Both studies were published in a top journal in the area (13% acceptance rate) and have respectable university professors in the area among their authors. The reason other studies did not found the same thing is because they weren’t looking at that range. The common assumption was that anything below 800ppm is equally perfect. You will find some blogs in the area giving this same explanation. The effect size really is suspiciously huge, but it is not entirely implausible either given that we already know CO2 does have a brutal effect on cognition at higher ppm and understand the mechanism fairly well.
Anders made the following calculations. A human consumes about 45 liters of oxygen per hour, producing about 10 liters of carbon dioxide per hour. To maintain a good CO2 level you want 8-10 l/s/person in an office. Now, if the airspeed is 0.15 m/s (about the limit of drafty) you need 0.01/ 0.15 = 6.7 cm^2 window area.
My credence on the finding being true is high. Even if it is false, the cost would be leaving the window very slightly opened (6.7cm2 is pretty small), or opening in every other hour. I’ve been doing so since the last study came out and I would add the room also feels more pleasant like that.
The quoted calculation seems to assume that the indoor air is 100% CO2, when in fact it is about 0.1% CO2? So your conclusions seem to be off by a factor of 1000. Actually a factor of 5000 if you are trying to maintain 600ppm, since the outdoor air also has 400ppm and presumably the net flux is 0.
ETA: Actually maybe that was how you moved from l/hour to l/second, your figures seem about right for keeping levels at 700ppm assuming your airspeed.
Also a cracked window just doesn’t seem to do it empirically.
My credence on the finding being true is high.
I had also seen the replication, and I believe that the paper correctly reports the result of an experiment. (And its certainly not publication bias with p < 0.0001 or whatever.) The question is whether a particular interpretation of the results is correct. At a minimum it depends on just what the test is measured.
Here’s another study which found the same thing: http://ehp.niehs.nih.gov/wp-content/uploads/advpub/2015/10/ehp.1510037.acco.pdf
Both studies were published in a top journal in the area (13% acceptance rate) and have respectable university professors in the area among their authors. The reason other studies did not found the same thing is because they weren’t looking at that range. The common assumption was that anything below 800ppm is equally perfect. You will find some blogs in the area giving this same explanation. The effect size really is suspiciously huge, but it is not entirely implausible either given that we already know CO2 does have a brutal effect on cognition at higher ppm and understand the mechanism fairly well.
Anders made the following calculations. A human consumes about 45 liters of oxygen per hour, producing about 10 liters of carbon dioxide per hour. To maintain a good CO2 level you want 8-10 l/s/person in an office. Now, if the airspeed is 0.15 m/s (about the limit of drafty) you need 0.01/ 0.15 = 6.7 cm^2 window area.
My credence on the finding being true is high. Even if it is false, the cost would be leaving the window very slightly opened (6.7cm2 is pretty small), or opening in every other hour. I’ve been doing so since the last study came out and I would add the room also feels more pleasant like that.
The quoted calculation seems to assume that the indoor air is 100% CO2, when in fact it is about 0.1% CO2? So your conclusions seem to be off by a factor of 1000. Actually a factor of 5000 if you are trying to maintain 600ppm, since the outdoor air also has 400ppm and presumably the net flux is 0.
ETA: Actually maybe that was how you moved from l/hour to l/second, your figures seem about right for keeping levels at 700ppm assuming your airspeed.
Also a cracked window just doesn’t seem to do it empirically.
I had also seen the replication, and I believe that the paper correctly reports the result of an experiment. (And its certainly not publication bias with p < 0.0001 or whatever.) The question is whether a particular interpretation of the results is correct. At a minimum it depends on just what the test is measured.