Waste heat: the dominating root cause of current global warming

Abstract

Background
Pursuing GHG reductions by means of all resources and efforts has turned out no result to stop or even slow the global warming: the globe still gets warmer and warmer, especially in the recent years, at record-breaking rate almost each single year. Additionally, no definitive relationship has been found between the warming and the atmospheric GHG concentration. The link between them even in IPCC’s report lacks support and is unconvincing. All these imply that something else is responsible for the warming. On the other hand, huge amount of residual heat or waste heat from human activities has been poured into the climate system but has not been considered seriously in the context of global warming or climate change.

Results
This article features deploying the basic principles of thermodynamics and applying a new model, Equivalent Climate Change Model, to analyse the currently available data on world energy consumption between 1965 and 2017, and to study the relation between the global warming and the waste heat entered the climate system. The results show that the temperature changes in air, oceans and land are definitively correlated to the respective heat allocated from the waste heat stream based on their specific heat capacities, with high certainty and reliability. The observed anomalies in air fall within a range of simulations at an equivalent climate change surface air boundary layer depth between 50 and 100 m (60 ~ 100 m in recent decades due to more establishments of high-rising heat discharging sources); the anomalies in oceans fall within a range of simulations at an equivalent climate change waters surface boundary layer depth between 0.10 and 0.20 m (0.125 ~ 0.20 m in recent decades); and the anomalies in land fall within a range of simulations at an equivalent climate change land surface boundary layer depth between 0.05 and 0.10 m (0.06 ~ 0.10 m in recent decades). The simulation results at the air layer depth of 70 m are almost the same as NASA’s Lowess smoothing trend. Forecast of future global warming based on this model under the scenario of business as usual indicates that the possible air temperature risings will be in the range of 0.68 ~ 1.13 °C in 2030 and 0.73 ~ 1.22 °C in 2040; the possible sea temperature risings will be in the range of 0.61 ~ 0.98 °C in 2030, 0.66 ~ 1.05 °C in 2040; and the possible land temperature risings will be in the range of 1.02 ~ 1.71 °C in 2030, 1.10 ~ 1.84 °C in 2040. However, if the energy conversion efficiency increased by 10% by 2030 and another 10% by 2040, then the possible air temperature risings would be in the range of 0.54 ~ 0.90 °C in 2030 and 0.44 ~ 0.73 °C in 2040; the possible sea temperature risings would be in the range of 0.49 ~ 0.78 °C in 2030, and 0.40 ~ 0.64 °C in 2040; and the possible land temperature risings would be in the range of 0.81 ~ 1.36 °C in 2030 and 0.66 ~ 1.11 °C in 2040. The observed global average air temperature changes and the Lowess Smoothing values in 2018 and 2019 fall within the range set by the air layer depth between 60 and 100 m, are consistent with the forecast under the scenario of business as usual, further confirms the reliability of this approach.

Conclusions
Greenhouse gases are not the culprit of the current global warming, instead, huge amount of residual heat or waste heat discharged into the environment from human activities has dominated the warming (beside of solar irradiance and volcano eruptions). Pursuing GHG reductions is bound to be ineffective in preventing the globe from further warming but increases unnecessary burdens. Switching to 100% of surface renewable energies is the ideal solution to completely solve further warming problem. However, geotherm does cause global warming although it is a type of renewable energy. Increasing energy’s conversion efficiency can effectively help slow down the warming, it requires vast investment and will embrace breakthroughs in technologies. Changing human’s behavior individually and socially and retrofitting can decrease the energy consumption and the amount of heat entering the environment and thus help mitigate climate change and its impact in the most cost-effective way. Unlike the General Circulation Models that can only simulate the past air temperature changes with greater uncertainty, the Equivalent Climate Change Model can not only trace the past temperature changes in air, oceans and land, but also can predict the future changes in them, respectively, with high certainty and reliability.

Full text

Bian Environ Syst Res (2020) 9:8
https://doi.org/10.1186/s40068-020-00169-2
RESEARCH
Waste heat: thedominating root cause
ofcurrent global warming
Qinghan Bian*
Abstract
Background: Pursuing GHG reductions by means of all resources and efforts has turned out no result to stop or even
slow the global warming: the globe still gets warmer and warmer, especially in the recent years, at record-breaking
rate almost each single year. Additionally, no definitive relationship has been found between the warming and the
atmospheric GHG concentration. The link between them even in IPCC’s report lacks support and is unconvincing. All
these imply that something else is responsible for the warming. On the other hand, huge amount of residual heat or
waste heat from human activities has been poured into the climate system but has not been considered seriously in
the context of global warming or climate change.
