Guest Post by Willis Eschenbach

[OK, had to start over, had bad numbers for the areas. Graphics have been replaced. I was using “core area” but I should have been using “greater metropolitan area”. All conclusions are unchanged.]

I got to thinking about the phenomenon known as the “Urban Heat Island” effect, or UHI. Cities tend to trap heat due to the amount of black pavement and concrete sidewalks, the narrow canyons between buildings that slow down the wind, and the sides of the buildings reflecting sunlight downwards.

As a result, cities are often warmer than the surrounding countryside. In some cities, it’s hot enough that it affects the local weather. Here’s a simplified diagram:

Figure 1. A simple sketch of typical increases in temperature due to the Urban Heat Island effect.

What I was curious about, however, was another kind of urban heat effect. This is the heat from all of the energy used within the city—electricity, fuel for transport, fuel for heating buildings, all of it. Eventually, almost all energy ends up as heat. So I went and got the energy usage for 27 huge “megacities”, along with the area of the city itself. I then combined the two to give me a measure of citywide energy usage in watts per square metre (W/m2). As a measure for comparison with Figure 2 below, a doubling of CO2 is said to increase the “forcing”, the total radiant energy impinging on the surface, by 3.7 W/m2.

Figure 2. Additional forcing from direct energy use. The energy data is paywalled. The link is to SciHub’s copy of the paper. It may have a “CAPTCHA” that asks you in Russian to type in a word to prove you’re actually a humanoid. Just type it in, it’s not Putin in disguise.

This was surprising to me. I hadn’t expected the effect to be so large.

Finally, I converted the forcing to an equivalent warming. The Intergovernmental Panel on Climate Change (IPCC) fifth assessment report, completed in 2014, gave a likely “Transient Climate Response” of about 1°C to 2.5°C for each additional 3.7 W/m2 of forcing. I’ve used 1.5°C because the heat generation persists over time. As a result, the cities have had time to equilibrate to the additional heating. Figure 3 shows that result.

Figure 3. Nominal warming from the additional forcing due to direct energy use. Colors indicate that I don’t like boring graphs.

Not much more to say about all of that. Note that this is a “first cut” analysis, I make no overarching claims about the accuracy of the results. I’ve used conservative assumptions and the best data I could find. It looks to be a significant additional heating source due to direct energy usage in the densest of the largest cities, one that is not generally included in the calculations of the Urban Heat Island.

Here, I’m in the Forest Cool Island, life is good. I spent my morning crawling around under my house successfully putting a new “generator” into my floor furnace so we now have a warm house again, a less than pleasant job that came complete with a veritable plethora of bad words. Then I got out the pumice stone and scrubbed a toilet bowl until it sparkled, and this has been my afternoon project … do I know how to have fun, or what?

My very best wishes to each of you,

w.

[UPDATE] In the comments below, someone asked about human body heat and how that affects the forcing in megacities. Humans on average put out on the order of 120 watts continuously. Here’s how that plays out.

Figure 4. Additional forcing from the heat emitted 24/7 by the human body.

You can see how densely populated Seoul, South Korea is …

DATA: I’ve appended the data below, in comma-delimited form. PJ is petajoules, 10^15 joules.

City, PJ, km2,Population Beijing, 952, 6562, 21516000 Buenos Aires, 702, 10888, 3054000 Cairo, 282, 1600, 10230000 Delhi, 316, 3182, 11034000 Dhaka, 350, 1353, 8906000 Guangzhou, 1474, 7711, 14043000 Istanbul, 464, 5500, 14025000 Jakarta, 589, 5100, 10075000 Karachi, 339, 1100, 14910000 Kolkata, 78, 1785, 4486000 Lagos, 350, 1535, 861000 London, 1065, 11391, 8825000 Los Angeles, 1848, 10780, 3884000 Manila, 918, 2521, 1780000 Mexico City, 1099, 7346, 9041000 Moscow, 1984, 14925, 12197000 Mumbai, 191, 2350, 12478000 New York, 2824, 17884, 8622000 Osaka, 1258, 6930, 2691000 Paris, 657, 17174, 2229000 Rio De Janeiro, 384, 4540, 6718000 Sao Paulo, 589, 8479, 12252000 Seoul, 1848, 5076, 10197000 Shanghai, 1644, 5177, 24256000 Shenzhen, 350, 3051, 8378000 Tehran, 1145, 9500, 8154000 Tokyo, 2438, 8014, 13839000

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