Anthropogenic Heating of the Atmosphere
Technical notes
The heat release from global commercial energy is about 400 EJ a year. If we divide this figure by number of seconds in a year (3.1536 * 107) and by the land area of the Earth (1.3 * 1014 m2), we obtain approximately 100 mWm-2. This is an average value. The heat release in urban areas can be much higher. For instance, the anthropogenic heat release in central Tokyo exceeds 400Wm-2 in daytime with maximum value of about 1600 Wm-2, the typical values being around 200 Wm-2.[1]
The heat release from global commercial energy is about 400 EJ a year. If we divide this figure by number of seconds in a year (3.1536 * 107) and by the land area of the Earth (1.3 * 1014 m2), we obtain approximately 100 mWm-2. This is an average value. The heat release in urban areas can be much higher. For instance, the anthropogenic heat release in central Tokyo exceeds 400Wm-2 in daytime with maximum value of about 1600 Wm-2, the typical values being around 200 Wm-2.[1]
The anthropogenic heat release consists
of the following components: heat release from commercial and non-commercial
energy and heat release from human metabolism. The commercial and non-commercial
energy figures were taken from Renewables Information
Database of IEA.[2] To estimate heat from human metabolism,
it was assumed that a human body releases on average approximately 100
W.
Commercial energy use is concentrated in urban areas, while
use of non-commercial energy takes place in mainly rural areas. Industrialized
countries have very low or zero use of non-commercial energy. Heat release
from human metabolism is expected to be the highest in the areas with
the highest population densities.
The radiance calibrated nighttime lights map of DMSP [3] was used as a proxy to allocate heat from commercial energy. The map is a global grid set with a cell size of 30 x 30 arc seconds, or approximately 1 x 1 km. It was derived from nighttime lights images of the period from March 1996 to January-February 1997. Each grid cell contains a value between 0 and 255; the values between 0 and 254 represent non-sauturated lights and can be converted to radiance values, and the value 255 indicates that there were no non-saturated light found at the location.
The grid was resampled to a lower resolution grid (2.5 x 2.5 arc minutes, or 4.6 x 4.6 km at the equator), to make it consistent with the gridded population data set [5].
The radiance values were calculated according to the formula
Radiance = [Cell Value]3/2 * 10-10 Wcm-2sr-1
provided in [3]. The resulting values are relatively small and do not exceed 0.004 Wm-2sr-1, which is much less than estimated average heat release from commercial energy, therefore they cannot be used directly.
Thee values were then multiplied by physical areas of the cells (from 5 to 22 km2, depending on the latitude) in order to get sums of radiance values in each grid cell. Finally, sums of radiance values were calculated for each country. The sums were compared with commercial energy data of the countries in 1996. As seen from the Figure 1, the sums of radiance values highly correlate with commercial energy figures.
The radiance calibrated nighttime lights map of DMSP [3] was used as a proxy to allocate heat from commercial energy. The map is a global grid set with a cell size of 30 x 30 arc seconds, or approximately 1 x 1 km. It was derived from nighttime lights images of the period from March 1996 to January-February 1997. Each grid cell contains a value between 0 and 255; the values between 0 and 254 represent non-sauturated lights and can be converted to radiance values, and the value 255 indicates that there were no non-saturated light found at the location.
The grid was resampled to a lower resolution grid (2.5 x 2.5 arc minutes, or 4.6 x 4.6 km at the equator), to make it consistent with the gridded population data set [5].
The radiance values were calculated according to the formula
Radiance = [Cell Value]3/2 * 10-10 Wcm-2sr-1
provided in [3]. The resulting values are relatively small and do not exceed 0.004 Wm-2sr-1, which is much less than estimated average heat release from commercial energy, therefore they cannot be used directly.
Thee values were then multiplied by physical areas of the cells (from 5 to 22 km2, depending on the latitude) in order to get sums of radiance values in each grid cell. Finally, sums of radiance values were calculated for each country. The sums were compared with commercial energy data of the countries in 1996. As seen from the Figure 1, the sums of radiance values highly correlate with commercial energy figures.