Results: This article features deploying the basic principles of thermodynamics and applying a new model, Equiva-
lent Climate Change Model, to analyse the currently available data on world energy consumption between 1965
and 2017, and to study the relation between the global warming and the waste heat entered the climate system.
The results show that the temperature changes in air, oceans and land are definitively correlated to the respective
heat allocated from the waste heat stream based on their specific heat capacities, with high certainty and reliability.
The observed anomalies in air fall within a range of simulations at an equivalent climate change surface air bound-
ary layer depth between 50 and 100 m (60 ~ 100 m in recent decades due to more establishments of high-rising
heat discharging sources); the anomalies in oceans fall within a range of simulations at an equivalent climate change
waters surface boundary layer depth between 0.10 and 0.20 m (0.125 ~ 0.20 m in recent decades); and the anomalies
in land fall within a range of simulations at an equivalent climate change land surface boundary layer depth between
0.05 and 0.10 m (0.06 ~ 0.10 m in recent decades). The simulation results at the air layer depth of 70 m are almost the
same as NASA’s Lowess smoothing trend. Forecast of future global warming based on this model under the scenario
of business as usual indicates that the possible air temperature risings will be in the range of 0.68 ~ 1.13 °C in 2030 and
0.73 ~ 1.22 °C in 2040; the possible sea temperature risings will be in the range of 0.61 ~ 0.98 °C in 2030, 0.66 ~ 1.05 °C
in 2040; and the possible land temperature risings will be in the range of 1.02 ~ 1.71 °C in 2030, 1.10 ~ 1.84 °C in 2040.
However, if the energy conversion efficiency increased by 10% by 2030 and another 10% by 2040, then the possible
air temperature risings would be in the range of 0.54 ~ 0.90 °C in 2030 and 0.44 ~ 0.73 °C in 2040; the possible sea
temperature risings would be in the range of 0.49 ~ 0.78 °C in 2030, and 0.40 ~ 0.64 °C in 2040; and the possible land
temperature risings would be in the range of 0.81 ~ 1.36 °C in 2030 and 0.66 ~ 1.11 °C in 2040. The observed global
average air temperature changes and the Lowess Smoothing values in 2018 and 2019 fall within the range set by the
air layer depth between 60 and 100 m, are consistent with the forecast under the scenario of business as usual, further
confirms the reliability of this approach.
Conclusions: Greenhouse gases are not the culprit of the current global warming, instead, huge amount of residual
heat or waste heat discharged into the environment from human activities has dominated the warming (beside
© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing,
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permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco
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Open Access
*Correspondence: bianqinghan@hotmail.com
Victoria, BC V8P 5B6, Canada
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Background
Greenhouse gases don’t cause thecurrent global warming/
climate change
Global warming drives climate change. It has been an
urgent, sustainability threatening issue. e globe gets
warmer and warmer, especially in recent years at record-
breaking rates year after year, and no slow-down sign
has been seen yet although huge efforts and resources
have been deployed. is basically indicates that the cur-
rent approach to fighting climate change through reduc-
ing greenhouse gas (GHG) emissions is ineffective and
inefficient.
ree things might have influenced the climate. ey
are tectonic changes, solar irradiance variance and
human activities. Regarding solar irradiance, it is believed
that its variance can only induce a temperature change
up to a level of 0.1°C during an 11-year solar cycle as
mentioned in (Bian 2019), though arguments exist. Con-
sequently, it is unlikely that the variance of solar activ-
ity has caused climate change to the currently observed
level.
It is reported that the comparison between prehistori-
cal global warming and atmospheric GHG (i.e. CO2 and
CH4) concentrations found their similarity in the change
trend, and thus it is concluded that GHGs caused the pre-
historical warming (Skeptical Science 2020) based on the
concept of Greenhouse Effect. It is worth to note that in
the far ancient time fierce tectonic changes and volcano
eruptions blew out vast amount of geotherm with asso-
ciated gases of CO2 and CH4. e geotherm broke the
earth’s energy budget balance (Bian 2019), warmed the
air and caused the warming, while the GHGs just coin-
cidently experienced the change. e concurrent partici-
pation of the geotherm and GHGs in the ancient climate
change may explain why the prehistoric climate change
has the similar trend to the then-atmospheric GHGs.
In modern time such fierce tectonic changes (except for
earthquakes) have not occurred, but volcano eruptions
do make contributions to the current climate change, to
some extent, as discussed in (Bian 2019).
