Solar Photovoltaics

When most people think of “solar power,” they think about one of two things – vast arrays of solar collectors laid out in hot deserts (the left-hand panel below) or smaller arrays on rooftops or highways (the right-hand panel below). This is perhaps the most ubiquitous method of converting solar energy into electricity, but it is not the only method. These arrays of solar collectors are known as “solar photovoltaic” installations or Solar PV for short.

Solar photovoltaics, large and small

Credit: Left-hand panel is US Air Force, right-hand panel is licensed under CC-BY-SA-3.0

Solar PV installations consist of individual collectors called cells, which are packaged together in bundled modules. An individual cell does not generate enough electricity to power much of anything, which is why they must be bundled together. A single module might be enough to provide electricity for a single parking meter or roadside telephone. A number of modules can be further bundled together to form an array (see below). Multiple arrays might be needed to provide electricity for a building or a house.

Solar cell, module, and array

Credit: Argonne National Laboratory [3]

There are many different kinds of solar PV cells in existence (and even more being developed in research laboratories), but they all work in more or less the same way. Unlike virtually any other type of power plant (be it coal, natural gas or wind), there is no turbine in a Solar PV cell. In fact, there are basically no moving parts at all. .

Solar PV cells harvest solar energy through a phenomenon called the photovoltaic effect, discovered in 1839 by the French physicist Bequerel. Photons of solar energy interact with electrons to “excite” them, causing them to move through conductors, thus producing an electric current. The first solar PV module was made at Bell Labs in the 1950s, but was too expensive to be more than a curiosity; in the 1960’s NASA started to use PV modules in spacecraft and by the 1970s, people started to explore their use in a wider range of terrestrial applications.

This following video explains a bit more about how Solar PV cells work and describes the different Solar PV technologies in use today. One of the potentially most important evolutions in Solar PV technology is the use of semiconducting materials other than silicon in Solar PV cells. These materials are of interest because they could, in concept, allow more of the sun’s energy to be captured on a single array. But they face barriers in the form of high costs and, in some cases, questions about the availability of raw materials.

Video: Photovoltics, a Diverse Technology (4:26)

Most modern Solar PV technologies are relatively inefficient compared to other forms of electricity generation. Remember here that “efficiency” refers to how much of the fuel that is injected into an electricity generation system is actually converted into useful electricity, versus being rejected as waste heat or otherwise escaping from the generation system. While modern coal-fired and gas-fired power plants can have efficiencies as high as 60% (or sometimes even higher), most Solar PV cells convert sunlight to electricity with an efficiency of 20% or less (see below), though this number has been rising over time.

Efficiency of different Solar PV technologies over time

Click for a text description of the Solar PV technologies graph.

This chart from NREL (National Renewable Energy Laboratory) tracks the best research efficiencies of various solar cell technologies over time. Below is a detailed breakdown of each dataset, categorized by solar cell type, along with trends and notable efficiency milestones.

Multijunction Cells (Purple)

• Description: High-efficiency solar cells made from multiple semiconductor materials that capture different parts of the solar spectrum.
• Types:
  • Three-junction (concentrator)
  • Three-junction (non-concentrator)
  • Two-junction (concentrator)
• Trends:
  • Rapid efficiency gains from the 1980s onward.
  • 1995: First exceeded 30% efficiency.
  • 2005–2015: Surpassed 40% efficiency, reaching 45.5% in 2015 (record efficiency).
  • Key contributors: Spectrolab, Fraunhofer ISE, Boeing-Spectrolab, NREL.

Single-Junction GaAs Cells (Pink)

• Description: Made from Gallium Arsenide (GaAs), known for high efficiency.
• Types:
  • Concentrator
  • Thin-film crystal
• Trends:
  • 1980s: Early developments showed steady progress.
  • 1995–2005: Efficiency surpassed 25%.
  • 2010–2015: Efficiency reached 29–30%.
  • Key contributors: NREL, Radboud, Alta Devices.

