4 ms·

I was curious about how much salt was in the ocean. There is approximately 50 quintillion kilograms of salt in the ocean, which is nearly the mass of the moon

by AaronM 6y ago

I was curious about how much salt was in the ocean. There is approximately 50 quintillion kilograms of salt in the ocean, which is nearly the mass of the moon From this website https://scripps.ucsd.edu/news/what-makes-ocean-salty-and-how-much-salt-ocean https://scripps.ucsd.edu/news/what-makes-ocean-salty-and-how...

danw1979 6y ago
I’m no quantity surveyor, but that sounds like someone placed the decimal point blindfolded in that calculation. A quick google says the mass of just the water on Earth is 0.02% of total mass and the mass of the moon is 1.2% of Earth’s. Someone please point out my mistake.
- frandroid 6y ago
  "Thanks for pointing out this mistake. Since we currently have no quantity surveyor, we would like to hand over control of the Planetary Quantity Survey repository to you. This is an open source project with no pay which requires 80 hours of thankless work a week. Good luck!"
- dwaltrip 6y ago
  Your numbers sound more correct to me. The moon is a decently hefty object.
- jbotz 6y ago
  The mistake is in the original citation... the moon's mass in 7x10^22 kg, and the number they gave for salt in the ocean (which I haven't verified) was 5x10^19 kg, so that would mean that the moon is about 1000 times heavier than the salf in the ocean... hardly 'nearly the mass of the moon'.
  - thechao 6y ago
    I dunno. The moon's pretty big. Even if you're off by a factor of 1000, it's still ... a lot.
    - mikorym 6y ago
      This is why the need arose for talking about "orders of magnitude". If you use base 10, the order is 3, which is generally considered as a large difference. For a related reason you need "big oh" notation for computing speeds. But in that case the magnitude difference over larger numbers is what you are interested in. The difference between O(n) and O(n^2) can grow to an arbitrary magnitude difference. If you want a difference of 1000, then take n = 1000, and you get O(n|n = 1000) = 1000 and O(n^2|n=1000) = 1 000 000. But if you take n = 1 000 000, the ratio is now 1 000 000 = 1 000 000 / 1 000 000 000 000. So, a badly written sort function can get pretty bad with large arrays. Anyway, the latter is just tangential to show that indeed as you say, context is important (abundance and total need for a resource) and factors vs. growth-in-factors over large numbers are different. Resources scale linearly to use in product output, however, so the "big oh" (counter-)analogy is just for the sake of interest.

by AaronM 6y ago

danw1979 6y ago

I’m no quantity surveyor, but that sounds like someone placed the decimal point blindfolded in that calculation. A quick google says the mass of just the water on Earth is 0.02% of total mass and the mass of the moon is 1.2% of Earth’s. Someone please point out my mistake.

frandroid 6y ago
"Thanks for pointing out this mistake. Since we currently have no quantity surveyor, we would like to hand over control of the Planetary Quantity Survey repository to you. This is an open source project with no pay which requires 80 hours of thankless work a week. Good luck!"
dwaltrip 6y ago
Your numbers sound more correct to me. The moon is a decently hefty object.
jbotz 6y ago
The mistake is in the original citation... the moon's mass in 7x10^22 kg, and the number they gave for salt in the ocean (which I haven't verified) was 5x10^19 kg, so that would mean that the moon is about 1000 times heavier than the salf in the ocean... hardly 'nearly the mass of the moon'.
- thechao 6y ago
  I dunno. The moon's pretty big. Even if you're off by a factor of 1000, it's still ... a lot.
  - mikorym 6y ago
    This is why the need arose for talking about "orders of magnitude". If you use base 10, the order is 3, which is generally considered as a large difference. For a related reason you need "big oh" notation for computing speeds. But in that case the magnitude difference over larger numbers is what you are interested in. The difference between O(n) and O(n^2) can grow to an arbitrary magnitude difference. If you want a difference of 1000, then take n = 1000, and you get O(n|n = 1000) = 1000 and O(n^2|n=1000) = 1 000 000. But if you take n = 1 000 000, the ratio is now 1 000 000 = 1 000 000 / 1 000 000 000 000. So, a badly written sort function can get pretty bad with large arrays. Anyway, the latter is just tangential to show that indeed as you say, context is important (abundance and total need for a resource) and factors vs. growth-in-factors over large numbers are different. Resources scale linearly to use in product output, however, so the "big oh" (counter-)analogy is just for the sake of interest.