It’s been widely perceived that Greenhouse Effect
dominates the current warming based on the presump-
tion that GHGs form a blanket over the earth. e blan-
ket traps the infrared radiations from the earth surface
from escaping into the space, and then reflects the radia-
tion back to the earth as heat, warming it up. However,
it’s very difficult to imagine how these spatially randomly
distributed trace gases (only about 0.04% of the air vol-
ume) can form a blanket in the atmosphere over the
earth, because 99.96% of the air volume is occupied by
other molecules, leaving almost all the atmosphere “free
of GHGs”, forming an open gateway for the radiations
to travel to the space. erefore, GHG’s effect has been
exaggerated.
Additionally, do GHGs really have so strong forcing
and heat-trapping capacities in such low level of concen-
trations? If so, then it would be very possible to develop
new energy storage sources by using their concentrates to
trap/absorb heat, since commercial natural gas and dry
ice are readily available, and even collecting them from
emission sources is not difficult, but it is not the case yet.
Unlike specific heat capacity—an attribute of a material,
the forcing and global warming potentials of GHGs are
just given indices calculated based on the warming level
and the gas’ concentrations, not the material’s intrinsic
properties.
On the other hand, no definitive relation has been
found between the current global warming and the GHG
concentration though large number of climate change
models have been developed. is can be seen from
IPCC’s assembly of many simulations from selected mod-
els. eir mean of these simulations is used to compare
with the observed temperature anomalies, but big gaps
still exist (Fig.1) (Flato 2013). erefore, claiming GHGs
have caused the current global warming and climate
change lacks solid support and is unconvincing, because,
of solar irradiance and volcano eruptions). Pursuing GHG reductions is bound to be ineffective in preventing the
globe from further warming but increases unnecessary burdens. Switching to 100% of surface renewable energies
is the ideal solution to completely solve further warming problem. However, geotherm does cause global warming
although it is a type of renewable energy. Increasing energy’s conversion efficiency can effectively help slow down
the warming, it requires vast investment and will embrace breakthroughs in technologies. Changing human’s behav-
ior individually and socially and retrofitting can decrease the energy consumption and the amount of heat entering
the environment and thus help mitigate climate change and its impact in the most cost-effective way. Unlike the
General Circulation Models that can only simulate the past air temperature changes with greater uncertainty, the
Equivalent Climate Change Model can not only trace the past temperature changes in air, oceans and land, but also
can predict the future changes in them, respectively, with high certainty and reliability.
Keywords: Climate change, Equivalent climate change model, Energy conversion efficiency, Forecast, Global
warming, Residual heat, Waste heat
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Bian Environ Syst Res (2020) 9:8
as well known, a definitive relation must exist between
any two correlated things. is may be the reason why
IPCC cautiously declares “climate change is real and
human activities are the main cause” (United Nations
et al. 2020), without explicitly linking the warming to
GHGs. Unfortunately, almost all the efforts and resources
have been focused on GHG emissions and their reduc-
tions worldwide so far, while the energy flow and the
associated waste heat from human activities have been
overlooked. Furthermore, by the current GHG-based
theory, it is neither possible to track the past temperature
changes nor to predict the future temperature changes in
the surfaces of both oceans and land.
Global warming is a thermodynamic problem, it starts
from the ground level. Studies should focus on the phe-
nomena in the surface level of air, oceans and land since
they regulate and dominate concurrently the ground
level temperature that suits for human’s living. e tem-
perature changes in surface air, oceans surface and land
surface are “coordinated” by these components through
allocating heat entered the climate system based on their
specific heat capacities (Bian 2019).
Fig. 1 Observed and simulated time series of the anomalies in annual and global mean surface temperature. All anomalies are differences from the
1961–1990 time-mean of each individual time series. a Single simulations for CMIP5 models (thin lines); b Single simulations from available EMIC
simulations (thin lines), from Eby et al. (2013); multi-model mean (thick red line); different observations (thick black lines) (Fig. 9.8 in the original
source) (Flato 2013)
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Bian Environ Syst Res (2020) 9:8
Waste heat—huge amount entering theenvironment
According to the Law of Conservation of Energy, energy
cannot disappear nor be destroyed after use, it can only
be converted from one form to another. Beside of the
energy converted to useful work or chemical energy
stored in new products, there is also residual heat or
waste heat from energy application processes that has
been discharged into the climate system, for example
(Bian 2019):
• In our daily life, taking showers, drying laundry
(except for sun dry) directly pour heat into the envi-
ronment, while air conditioning directly heats the air;
• In transportation, only about 12 ~ 41% of the fuel
consumed is used to do the “useful work”, while all
the rest is discharged into the environment in the
form of heat;
• In industries, drying moisture-containing materi-
als discharges all consumed energy directly into the
environment in the form of heat along with the evap-
orated water and the hot materials;
• During lime production with a typical rotary kiln
process, about 43.4% of the input energy is dispersed
into the environment as heat. For other types of kilns,
the waste heat may be more;
• In cement production, about 55.5 ~ 68.6% of the
input energy is lost in the form of heat, through
exhaust gas, kiln shell, hot product etc.;
• As for electricity generation, only about 38% of the
primary energy is converted to electricity in a mod-
ern plant, with the rest wasted to the environment in
the form of heat.
