in urban areas? they alno have fans, surely.
question is, why publish it if it is so obviously (and willfully) wrong?
Urban backgrounds n=4 and gas stations n=8
are you fucking kidding me
Why higher particulate matter was found in the air at EV-charging stations?
Because your sample sizes are shit, which means your methodology is probably also shit and the report carries less weight than a shampoo advert statistics
Look at the map this is just higher near larger population, Correlation vs. Causation. This smells like bull shit.
A research participant, Yifang Zhu, is tied to a thing called Mobility Justice Frameworks. It’s pushing for greenspaces in urban areas, including making existing infrastructures look bad for its cause(s).
The research team has more A.I. tools than proper researching. It’s odd.
Do you not see the summary text in your front end, or did you just not read it? This is what it looks like on the default web front end on my instance:
I also saw where they used a graphic of the entire US when the study only encompasses 1 county in California.
Were those other urban areas specifically parking lots/garages? (The places that charging stations tend to be)
Wtf kind of article is this? This would be a great example of sampling bias.
Can’t wait for the “electric cars are killing children” research next
I just web searched the names of this research team… The last one on the list is a teeth-puller, folks.
Yuan Yao, teacher of sustainable systems.
Muchuan Niu, UCLA student, MS in Environmental Sciences.
Haoxuan Chen, Stanford student, machine learning.
Qiao Yu, Shanghai A.I. Laboratory.
Qingyang Wu, private A.I. developer.
Yuhang Li, student, Art History, A.I. cloud data processor.
Yijie Zhang, UCLA student, A.I. machine learning.
Aydogan Ozcan, UCLA, computational imaging and deep learning optics.
Michael Jerrett, teacher at UCLA, geographic information systems science, spatial exposure science.
Yifang Zhu, student in Environmental Sciences, associate of UCLA Fielding School project group, funds and\or law underwriter for Mobility Justice Frameworks (Mobility Justice is an almost eco-extremist entity that also uses racial cause to gather USDOT public funding).
My bottom-of-the-rabbit-hole best guess. Create premature science data media for campaigns for lawmakers to push for more greenspaces in urban areas.
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