I won’t comment on the final accuracy, but I will note that this is an extremely roundabout path to your final answer, and some of the intermediate steps are…weird. Most notably, the speculation that every man, woman, and child on the planet might run a 1 kW appliance 24/7/365. This is 7e13 kWh or 70k TWh, about 3x current global energy use (not just electicity) before accounting for efficiency. The equation you cite for radiative forcing, specifically its ln(new/old) term is very non-linear, so you should get a much lower marginal effect from 70k TWh than from 1 kWh.
A simpler approach is to calculate the CO2 required for your 1 kWh AC, i.e.: 1kWh * 3600 kJ/kWh / 0.6 efficiency / 890 kJ/mol = 6.7 mol CO2. Current atmospheric CO2 is 75 Pmol. From that, I get radiative forcing of ln((7.4e16 + 6.7)/7.4e16)/ln(2)3.7 * 4pi*(6.4e6^2). Numpy won’t tell me what ln(74000000000000006.7/74000000000000000). It will tell me the forcing from 10 kWh is ~2.5W, or the same 0.25W/kWh you got. I guess ln is not that nonlinear in the 1+1e-16 to 1+1e-4 range, after all.
0.25W/kWh seems improbably high. 1 kWh is about 0.1 W running 24/365. At 60% efficiency, that’s burning 0.2W of natural gas and implies that the radiative forcing from CO2 is much greater than the energy to produce the CO2 in the first place. I get that the energy source for heating is different from the energy source for electricity, but it feels wrong, even without the 1000 year persistence. I don’t know where the radiative forcing equation came from nor its constraints, so I’m suspicious of its application in this context. There’s a lot of obscenely large numbers interacting with obscenely small numbers, and I don’t know enough to say whether those numbers are accurate enough for the results to be reasonable. Then there’s the question of converting the energy input to temperature change.
Numpy won’t tell me what ln(74000000000000006.7/74000000000000000).
Ran into exactly this problem for individual calculation 😆. Which is also why I multiplied by 8 billion and divided in the end - make the calculator behave. ln is linear enough around 1±epsilon to allow this.
implies that the radiative forcing from CO2 is much greater than the energy to produce the CO2 in the first place
That’s what I wanted to find out and it does appear to look exactly that way. Makes sense in retrospect since the radiative forcing is separate from the energy content of CO2 itself, same way as a greenhouse gets hot for no energy expended on its own.
Numpy won’t tell me what ln(74000000000000006.7/74000000000000000). Ran into exactly this problem for individual calculation
Trouble is that 74000000000000006.7/74000000000000000 ~ 1.000 000 000 000 000 1 and double-float precision is 0.000 000 000 000 000 2. Needs a 96 or 128 bit float. The whole topic of estimating one’s personal contribution to global phenomena is loaded with computer precision risks, which is part of what makes me skeptical of the final result, without looking far more closely than my interest motivates. Like calculating the sea level rise from spitting in the ocean - I believe it happens, but I’m not sure I believe any numerical result.
Your skepticism is excessively cautious 😁. You can work around precision limits perfectly fine as long as you are aware they exist there. Multiplying your epsilon and then dividing later is a legitimate strategy, since every function is linear on a small enough scale! You can even declare that ln(1+x) ~= x and skip the logarithm calculation entirely. Using some random full precision calculator I get:
<span style="color:#323232;">ln(1+x) ~= x
</span><span style="color:#323232;">6.7/74e15 = 9.0540540...e-17
</span>
You are worried about differences in the final answer of less than 1 part in a million! I try to do my example calculations in 3 significant figures, so that’s not even a blip in the intermediate roundoffs.
I know this is kind of off topic but I wanted to point out that the refrigerant that escapes from air conditioners when they leak or are thrown away, is a bigger contributor to climate change than the electricity they use.
Good point! Freon (CFC-12, with 10800x warming potential of CO2) has thankfully been banned by Montreal Protocol of 1987, and HCFC-22 (5280x) is being phased out. We are using what now, HFC-32 at 2430x? How much refrigerant does an AC contain, about a mole? I’ve been taught that refrigerant should normally never leak throughout the lifetime of the appliance (technicians are even prohibited from “recharging” refrigerant without identifying and fixing the point of the leak first) and that all gas must be recovered after end-of-life, but we can’t be sure that’s really what happens every time.
In that case leaking 1 mole of HFC-32 would be equivalent to… running the 1kW AC for 360 hours?
In my experience with the automotive industry. AC systems leak frequently and it is very common for the leak to be so small that it is not always possible to find the source.