In general, about 100% of energy consumed in residen-
tial and commercial, 75% in transportation and 70% in
industrial applications are discharged into the environ-
ment as heat globally (Bian 2019).
Additionally, there is countless flaring at oil and gas
development/processing sites, petroleum refineries and
petrochemical plants, coal mining and processing facili-
ties, waste management and landfill locations etc., which
heats the air and sends heat to the environment continu-
ously (24/7/365) worldwide.
It is further estimated that the current global energy’s
total effective conversion efficiency (GETECE, or sim-
ply energy conversion efficiency) is only about 20%, i.e.
merely about 20% of the consumed global energy is con-
verted to new products and useful work, while the rest
80% enters the climate system as residual heat or waste
heat, breaks the earth’s energy budget balance (Bian
2019). It is this huge amount of heat that has caused
and is continuing to cause the global warming (Bian
2019). Among the 80%, industry contributes about 44%,
residential and commercial 36% and transportation 20%.
erefore, personal contribution is not small globally and
cannot be ignored. Furthermore, this heat, after entering
the environment (i.e. land–ocean-air climate system), is
redistributed among the air, land and oceans based on
their specific heat capacities (Bian 2019).
Some studies have discussed the effect of waste heat
(Flanner 2009), or anthropogenic thermal emission
(Murray and Heggie 2016). Flanner (2009) indicated that
almost all energy used for human purposes is dissipated
as heat within Earth’s land–atmosphere system, while the
heat from non-renewable sources constitutes a climate
forcing term, with a global average value of 0.028 W/
m2. e latter is compared to GHG’s forcing of 2.9 W/
m2 (IPCC Fourth Assessment Report: Climate 2007) and,
thus it is concluded that waste heat from human activities
is only about 1% of the GHGs’ effect (Skeptical Science
2020). However, estimating waste heat’s forcing at the
top of the atmosphere itself neglects its absorption by air,
exaggerated its effect, if that is appropriate. On the other
hand, about 30% of industrial energy converted to new
products in the form of chemical energy and 25% of fuel
converted to useful work in transportation (Bian 2019)
undercut Flanner’s claim. us, Flanner’s insistence of
“almost all energy… is dissipated as heat within Earth’s
land–atmosphere system” seems to be overestimated and
inaccurate. Flanner (Flanner 2009) pioneeringly tried to
incorporate waste heat into GHG-based climate change
modelling, but did not examine how the heat directly
warmed the air from the perspective of thermodynamics.
Murray and Heggie (2016) compared anthropogenic
thermal emission and temperature changes at national level
for Japan and Great Britain, found that the energy con-
sumption (serving as the proxy of thermal emission) and
the temperature above background change have strong cor-
relation, in contrast with the weaker correlation by CMIP5
model. Although being very interesting, Murray and Heg-
gie(2016) obviously overestimated the thermal output and
thus provided less accuracy; did not explore further how
the thermal emission affected the temperature change. In
addition, because of only considering two countries, the
results is less representative in the context of a global scale.
Nevertheless, all these suggest that waste heat or resid-
ual heat from human activities contribute to the global
warming and climate change, but how much its contribu-
tion is and what is the exact relation between them need
to be investigated on a global scale.
Method
Studying global warming and climate change must look
at the temperature changes in air, sea and land at the
same time. is project features the simultaneous inves-
tigation of temperature changes in surface air, sea surface
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Bian Environ Syst Res (2020) 9:8
and land surface on global scale by thermodynamics,
through allocating the waste heat stream to these three
components (i.e. air, oceans and land) according to their
specific heat capacities, and by using a new global model,
i.e. Equivalent Climate Change Model (Bian 2019). e
model consists of an equivalent climate change surface
air boundary layer, an equivalent climate change waters
surface boundary layer and an equivalent climate change
land surface boundary layer. By following the proce-
dures described in (Bian 2019), currently available data
on world energy consumption is used to determine heat
energy entered the climate system in order to simulate
the past (global average) temperature changes in these
components, and their future temperature changes are
also forecast based on predicted energy consumption.