Crystalline Silicon (Blue)

• Description: The most widely used commercial solar cell technology.
• Types:
  • Single crystal (Monocrystalline)
  • Multicrystalline (Polycrystalline)
  • Thin-film Silicon
  • Silicon Heterojunction (HIT)
• Trends:
  • 1980s: Efficiency ranged from 10% to 15%.
  • 1990s: Research pushed efficiency beyond 20%.
  • 2015: Efficiency peaked at about 26.6%.
  • Key contributors: SunPower, Panasonic, UNSW, Fraunhofer ISE.

Thin-Film Technologies (Green)

• Description: Low-cost, lightweight solar cells using non-silicon materials.
• Types:
  • Cu(In,Ga)Se₂ (CIGS)
  • CdTe (Cadmium Telluride)
  • Amorphous Si:H (stabilized)
  • Nano-, Micro-, Poly-Si
  • Multijunction Polycrystalline
• Trends:
  • 1975–1990: Slow improvements, with efficiencies around 5–10%.
  • 2000s: Notable breakthroughs, pushing CdTe and CIGS beyond 15% efficiency.
  • 2015: Best CIGS efficiency reached 22.3%; CdTe around 21.5%.
  • Key contributors: First Solar, NREL, ZSW, Solar Frontier, GE.

Emerging PV Technologies (Red)

• Description: Next-generation solar technologies still in early development.
• Types:
  • Organic solar cells
  • Organic-inorganic perovskites
  • Quantum dot solar cells
• Trends:
  • 2000s: Initial efficiencies below 5%.
  • 2010s: Perovskite solar cells saw rapid efficiency increases, reaching over 20% by 2015.
  • Key contributors: Oxford PV, UCLA, EPFL, University of Valencia.

Overall Observations

• Multijunction Cells remain the most efficient, exceeding 45%.
• Crystalline Silicon dominates commercial markets, reaching 26.6%.
• Thin-Film and Emerging PV show promise for future cost-effective solutions.
• Perovskites and Quantum Dots could revolutionize the field if efficiency gains continue.

Credit: National Renewable Energy Laboratory [6]

Whether the efficiency of Solar PV cells is all that important is a matter of some debate. On the one hand, higher-efficiency cells would require less land or space to produce a given amount of electricity. Land use (or the number of rooftops) can be a significant limiting factor in the deployment of Solar PV. On the other hand, fuel from the sun is free and there is no scarcity of sunlight, so whether Solar PV cells can achieve 30% efficiency versus 20% efficiency may not be such a big deal, and may not be worth the extra economic cost to produce such high-efficiency cells.

Concentrating Solar Power

If you have ever left a cold drink out in the sun during the summertime (or if you have children, if you have ever left water in the kiddie pool out in the sun for a long time), you would notice that the formerly cold water gets warm – maybe even hot. If it happens to be summertime where you are living right now, try it! Whether you realize it or not, this little science experiment is the basis for a second way of harnessing the sun’s energy to produce electricity, called “concentrated solar power” or CSP. (This technology is also sometimes called “solar thermal.”)

The Gemasolar CSP plant in Spain is using molten salt to collect solar energy concentrated by an array of mirrors. This molten salt acts as a thermal battery, enabling the generation of electricity even when the sun is not shining.

Credit: Gemasolar2012 [7], by Ion Tichy [8] (CC BY-SA [9]) from Wikimedia Commons [10]

The following video explains how CSP works. The basic idea is that a collection of mirrors reflects the sun’s light (and heat) onto a large vessel of water or some other fluid in a metal container. With enough mirrors reflecting all of that sunlight, the fluid in the metal container will get hot enough to turn water into steam. The steam is then used to power a turbine just like in almost any other power plant technology

Solar Energy Potential and Utilization

In addition to being free as a source of energy (it does cost money to harness it and turn it into electricity), energy from the sun is practically limitless. The surface of the Earth receives solar energy at an average of 343 W/m². If we multiply this times the surface area of the Earth, about 5x10¹⁴ m², we get 1715x10¹⁴ W. But, 30% of this is reflected, and only 30% of the Earth is above sea level, so the usable solar energy we receive on the land surface is about 360x10¹⁴ W. We need to reduce this further because not all of the land surface is suited to installation of solar PV panels — we don't want to cut down forests, and ice-covered areas are not suitable, so we reduce the area by about one half. Over the course of a year, this amount of solar energy adds up to 66x10²² Joules. In 2018, we used about 600x10¹⁸ Joules of energy, which is just a shade less than 0.1% of the harvestable solar energy we receive on the land. This means that even if we got all of our energy from the Sun, we would not make a dent in the total! The potential is vast — 10,000 times what we need!