Figure 1. Commercial Energy vs Nighttime Lights
(click for the larger image)
A map of commercial energy heat release
is shown in the Figure 2. One can see "heat islands" in the USA, Europe,
Japan, South Korea, China and India. The highest estimated values are
observed for Shanghai, of 160.2 Wm-2 [see the table]. The estimated heat release in
Tokyo is 94
Wm-2, which is lower than the figures
given in [1]. One should note, however, that in the current
study larger grid cells were used, i.e. 4.6 x 4.6 km versus 0.025 x 0.025
km used in [1]. Therefore, the estimated value is an average
one within an area of approximately 20 km2; the smaller the size
of a grid cell, the higher can be the values. The values of commercial energy
heat observed in urban agglomerations are normally between 20 and 70 Wm-2; again,
these are average values of a grid cell, the actual values can be much higher.
Figure 2. Commercial Energy, W/m2, 1996
Derived from IEA energy data and nighttime lights data
Larger scale
maps:
North America | USA | Latin America | Europe | Africa | Europe, North Africa and Middle East
Asia | Far East | South Asia and Australasia | South and South-East Asia
North America | USA | Latin America | Europe | Africa | Europe, North Africa and Middle East
Asia | Far East | South Asia and Australasia | South and South-East Asia
The map of the gridded population
of the world [5] was used to allocate heat from non-commercial
energy and from human metabolism.
Since the use of non-commercial energy takes place mainly in rural areas, the population map was combined with the human settlements map of DMSP [4], in order to exclude urban areas. The heat from non-commercial was then allocated to the rural areas from the resulting grid.
The map of the heat from human metabolism was simply derived from the gridded population map by the formula:
Heat=[cell value]*100 W/[cell size, m2]
The map of total anthropogenic heat is shown on the Figure 3. The map does not differ much from the previous map, however, one can see the larger number of "heat islands" in Asia, especially in India, which is because of high population density.
Since the use of non-commercial energy takes place mainly in rural areas, the population map was combined with the human settlements map of DMSP [4], in order to exclude urban areas. The heat from non-commercial was then allocated to the rural areas from the resulting grid.
The map of the heat from human metabolism was simply derived from the gridded population map by the formula:
Heat=[cell value]*100 W/[cell size, m2]
The estimated values both of the
heat from non-commercial energy and the heat from human metabolism
do not exceed few watts per square meter. The typical values are few
dozens of milliwatts.
The map of total anthropogenic heat is shown on the Figure 3. The map does not differ much from the previous map, however, one can see the larger number of "heat islands" in Asia, especially in India, which is because of high population density.
Figure 3. Total heat , W/m2, 1996
(commercial energy + combustial renewables and waste + heat from human metabolism)
Derived from IEA energy data, gridded population of the world and nighttime lights data
Larger scale maps:
North America | USA | Latin America | Europe | Africa | Europe, North Africa and Middle East
Asia | Far East | South Asia and Australasia | South and South-East Asia
Additional data: Maximum values of waste heat in the cities over 750,000
inhabitant
Atmospheric Environment, 33, 1999, pp 3897-3909
2. Renewables Information Database from IEA
3. Radiance Calibrates Nighttime Lights: 1996 - 1997 by DMSP
4. Nighttime lights of the World - change pair. Human settlements by DMSP
5. Gridded Population of the World [v2] by SEDAC
Reference and Data sources:
1. Toshiaki Ichinose, Kazuhiro Shimodozono, Keisuke Hanaki, Impact of anthropogenic heat on urban climate in Tokyo,Atmospheric Environment, 33, 1999, pp 3897-3909
2. Renewables Information Database from IEA
3. Radiance Calibrates Nighttime Lights: 1996 - 1997 by DMSP
4. Nighttime lights of the World - change pair. Human settlements by DMSP
5. Gridded Population of the World [v2] by SEDAC
Vadim Chirkov chirkov@iiasa.ac.at
TNT, IIASA
Laxenburg 2361, Austria
last updated:17 October, 2003