It is assumed that part of the waste heat has been con-
sumed to melt ice and raise its temperature to sea water’s
temperature before raising the temperatures in air,
oceans and land, as shown below (Bian 2019):
e temperature changes in air, oceans and land are the
unique functions of the respective heat entered them (Bian
2019). e relations between temperature changes and the
heat “input” are clear and determinative as shown below:
e relationship between surface air temperature
changes and the allocated waste heat,
e relationship between sea surface temperature
changes and the allocated waste heat,
e relationship between land surface temperature
changes and the allocated waste heat,
Where,
R0 Earth’s radius, 6371km
h e depth (or altitude) of the air layer measured
from the earth surface
Sw Seawater surface area, 361,800,000km2
Dw e depth of the sea waters’ layer
ρa Air density under normal pressure
Cpa Air specific heat capacity under constant pres-
sure, or the isobaric heat capacity
(1)
�Hiw
=
Qi
·
Lpi
+
Qi
·
Cpw
·
(Tsw
−
Tiw)
(2)
�
ta=
3�H
a
4π

(Ro+h)3−R3
o

·ρa·C
pa
(3)
�
tw=
�H
w
S
w
·D
w
·ρ
w
·C
pw
(4)
�
tL=
�H
L
S
L
·D
L
·ρ
L
·C
pL
∆Ha e heat entered air layer that incurs the temper-
ature change ∆ta
∆ta e temperature change in the air layer after
experiencing heat change ∆Ha
ρw e waters’, mainly seawaters’ density
∆Hw e heat entered seawaters layer that incurs the
temperature change ∆tw
∆tw e temperature change in the seawaters layer
after experiencing heat change ∆Hw
Cpw Seawaters specific heat capacity under normal
pressure
ρL e land (soil) density
∆HL e heat entered land layer that incurs the tem-
perature change ∆tL
∆tL e temperature change in the land layer after
experiencing heat change ∆HL
CpL Land (soil) specific heat capacity under normal
pressure
SL Land area on the earth surface, 148,264,472km2
based on the Earth’s total surface area
(510,064,472km2) and the total oceans’ surface
area (361,800,000km2)
DL Depth of land layer
e simulation results calculated at different boundary
layer depths are compared to those observed tempera-
ture anomalies, and future predictions are conducted too.
Results anddiscussions
Past simulations
It is revealed that (Bian 2019) an equivalent climate
change surface air boundary layer with a depth between
50 and 100m (also referred to as the depth’s lower and
upper layer limits), an equivalent climate change waters
surface boundary layer with a depth between 0.1 and
0.2 m, and an equivalent climate change land surface
boundary layer with a depth between 0.05 and 0.1m can
well characterize their respective temperature changes
due to the heat entered air (Fig.2), oceans and land from
human activities. e simulations at these depths are well
consistent with the observed temperature anomalies in
these three components (Bian 2019). ese depths are
referred to as equivalent climate change boundary layers’
depths.
Additionally, in recent decades the lower limit of air
boundary layer depth of 50 m may have overestimated
the warming due to more establishments of high-rising
heat discharging sources, while an extended lower-depth
of 60 m produces more reasonable results. Even so, a
70-m depth of the air layer is still representative for the
simulations and its results are almost the same as the
NASA’s Lowess Smoothing trend as the small insert in
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Bian Environ Syst Res (2020) 9:8
Fig.2 shows (note that NASA’s Lowess Smoothing data-
set in Bian (2019) was taken from NASA’s website in
later 2018, while the dataset used here was taken from
NASA’s website in April 2020), which is the most match-
ing results to NASA’s values through a single simulation
found so far among various simulations, providing the
evidence that waste heat influences the air temperature.
e similar trends are also seen in the oceans and land
boundary layers. As augmented amount of heat flux
entered them, the minimal heat transfer distances, i.e. the
lower limits of depths of the oceans and land boundary
layers shifted to 0.125m from 0.10m, and 0.06m from
0.05m in recent decades, respectively.
Compared to those approaches using General Cir-
culation Models (GCMs) and atmospheric GHG con-
centration as summarized in Fig.1 (Flato 2013) above,
by which their individual simulation results of past
air temperature changes cannot match the observed
anomalies, and by which past temperature changes in
oceans and land cannot be simulated, this newly pro-
posed modelling described here and in Bian (2019),
based on the allocated waste heat flux, can not only
match the air temperature anomalies (Figs.2, 3, 4) but
Fig. 2 Simulation of global surface air temperature changes in an air boundary layer at different depths between 1965 and 2017, and NASA, NOAA’s
surface air temperature anomalies (SAT), NASA’s Lowess Smoothing trend
(See figure on next page.)