Let’s consider what it would mean for us to get all of our energy from Solar PV — how much of the Earth’s surface would we need to cover with panels? The black dots (radii of 100 km) in the figure below represent areas that could generate enough energy from sunlight to completely power the planet for an entire year. Practically, there are barriers to running the planet entirely on sunlight (everything would need to be electrified, we would need very large quantities of battery energy storage, and so forth), but the dots are useful as a demonstration of just how vast the energy production potential from solar is.

Global average solar irradiance. Areas in red have a higher-strength solar energy resource on average. The black dots indicate areas with sufficient solar energy potential to supply the entire world’s energy demands.

Click here for a description of the Global average solar irradiance image.

This image is a world map illustrating the annual mean solar potential across the globe, measured in watts per square meter (W/m²). The map is sourced from Matthias Loster, 2006, and includes a total solar potential estimate of 18 terawatt-equivalents (TWe) indicated in the bottom right corner with the symbol "Σ⦿ = 18 TWe."

Map Overview:
The map shows a global view with continents outlined in black, including North and South America on the left, Africa in the center, Europe and Asia above, and Australia on the right. The background is a gradient of colors representing solar potential, with a color scale at the bottom ranging from purple (lowest) to red (highest)

• Color Scale:
  The color bar at the bottom ranges from 0 to 350 W/m². Purple represents the lowest solar potential (0–50 W/m²), transitioning through blue (50–100 W/m²), green (100–150 W/m²), yellow (150–200 W/m²), orange (200–300 W/m²), and red (300–350 W/m²) for the highest solar potential.
• Solar Potential Distribution:
  • High Solar Potential (Red/Orange): Areas with the highest solar potential (250–350 W/m²) are concentrated near the equator, including Central Africa, the Middle East, northern Australia, and parts of the central Andes in South America. These regions appear in shades of red and orange.
  • Moderate Solar Potential (Yellow/Green): Moderate solar potential (150–250 W/m²) spans much of South America, Southern Africa, India, Southeast Asia, and northern Australia, shown in yellow and green shades.
  • Low Solar Potential (Blue/Purple): Areas with the lowest solar potential (0–150 W/m²) include the polar regions, northern North America, Northern Europe, and parts of Russia, depicted in blue and purple shades
• Black Dots:
  Several black dots are scattered across the map, likely representing specific locations or solar energy projects. These dots are located in the southwestern United States, central South America, central and Southern Africa, the Middle East, India, and northern Australia.
• Additional Details:
  The map uses a gradient color scheme to visually represent the intensity of solar potential, with equatorial regions showing the highest potential due to their proximity to the sun’s direct rays. The source, "Matthias Loster, 2006," is noted in the bottom right corner.

It’s kind of amazing to see how little area of the Earth would need to be covered to achieve this.

Source: Total Primary Energy Supply [13]

One of the important differences between Solar PV and CSP is that CSP requires more intense sunlight, and as such, it is not a viable option in many places. In contrast, Solar PV works just about everywhere — it is more versatile. Another important difference is in scale — CSP is really suited to utility-scale power plants, whereas Solar PV works at both the utility-scale and the very small scale.

The map below shows the PV potential for the world. The variability in the map is mainly a function of cloudiness and latitude. Many of the big, utility-scale solar PV plants are located in the red areas, but there is a surprising amount of Solar PV energy being harvested in places like Germany and Japan, both of which are fairly cloudy. But, even in a fairly cloudy place like Pennsylvania, you can see from the map that we could expect about 1460 kWh per year from a 1 kW PV array. From this, you can calculate how many square meters of PV panels you’d need to provide the electricity for a house that uses the typical 10,800 kWh per year. If you divide 10,800 kWh by 1460, you see that you’d need about 7kW of solar panels, which would fit on a typical house roof. The main point here is that Solar PV is a viable energy source in most parts of the world where people are living. In contrast to Solar PV, energy from CSP is only viable in places where the daily totals in the map above are higher than 6 kWh/day. Nevertheless, there are many regions where CSP viability and human population coincide, so it too can be an important energy resource in the future.

