While the previous discussion is retrospective, here I consider the future possibility of internalizing
emissions into expenditures on energy (see
Figure 3). In this section I describe the following rationale. The longer the world waits to reduce annual GHG emissions, the faster the required rate of reductions to stay below a total carbon budget. The faster the reduction in emissions, the higher the rate of investment required to convert to the low-carbon energy system. The larger the investment in the energy system, the more resources are allocated to it, and the higher the
(assuming the energy sector does not go significantly into debt). Consequently, the higher the
, the higher the probability of (at least short term) economic recession during the transition.
Figure 3.
Top: Estimated expenditures on energy (
) as a fraction of GDP (for the 44 countries in the data set) from 1978 to 2010 including hypothetical costs on
emissions of 10, 50, and 100 $2005/t
. The data for annual
emissions from fossil energy (oil, natural gas, and coal) are from the IEA website [
62] Bottom: The
cost that would cause expenditures for both energy and
combined to equal a constant fraction of GDP each year.
4.2.1. The Energy Trap
Because the majority of global primary energy still comes from fossil fuels and approximately 57 t
are emitted per TJ of primary energy [
62,
65], a rapid reduction in emissions rates translates to a rapid reduction in fossil energy consumption rates and/or substantial investment in
capture and storage systems. Further, it takes energy to manufacture and install renewable energy and low-carbon energy systems. The lower the energy return ratio of low-carbon technologies and the faster the low-carbon/renewable energy transition, the higher the increase in short-term energy consumption,
emissions, and costs that are associated with that transition [
66,
67].
Equations (
1)–(
3) demonstrate why lower net energy systems make an energy transition more difficult [
67]. In these equations, NEER is net external energy ratio equal to energy return on energy invested (EROI) (see King
et al. [
1] for terminology details), and
α is the expansion growth rate of a technology assuming some of the net energy from the energy technology is used to build and install more of that technology. EPBT is the energy payback time, or the time required for the energy technology to generate a quantity of energy equal to the energy required to install the technology (assuming no decomissioning). The other symbols, taken from Kessides and Wade [
67] describing power plants, are as follows:
is the energy required for capital manufacturing and installation,
is nameplate power capacity,
ϕ is capacity factor,
h is the fraction of gross energy production needed to operate and maintain the technology,
T is the lifetime of the technology,
is the construction time to install the technology, and
β is the chosen fraction of produced energy that is used to construct new power plants.
β is an economic decision variable, and if
then all energy from the technology is used to build more of itself.
Imagine a current energy system that is retiring one unit of capacity per year, and that we are used to replacing it with a technology
;
;
,
;
;
and
that has EROI = NEER = 20, EPBT = 0.013 years, and
. We consider now replacing the annual retirement with an energy technology that has half the capacity factor, half the lifetime, and requires twice as much energy,
, to install the same capacity,
, as the usual incumbent technology. The new system has NEER = EROI = 19, approximately equal to the incumbent, but to have the same expansion rate,
α, it must take only
years to install. Further, in order to produce the same amount of gross power (=
), we must install twice as many of the new systems each year. Therefore, twice as many new systems at twice the energy to install is four times more energy for installing energy technologies to replace the retiring system. In addition, during installation, there are fewer units of net energy for the energy system to deliver as output to the rest of the economy. Subsequently, energy prices would rise and demand would fall to meet the diminished net supply. This concept has been termed the “energy trap”, as noted by Sgouridis [
68].
This energy trap scenario is what can happen during a renewable and/or low-carbon transition
1 [
68]. The
emissions associated with a low-carbon transition can act against meeting the annual carbon emissins constraint early in the transition [
66]. Some researchers and proponents believe we can perform a 30–50 year transition to near 100% use of modern renewable energy without negative impact to economic growth [
69,
70], but this is simply unknown. It is one thing to know renewable energy systems (e.g., wind and PV solar), powered by primary energy flows, are economic at the margin in today’s fossil-dominated economy. It is yet another to model their future complete substitution for stocks of fossil fuels that require minimal investment for storage (e.g., a pile or coal or tank of gasoline). Photovoltaics as a global industry have only recently become net producers of energy during the initial production ramp up [
31]. Thus, at this point it is too much of an extrapolation to assume that renewables plus storage (electrochemically, thermally, and as gaseous or liquid fuels such as hydrogen and biofuels) can enable current consumption levels of the developed countries [
71,
72].
4.2.2. Internalizing Emissions into
Here I contemplate the implications of internalizing
emissions from fossil energy consumption. Data for
emissions for each country come from the IEA (see
Supplemental Information for more detail). Internalizing
emissions effectively decreases technology-specific and system-wide power return ratios (PRRs) and energy return ratios (ERRs) due to an emissions penalty (e.g., tax or price) and/or the increased capital and operating investments to reduce
per a given amount of delivered energy. Investments in energy efficiency, for example, can counteract this increase in cost, and efficiency investments become increasingly attractive as energy expenditures increase.