Fig. 3 Calculated past temperature changes at the lower and upper depth limits of equivalent climate change surface air boundary layer (top),
equivalent climate change waters surface boundary layer (middle), and equivalent climate change land surface boundary layer (bottom), and the
temperature change forecast as well as their observed temperature anomalies under scenario SF1
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Bian Environ Syst Res (2020) 9:8
also match those in land and oceans (Figs. 3, 4), all
with high certainty and reliability.
All these clearly suggest that the current global
warming is a direct result of the huge amount of waste
heat discharged into the climate system from human
activities, implying that the residual heat or waste heat
is the main contributor to the current global warming
or climate change.
Future warming forecast
Figures3, 4 show the future temperature forecasts in air,
oceans and land by following the procedures described in
(Bian 2019) according to BP’s prediction of global energy
consumption in 2030 and 2040 (BP Energy Outlook
2019), where the simulated past temperature changes
at the lower and upper depth limits of the respective
boundary layers are also exhibited together with the
observed temperature anomalies. It is assumed that, as
for the simulation of past temperature changes, ice melt-
ing remains at the current rate constantly for the calcu-
lations. e results suggest that using this model and
the appropriate boundary layer depths can estimate the
ranges of future global temperature changes with high
certainty and reliability, while the temperature changes
calculated at the depths of 70m for air, 0.15m for oceans
and 0.075m for land are considered representative of the
future warmings.
Future temperature changes in 2030 and 2040 are pre-
dicted under two different scenarios: (1) business as usual
(SF1, Fig.3) and (2) elevated GETECEs, i.e. the energy
conversion efficiency increased by 10% at 2030 and 2040,
respectively (SF2, Fig.4).
Under scenario SF1, the forecast of future warming will
be in the following ranges (°C): in 2030 air 0.68 ~ 1.13,
oceans 0.61 ~ 0.98 and land 1.02 ~ 1.71; in 2040 air
0.73 ~ 1.22, oceans 0.66 ~ 1.05 and land 1.10 ~ 1.84 at
the layer depth between 60 and 100m for air, 0.125 and
0.2m for oceans, and 0.06 and 0.1m for land, as shown
in Fig.3, where their representative temperature change
forecast are also indicated.
It is important to note that the respective global aver-
age air temperatures, 0.85 and 0.98°C in 2018 and 2019,
and their respective Lowess Smoothing values, 0.95 and
0.98°C (National Aeronautics and Space Administration
2020), fall within the forecast range set by the air layer
depth between 60 and 100m under the business as usual
scenario as can be seen in Fig. 3. is further confirms
that this approach is reliable, and the forecast is consist-
ent with the expectation under the scenario of business
as usual.
Under the scenario SF2, the corresponding tempera-
ture changes would be in the following ranges (°C): in
2030 air 0.54 ~ 0.90, oceans 0.49 ~ 0.78 and land 0.81 ~ 1.
36; in 2040 air 0.44 ~ 0.73, oceans 0.40 ~ 0.64 and land
0.66 ~ 1.11 at the layer depth between 60 and 100m for
air, 0.125 and 0.2m for oceans, and 0.06 and 0.1m for
land, as shown in Fig.4, where their representative tem-
perature change forecast are also indicated.
e existing approaches for studying climate change
have great uncertainty, therefore, four Representa-
tive Concentration Pathways (RCPs) were proposed.
Compared to those forecasts under various scenarios,
for example, the global mean surface (air) temperature
change for the period 2016 ~ 2035 relative to 1986 ~ 2005
will likely be in the range of 0.3 ~ 0.7 °C (medium con-
fidence, similar for the four RCPs), for the period
2046 ~ 2065 in the range of 0.4 ~ 2.6°C for the four RCPs
(IPCC 2014), the forecasts by this study under the sce-
nario of business as usual are very reasonable and of
greater confidence and certainty, plus the trend is unique
and only relies on the projected global energy consump-
tion and dissipated waste heat.
Conclusion andstrategies
We need to realize the reality that huge amount of resid-
ual/waste heat from human activities has entered and
continues to enter the climate system that incurs the cur-
rent global warming. e amount of waste heat is about
80% of the consumed global energy, among which indus-
try contributes about 44%, commercial and residential
about 36% and transportation 20%. Everyone contributes
to it unconsciously and unwillingly. GHGs are not culpa-
ble for the current global warming.
