This article http://news.bbc.co.uk/2/hi/science/nature/3085885.stm claims:

Astronomers in Australia say there are 10 times more stars in the visible Universe than all the grains of sand on the world's beaches and deserts.

...

The figure - presented to the International Astronomical Union conference in Sydney - is the kind that really can be called astronomical: 70 sextillion, or seven followed by 22 zeroes.

I have been unable to find a source for this comparison (e.g. an article or presentation by the authors) other than the BBC article itself.

The only estimation that I found online in relation to this claim is an exercise that was put up by Howard C. McAllister, a Professor of Physics University of Hawaii at Manoa here: http://www.hawaii.edu/suremath/jsand.html

Is there any way to verify or measure how reliable is this comparison?

Comparing the two estimates:

The star count estimate is documented in Astrobiology Magazine (Hat-tip Oliver_C):

At this week's General Assembly of the International Astronomical Union in Sydney, the researchers put forward their big number: 70 sextillion, or 70,000,000,000,000,000,000,000 [seven followed by twenty-two zeros]. Previous estimates were approximately twenty-five percent smaller. "This is not the total number of stars in the universe, but it's the number within the range of our telescopes," said Driver.

There's no error range cited here, but given the previous estimates are only 25% different, using 7×1022 seems reasonable.

The grains-of-sand estimate is already discussed in another Skeptics.SE question, where Thomas_O explains:

Estimating the number of grains of sand on Earth is difficult. This source suggests 7.5x10^18 grains, but only includes beaches (deserts, under-sea sand and other sources not included.) This source suggests 10^20 to 10^24 grains.

So, the lower number there, 7.5×1018 doesn't include the deserts explicitly included in the original quote; we can discard that.

The second estimate has a wide (two orders of magnitude) error range, which covers the star estimate.

So, the estimates we have previously found of the number of grains of sand in the world aren't accurate enough to answer the question.

  • In editing this, I've just noticed the circle-of-life nature of the argument. The second estimate for grains of sand is actually from a site comparing it to stars! – Oddthinking Apr 25 '12 at 0:00
  • if you go by volume earth can hold 1.1*10^30 grains of sand when you assume that each grain of sand is 1mm^3 but given that large portions of earth isn't sand... – ratchet freak Apr 25 '12 at 0:16
  • You are using a lower bound for the number of stars. Other sources give a number two orders of magnitude bigger. That doesn’t change the fact that the error margins overlap, though. – Konrad Rudolph Apr 25 '12 at 14:47
  • @Konrad, do you have a reference for such a source, so we can edit it in? – Oddthinking May 14 '12 at 23:02
  • @Oddthinking I had a resource. Unfortunately, I cannot find it at the moment. I’ll try to remember where I got that from but it doesn’t change the gist of the answer anyway. – Konrad Rudolph May 15 '12 at 8:54

Here's a thoughtful analysis in plain English.

It concludes there are easily more grains of sand on the world’s beaches than there are stars in our (visible) Universe.

So by my rough estimate, there are easily more grains of sand on our planet’s beaches (by at least two, maybe three magnitudes) than there are stars in our known visible Universe.

Stars or Sand? Are there more Grains of Beach Sand or Stars in our Visible Universe?

This article has abundant references to the number of stars in our galaxy and the number of galaxies and it provides measurements of sand grains made with a precise instrument.

  • 3
    Unfortunately, this article doesn’t cite its sources and uses estimates for the number of stars that are several orders of magnitude below the lowest estimate that the other answer uses, and thus below the lowest estimate used by astronomers. I’m also guessing that it over-estimates the grains of sand since that analysis is very rough and done in such a way as to exponentially accumulate estimation errors, which essentially makes it useless. – Konrad Rudolph May 15 '12 at 8:59

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