Figure 3 (top) presents calculations as if a constant
penalty were internalized in each year. In 1978 each 10 $2005/t
equates to 0.76% of the GDP in the 44 country data set, and in 2010 it equals 0.56% of the GDP. Thus, even a low price of 20 $2005/t
in 2010 is larger than the 1% of global GDP of annual climate-related investments called for in the Stern Review [
73].
The internalization of a
tax can be viewed from the standpoint of a threshold
above which the economic growth is severely limited or not possible for the incumbent economic structure. We might not know a precise economically critical
value, that changes over time as the economy undergoes structural changes, but this value certainly exists for a particular economy in its time [
14,
74]. Just by observing the few data for the modern post-World War II economy, a threshold
likely resides near 8% (between 6% and 10%) for developed economies. The two post-World War II major worldwide recessions have corresponded with
, and there is no post-World War II experience of
for any extended period of time. Bashmakov [
44] explains that this critical threshold value (approximately 11% for OECD consumer expenditures on energy, not primary energy as in this paper) creates an asymmetric impact on growth. The further
increases above the threshold value, the more the effect starts to dominate the economy and become a binding constraint [
44].
Assuming a constant critical value of
that includes a full internalization of
from fossil energy consumption, I can calculate the
cost associated with this fraction,
. The bottom graphic of
Figure 3 shows the required
emissions penalty in order for
to equal 6%, 8%, 10%, and 12% of the 44 country aggregate GDP.
If energy plus
expenditures were to rise toward a growth-limiting
, then a market price of
would decrease via feedback to prevent “energy +
” expenditures from breaching a critical
that induces recession (see
Figure 3). This feedback has been witnessed via the European Trading System (ETS) carbon price. In 2008 the European economy went into recession and has since had low growth. During the same time period the ETS carbon price dropped over 50% and remains below 10€/t
at time of writing.
In a pre-2008 world, European Union officials assumed that the economy would always grow such that the carbon price would rise to induce new low-carbon investments. An alternative scenario has emerged in which the opposite has happened: a no/low-growth economy has induced a low carbon price. Many have modeled and many hope, but the world has not yet proven, that an industrialized world economy can grow and decrease the rate of greenhouse gas (GHG) emissions (or fossil primary energy consumption) in the long run.
4.2.3. Summary of Relevance for Internalizing Emissions
The world is finite, and developed economies already have several near to medium-term structural headwinds to economic growth (e.g., population demographics, inequality, debt accumulation) that are occurring independent from a changing climate. As described by systems approaches, these headwinds are
expected to eventually occur on a finite planet [
40,
41]. As mentioned by Gordon [
39] regarding the US, “ …the consequences of environmental regulations and taxes that will make growth harder to achieve than a century ago …”, and thus reducing GHG emissions adds another headwind. The Stern Report (Part III, p. 204) notes that historical reductions in greenhouse gas emissions rates greater than 1%/year are associated with ‘economic recession or upheaval’ [
63,
73]. Anderson and Bows state that reducing emissions by >3%–4%/year is largely seen as incompatible with economic growth [
63]. Further, in one study that relates economic growth to increased use of renewables (one set of mitigation options), Chang
et al. [
75] analyze OECD countries from 1997–2006. They find that countries with annual GDP growth of >4.13% in one year tend to install more renewable energy in the following year whereas lower growth countries are less willing to spend on renewables. This type of insight could partially explain climate treaty success and failure. The Kyoto Protocol was successfully signed in 1997 at the third Conference of Parties (one year after
= 4.0%) whereas there was no comprehensive treaty signed at COP 15 (Copenhagen 2009) one year after
= 8.1%. The timing of these meetings relative to energy expenditures is merely coincidence, but perhaps the results are not.
However, sometimes a shift to cheaper fuels happened to coincide with that fuel having lower
emissions (e.g., UK “Dash for Gas” in 1990s [
73]), but rarely did total country emissions decrease. One exception is the US post-2008 due to increased activity in horizontal drilling and hydraulic fracturing for hydrocarbons. This drilling activity produced a large quantity of natural gas that has displaced some coal purchased for electricity. This coal displacement coincided with a decrease in total US energy-related
emissions (assuming no fugitive emissions from NG production) from 2007 to 2012 as well as a major economic downturn. However, the increased natural gas production was primarily driven by technological, financial, and other economic factors unrelated to policy goals for reducing GHG emissions. Further, globalization significantly disconnects the location of energy consumption (and GHG emissions) from that of consumption of goods and services [
12]. Thus, unless a country halts international trade of all goods and services, it is difficult to claim all absolute GHG reductions from energy from within the country’s borders.