By means of the Equivalent Climate Change Model and
allocating the waste heat stream to the climate system’s
three components i.e. air, land and oceans based on their
specific heat capacity, it is possible to simulate their past
temperature changes and predict future warmings with
high certainty and reliability. e temperature changes
in surface air layer with a depth between 50 (recently 60)
and 100 m are consistent with the observed global air
temperature anomalies; temperature changes in sea sur-
face layer with a depth between 0.10 (recently 0.125) and
0.20m are consistent with the observed sea temperature
Fig. 4 Calculated past temperature changes at the lower and upper depth limits of equivalent climate change surface air boundary layer (top),
equivalent climate change waters surface boundary layer (middle), and equivalent climate change land surface boundary layer (bottom), and the
temperature change forecast as well as their observed temperature anomalies under scenario SF2
(See figure on next page.)
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Bian Environ Syst Res (2020) 9:8
anomalies and the temperature changes in land sur-
face layer with a depth between 0.05 (recently 0.06) and
0.10m are consistent with the land temperature anoma-
lies. e air temperature changes at the air layer depth of
70m are almost the same as NASA’s Lowess Smoothing
trend.
Knowing the dominating root cause can provide the
right path and meaningful approaches for the battle.
Efforts in merely pursuing GHG reductions are bound
to be ineffective and inefficient but increase burdens. We
can no longer afford to waste any precious time, efforts
and resources, and must properly adjust our strategies
and policies effectively. International scientific commu-
nities should pay more attentions on the residual heat
or waste heat and investigate further how it impacts the
local and global climate patterns etc., and policymakers
should consider how to switch the efforts and resources
from focusing on GHG reduction to waste heat reduction
efficiently by developing effective policies.
Besides, ice interacts with the air, oceans and land and
ice melting influences the global warming by absorb-
ing vast amount of heat. However, assuming a constant
melting rate during a long term is evidently inappropri-
ate (especially at early time), it affects the accurate simu-
lation of past temperature changes. erefore, collecting
ice melting data in details such as the melt quantity, the
temperature at which the ice existed/exists, is of signifi-
cance to better understand the global warming and cli-
mate change.
It is forecast that under the business as usual scenario,
possible warmings in air will be 0.68 ~ 1.13 °C in 2030,
0.73 ~ 1.22°C in 2040; in oceans 0.61 ~ 0.98 °C in 2030,
0.66 ~ 1.05°C in 2040; in land 1.02 ~ 1.71°C in 2030 and
1.10 ~ 1.84°C in 2040, respectively.
Improving energy’s conversion efficiency would sub-
stantially suppress the warming. Under the elevated
energy conversion efficiency scenario, the possible warm-
ings in air would be 0.54 ~ 0.90°C in 2030, 0.44 ~ 0.73°C
in 2040; in oceans 0.49 ~ 0.78°C in 2030, 0.40 ~ 0.64°C in
2040; in land 0.81 ~ 1.36°C in 2030, 0.66 ~ 1.11°C in 2040,
respectively.
In order to effectively slow down or stop the fur-
ther warming, here are three strategic approaches
recommended:
1. Developing surface renewable energies such as solar,
wind, hydro and ocean energies will be most effec-
tive; switching to 100% of surface renewable energies
is the most ideal solution and can completely stop
further warming (because they are within the earth’s
energy budget balance); Prudentially planned use of
biomass is advisable (concentratedly burning mas-
sive biomass in a short time may break the in-situ
energy budget balance); Pursuing low carbon fuel is
helpful to some extent (due to blending partly bio-
mass); Using geotherm, a kind of renewable energy,
will accelerate the global warming from the perspec-
tive of energy budget balance. All these will certainly
promote the advancements and applications of new
technologies in these surface renewable energies.
2. Reducing energy consumption and saving energy will
directly reduce the heat amount entering the envi-
ronment through retrofit (of existing technologies
and processes) and individual and social behavior
changes. is is the easiest, most cost-effective and
practical solution. Eliminating flaring will contrib-
ute greatly to mitigating the current climate change,
helping conserve resources. Education plays a very
important role in this aspect.
3. Increasing the global energy’s total effective conver-
sion efficiency or simply the energy conversion effi-
ciency will efficiently mitigate the warming and cli-
mate change. is is the most important but difficult
task and will largest challenge the technology and
industrial sectors and need great deal of investments
too. It may embrace new technology breakthroughs
and great changes in production processes.
It is anticipated that after implementing these strate-
gies both in technologies and processes, human’s lifestyle
will be dramatically changed. Energy applications will
be more efficient and cleaner. Human’s reliance on fos-
sil fuels will shift onto surface renewable energies, while
traditional resources development and applications will
be limited.