This world map from the World Bank Group’s Global Solar Atlas shows the estimated potential for Solar PV energy in terms of kWh energy produced from a solar PV array of 1 kW. It is important to understand that daily totals are an average value — the output each day will vary according to how cloudy it is and how high in the sky the Sun is. The yearly totals are just the daily total times 365.

Click for a text description of the Photovolitic power potential map.

The image is a world map titled "Solar Resource Map: Photovoltaic Power Potential," displaying the global distribution of photovoltaic power potential. The map uses a color gradient to indicate the long-term average of photovoltaic power potential (PVOUT), measured in kilowatt-hours per kilowatt-peak (kWh/kWp). Areas with higher potential are depicted in shades of red and orange, while lower potential areas are shown in blues and greens. Notably, regions such as North Africa, the Arabian Peninsula, and parts of Australia show high potential with intense red and orange hues. Northern Europe and parts of Canada show lower potential with blue and green shades. A scale beneath the map indicates the PVOUT values ranging from 2.0 to 6.4 kWh/kWp. Below the scale, yearly totals are listed from 730 to 2337 kWh/kWp. Logos of the World Bank Group, ESMAP, and Solargis are displayed at the top right.

Credit: Global Solar Atlas [15]

The Changing Economics of Solar Energy

The generation of solar energy – primarily through Solar PV – is a story of exponential growth. Since 2000, the global Solar PV industry has grown by around 25% per year on average, so installed capacity has been doubling every 2.7 years (see below). Even so, solar represents a very small sliver of total global power generation — for now.

This shows the history of global solar energy generation in Exajoules (EJ) of energy each year (1 EJ = 10¹⁸J). This growth history is following an exponential curve. In 2018, this represents a small fraction of global energy consumption, which is almost 600 EJ.

Click for a text description of the Global Solar Energy Generation History graph.

The image is a line graph illustrating the historical trend of global solar energy generation from 1985 to 2020. The x-axis represents the years, marked from 1985 to 2020, while the y-axis indicates the energy generated per year in exajoules (EJ), ranging from 0 to 6. The graph depicts a sharp upward trend starting around 2005, indicating significant increases in solar energy production. The blue line that represents the data forms a steep curve upward after 2010, emphasizing rapid growth. A text box on the graph annotates that the average growth rate is 25% per year. The title of the graph is "Global Solar Energy Generation History."

Source: David Bice, data from BP Statistical Review of Energy, 2018 [16]

The nice thing about exponential growth is that it is easy to project it into the future. Over the time period shown in the graph above, solar energy generation has grown by 25% per year; if we continue that into the future, we find that before long, we would have enough solar energy to make up a substantial portion of the global energy needs by 2030 (see figure below). By the year 2040, this growth would rise to 1360 EJ, more than twice the global energy consumption of the present. Of course, that makes no sense — we would not produce more energy than we need, and this reminds us of an important fact, which is that exponential growth cannot continue forever.

This shows the history of global solar energy generation in Exajoules (EJ) of energy each year (1 EJ = 10¹⁸J). This growth history is following an exponential curve. In 2018, this represents a small fraction of global energy consumption, which is almost 600 EJ.

Click for a text description of the Global Solar Energy Generation Projection graph.

The image is a line graph titled "Global Solar Energy Generation Projection," depicting projected solar energy generation from 1985 to 2030. The x-axis represents the year, ranging from 1985 to 2030, and the y-axis represents the energy generated per year in exajoules (EJ), ranging from 0 to 120. The graph starts with a nearly flat blue line from 1985 to around 2015, indicating little to no growth in solar energy production. After 2015, the line turns orange and begins to curve sharply upward, showing a significant increase, projecting exponential growth in solar energy generation up to 2030. A text box within the graph notes "Projection into the future assuming 25% per year growth."

Source: David Bice, data from BP Statistical Review of Energy, 2018 [16]

One reason to trust this projected future growth is that the price of solar energy has fallen dramatically over time as can be seen in the graph below. In fact, if the generation of solar PV energy has been growing exponentially, the price has been dropping exponentially.

The price history of solar PV cells in $/watt shows an incredible decline in price. This is due to technological advances and the economy of scale as more and more PV cells are manufactured.