Suffice it to say, predicting long-term economic growth, with or without GHG mitigation, is difficult to impossible. Most studies promoting renewable energy and/or the reduction of GHG emissions project economic growth and rapid GHG emissions reductions can happen simultaneously and into the future as far as they simulate [
76]. Here I use information from the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) as an example. The IPCC AR5 summarizes that GHG emissions reductions ≥3%/year are needed by 2030 and can accompany economic growth [
77]. The IPCC is informed by many models running baseline scenarios (those without additional mitigation efforts) from Integrated Assessment Models (IAMs) and other analyses. These baseline scenarios used by the IPCC indicate consumption grows anywhere from 300% to more than 900% between 2010 and 2100. When simulating idealized mitigation conditions, the IPCC estimates “…that reaching about 450 ppm
eq by 2100 would entail global consumption losses of…3% to 11% in 2100” [
78] or GDP losses of typically less than 10% in 2100.
Thus, most simulations show mitigation costs as trivial compared to gains in economic growth, and within the noise of the accuracy of the models. No matter what the investment in the energy system or the level of climate damages, the models simulate that economy will always grow. Stern [
79] and Pindyck [
80] point out how much IAMs are likely to underestimate damages and overestimate economic growth. One major reason is that IAMs often incorporate an exogenous assumption of constant annual rate of increase in total factor productivity (TFP) that is independent of energy-related factors (see Figure A.II.1 of [
81]). Thus, the normal IAM assumption is inadequate because it presents the case to policy makers that even dramatic increases in energy investment for a renewable energy transition and/or climate change mitigation don’t affect TFP and hence economic growth [
79,
80].
In addition, as pointed out by Loftus
et al. [
76], many low-carbon scenarios assume an annual decrease in energy intensity,
TPES/GDP, that is either faster than historical trends (∼−0.8%/year from 1970–2010 [
77]) or is sustained at decline rates of −1.5%/year to −2%/year that have only been temporarily achieved since 1970 (e.g., in the early 1980s and late 1990s/early 2000s). The mean (or “default”) of the baseline scenarios as used by the IPCC AR5 assume global energy intensity changes of approximately −1.0%/year to −1.7%/year (e.g., Figure 6.17 Chapter 6—Assessing Transformation Pathways [
78]).
If TFP and declines in energy intensity are overestimated, the subsequent calculations of the social cost of carbon (SCC) will be understated. Stern [
79] notes that this effectively leads one to conclude that high concentration levels (e.g., 650 ppm
eq) are acceptable. However, as previously discussed, results in this paper and other research show that energy resource and technology characteristics (e.g., conversion efficiency) can partially or largely describe TFP via impact on energy cost share [
8,
10,
18]. TFP is negatively affected by higher
that is itself a factor of the energy technologies and the rate of low-carbon energy transformation that IAMs are meant to simulate. Hence, if we invest in energy systems with worse biophysical and economic qualities (e.g., lower net energy, higher cost) and at a higher rate, we should expect lower TFP and hence lower economic growth. In addition to optimistic assumptions about TFP (even if assumed lower than historical values) and energy intensity, both Stern [
79] and Pindyck [
80] indicate that climate models grossly underestimate climate damages at high atmospheric concentration levels. Thus, those authors would argue that estimates for the social cost of carbon (SCC) are also too small.
Here I show an example calculation indicating that the future annual emissions cost ranges from the IPCC translate to 1%–2% of GDP—enough to potentially increase
from 6%–7% to above 8%, or from a condition associated with growth to one associated with recession. The IPCC reports that global carbon prices for a target 430–530 ppm
eq would be near 1500 $2010/t
(150–6000 $2010/t
) in 2100 (Figure 6.21 [
78]). The median net present value (NPV) of the price of
from these simulations is approximately 36 $2010/t
(20 to 55 $2010/t
at 25%–75% range, Figure 6.21 [
78]). Applying this median NPV price of carbon (=33 $2005/t
) to the 2010 emissions of the 44-country IEA data set (as in
Figure 3) translates to 940 $2005 billion (=1.8% of GDP), or
. Thus, the range of
price translates to 1%–2% of GDP. If
is already greater than 6%–7% of GDP (as it was in 1978–1985, 2008, 2010, and likely also during 2011–2014, see
Supplemental Figure S4) then
at these
prices will be 7%–9% of GDP, at a possible threshold above which there has historically been recession.
Climate policy might have no choice but to accept decreasing rates of GHG emissions along with a declining economy. The reasoning of this previous sentence is not based upon the uniqueness of investing in climate change mitigation. Rather, the reasoning derives from the mathematical premise of Pareto optimality [
82]. If one has optimized one objective (e.g., economic growth) without harming a second objective (e.g., GHG emissions), and also optimized the second objective without harming the first, it is then mathematically impossible to simultaneously further optimize one objective without hurting the other. Thus, it is possible that the world economy can reach a time where there is a necessary tradeoff between maximizing economic growth and minimizing GHG emissions (or any number of other socio-economic objectives). With respect to a tradeoff of economy and GHG, I do not claim that the world economy is currently at a point of Pareto optimality, that the world will ever will be at such a point, or that we will ever know if we reside at such optimality. I only state that this tradeoff of economic growth versus climate mitigation is real.