Abbreviations
GHG: Greenhouse gas; Lowess Smoothing: Locally weighted scatterplot
smoothing; ECCM: Equivalent climate change model; ECCSABL-x: Equivalent
climate change surface air boundary layer at depth of x meters, x = 50, 60, 70,
100, … meters; ECCWSBL-x: Equivalent climate change waters surface bound-
ary layer at depth of x meters, x = 0.1, 0.125, 0.15, 0.2 … meters; ECCLSBL-x:
Equivalent climate change land surface boundary layer at depth of x meters,
x = 0.05, 0.06, 0.075, 0.10 …meters; GETECE: Global energy’s total effective
conversion efficiency; SF1: Business as usual scenario regarding to the GEECE,
i.e. GEECE = 20%; SF2: Elevated energy conversion efficiency scenario, i.e.
GEECE increased by 10% by 2030 and increased another 10% by 2040; NASA-
LST: NASA’s land surface temperature anomalies; NASA-SAT: NASA’s surface air
temperature anomalies; NASA-SST: NASA’s sea surface temperature anomalies.
Acknowledgements
The author is grateful to his family for their unconditional support for this
research project conducted independently at home at his spare time.
Authors’ contributions
The author is responsible for all aspects of composing the paper. All authors
read and approved the final manuscript.
Funding
Not applicable.
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Page 11 of 11
Bian Environ Syst Res (2020) 9:8
Availability of data and materials
The data used to analyse and support this paper is available.
Ethics approval and consent to participate
Not applicable.
Consent for publication
This is an independent personal research project conducted at home at the
author’s spare time, the author is willing to publish it to share with the interna-
tional scientific communities and the policymakers.
Competing interests
As mentioned above, it’s a personal independent research, no any external
funding. Thus, there is no any conflicts with any body, any organizations or
institutions.
Received: 12 March 2020 Accepted: 30 April 2020
References
Bian Q (2019) The nature of climate change-equivalent climate change
model’s application in decoding the root cause of global warming. Inter
J Env Climate Change. 9(12):801–822. https ://doi.org/10.9734/ijecc /2019/
v9i12 30160
BP. P.l.c. BP Energy Outlook, 2019 Edition, 2019. https ://www.bp.com/en/globa
l/corpo rate/energ y-econo mics/energ y-outlo ok/energ y-outlo ok-downl
oads.html
Flanner MG (2009) Integrating anthropogenic heat flux with global climate
models. Geophys Res Lett 36:L02801. https ://doi.org/10.1029/2008G
L0364 65
Flato G, Marotzke J, Abiodun B, Braconnot P, Chou SC, Collins W, Cox P,
Driouech F, Emori S, Eyring V, Forest C, Gleckler E, Guilyardi C, Jakob V
Kattsov C. Reason and M. Rummukainen, 2013: Evaluation of Climate
Models. In: Climate Change 2013: The Physical Science Basis (Figure 9.8).
Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change [Stocker TF, D Qin, G-K.
Plattner, M Tignor, SK. Allen, J Boschung, A Nauels, Y Xia, V Bex and PM
Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom
and New York
IPCC, 2014: Climate change 2014: Synthesis Report. Contribution of Working
Groups I, II and III to the Fifth Assessment Report of the Intergovernmen-
tal Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A.
Meyer (eds.)]. IPCC, Geneva, Switzerland, pp 151 https ://epic.awi.de/id/
eprin t/37530 /1/IPCC_AR5_SYR_Final .pdf
IPCC fourth assessment report: climate change 2007, working group I: the
physical science basis, executive summary, https ://archi ve.ipcc.ch/publi
catio ns_and_data/ar4/wg1/en/ch2s2 -es.html
Murray J, Heggie D (2016) From urban to national heat island: the effect of
anthropogenic heat output on climate change in high population indus-
trial countries. Earth Future. https ://doi.org/10.1002/2016E F0003 52
National Aeronautics and Space Administration, GISS Surface Temperature
Analysis (v4), https ://data.giss.nasa.gov/giste mp/graph s_v4/, Accessed
11 April 2020
Skeptical Science, It’s Waste Heat. https ://skept icals cienc e.net/pdf/rebut tal/
waste -heat-globa l-warmi ng-inter media te.pdf, Accessed 6 April 2020
United Nations, Climate Change, https ://www.un.org/en/secti ons/issue
s-depth /clima te-chang e/ Accessed 4 Feb 2020
Skeptical Science, What does past climate change tell us about global warm-
ing?. https ://skept icals cienc e.com/clima te-chang e-littl e-ice-age-medie
val-warm-perio d-inter media te.htm. Accessed 7 Feb 2020
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