So the majority of the time a fluorescent dye is added to the system and it is recharged with refrigerant to help find the source when it gets low again.
It’s common to have a leak so slow and undetectable that no one notices a system is low on refrigerant until a year later when it is summer again.
Also, auto parts stores sell cans of refrigerant so anybody can just recharge a leaking system, which is often cheaper than actually fixing the leak. So these AC systems are just constantly leaking refrigerant and being recharged.
I wouldn’t be surprised if AC systems in buildings are handled similarly.
Even if a law is made that a failed part must be identified before the system can be recharged, the technician who can’t find a leak is going to just pick a part (randomly or educated guess) to replace if he can’t find the leak.
The answer is 1:1, conservation of energy means that 1kWh of energy going into the AC you introduce near as makes no difference 1kWh of heat energy into the world. The wonderful thing AC does is amplify that cooling or heating by moving heat from one place to another meaning modern systems can move 5kW of heat using only 1kW of energy. In this example 6kW is outside but you have removed 5kW from inside so it’s still just 1kW net.
If you want to reduce the impact of using your AC you need firstly insulate the crap out of your house to prevent heat escaping or entering. Then you can delve into the world of Mechanical Ventilation Heat Recovery (MVHR), sealing all the air gaps in your home, at least quad-glazing, and finally passive cooling (sun shades over your windows).
Edit: sorry forgot to say for solar powered AC - which is 100% of my systems. I’m ignoring the grid for the above as the only systems I install are combined with at least 3x kW of solar and batteries so they never use grid power.
People are inherently bad at rating things. Why not run a “This or that?” style study instead?
Given a list of items to rate, pair them up randomly. Ask a person which item they like better out of each pair. Run through Final Four type eliminations until you get down to their number one preference.
Run through this process for each person, beginning with different random pairings every time.
Record data on all the choices - not just the final ones. You should be able to get good data like that.
For example, there will probably be a thing that is so disliked that it gets eliminated in the first round more frequently than anything else. The inverse will likely be true of a highly-preferred item. And I am sure you can identify other insights as well.
Sounds like a good idea, however my participants neither have the attention span nor do I have the resources to do anything else :) after all, like I said, it’s just a small personal thing :)
Can you give more context to where the phrasing is used? Coming from a computer science angle, there are different data types for different things. For instance, you would use a “float” (floating point) data type to store a number like 7.12. Likewise, you use an “int” to store a whole number (such as 7). Because computers use a certain number of bits to store information, this means there’s a max size to your data. int data types specifically have a “signed int” option as well as an “unsigned int” (the latter being a non negative integer). The benefit there is that by not storing a sign, the int can store numbers about 2x as large as a signed int.
If I dont need to ever store a negative value, I might explicitly call out that when writing out an algorithm
An “integer” is a whole number- a number that isn’t a fraction/decimal. You can have negative integers/whole numbers, and 0 is also an integer that isn’t truly positive or negative.
If you specify that you want a positive whole number/integer that technically wouldn’t include 0, same if you specify a negative number.
So if you’re looking for a value that is a whole number that is either zero or positive “non-negative integer” is probably the most succinct way to phrase it.
They can also be called “natural numbers” but depending on context, that may not always include 0.
According to Randall Munroe (the author behind xkcd.com) in his book ‘what if? 2’ a house sized cumulus cloud, which would be very small for a cloud, contains roughly one litre of water, which in turn weighs 1 kilogramm.
If you want to look it up and somehow find a version of the book online, this information is in the chapter about the largest thing you could theoretically eat in one sitting (it’s the cloud).
Newton’s 3rd law applies. Both vehicles experienced an equal force of impact because it is implied there were no other relevant external forces, but their individual accelerations will be different.
In the newer editions it’s removed. On the older ones there’s no introduction of “impact force”. Maybe it’s just impulse they are talking about. Thanks for taking the time!
Unhealthy, processed food is cheaper to produce, cheaper to buy and more appealing to the consumer. Couple that with a society which is trending towards a more sedentary lifestyle and obesity rates climb. The issue is we’re seeing the results of this about 20 years too late to do anything to reverse the effects.
Should mention that I’m in the UK, but the story is a similar one; albeit currently slightly less extreme.
More people have been eating ultra-proccessed food low in nutrition and high in calories. They’ve gotten fat because nutritious food is expensive. But don’t worry, it’s not a plan by our Fat Cat overlords to extort is all for healthcare $$$, I’m sure we’re just headed for a Wall-E future for is all…(nervous laugh)…;(
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