Click for a text description of the graph: Price History of Silicon PV Cells.

This bar chart illustrates the decline in the cost of silicon photovoltaic (PV) cells from 1977 to 2015, measured in US dollars per watt ($/Watt).

Key Observations:

1977:

• • The price of silicon PV cells was $76.00 per watt, the highest recorded in the dataset.
  • Marked by a tall blue bar at the far left.

1980s:

• • Significant price reduction as PV technology improved.
  • By 1985, the price dropped to around $10 per watt.
  • The bars become progressively shorter, showing a steep decline.

1990s:

• • The price stabilized around $5–10 per watt.
  • The bars maintain similar heights, indicating slower reductions.

2000s:

• • Continued gradual decline, reaching around $2 per watt by mid-2000s.
  • More efficient manufacturing and increased adoption contributed to lower costs.

2015:

• • The price reached $0.30 per watt, as indicated by a highlighted blue label at the bottom right.
  • This marks a 99.6% reduction from 1977 prices.

Additional Details:

• A text box in the center of the graph reads:
  "Price history of silicon PV cells in US$ per watt"
• Data Source: Bloomberg New Energy Finance & pv.energytrend.com
• The trend follows Swanson’s Law, which states that solar PV prices drop by 20% for every doubling of cumulative shipped volume.

Source: Price history of silicon PV cells since 1977 [17] by Rfassbind [18]from Wikimedia Commons [19]

The price decrease is following a pattern that has been given a name: Swanson’s Law, which states that the price drops by about 20% for each doubling in the number of PV cells produced. This law suggests that the prices of solar PV energy will continue to decline in the future.

This brings us to an important question — how does the cost of solar energy compare to other sources of energy? Energy economists have come up with a good way of comparing these costs by adding up all of the costs related to producing energy at some utility-scale power plant (a big wind farm, a big solar PV array, a CSP plant, a nuclear plant, a gas or coal-burning power plant). This is called the levelized cost of energy, and you get it by taking the sum of construction costs, operation and maintenance costs, and fuel costs over the lifetime of a plant and then dividing that by the sum of all the energy produced by the plant over its lifetime. This cost provides us with a way of comparing the energy from different sources. Since the boom in natural gas production due to fracking, natural gas has been the lowest cost form of energy (which is why coal is being used less and less), but energy from solar and wind have been decreasing rapidly, as can be seen in the following graph. When a renewable electrical energy resource such as solar or wind becomes equal in cost to the cheapest fossil fuel source of electricity, we say that the renewable resource has reached "grid parity". Once grid parity is achieved, the renewable resource makes sense from a purely economic standpoint, and as it drops below the grid parity point, it is the smartest electrical energy resource.

The levelized cost of solar energy in the US has been dropping fast in recent years and has been slightly cheaper than electrical energy from natural gas since 2015. The point in time where the two are equal is when solar energy achieved what is called grid parity. Wind energy reached grid parity by 2012, so at this point in time, both of these renewable sources provide cheaper energy than the cheapest fossil fuel source.

Click for a text description of the graph: Levelized Costs of Solar, Wind, and Natural Gas (2008–2018).

This line graph displays the levelized cost of energy (LCOE) for solar, wind, and natural gas from 2008 to 2018 in 2018 dollars per megawatt-hour (MWh). The LCOE represents the total cost of generating electricity from each source, considering installation, maintenance, and fuel costs.

Key Observations:

Solar Energy (Red Line)

• • In 2008, the LCOE for solar was about $180 per MWh, the highest of the three energy sources.
  • The cost declined rapidly over the years, reaching approximately $40 per MWh by 2016.
  • By 2018, solar became the cheapest energy source at under $30 per MWh.
  • The decline reflects advances in solar panel technology, manufacturing efficiency, and increased adoption.

Wind Energy (Green Line)

• • The cost of wind energy fluctuated between $60–80 per MWh from 2008 to 2010.
  • After 2010, wind costs began to decline, reaching a low of about $20 per MWh in 2018.
  • The drop can be attributed to larger and more efficient wind turbines, better grid integration, and falling installation costs.

Natural Gas (Blue Line)

• • The LCOE for natural gas remained relatively stable, fluctuating between $40-60 per MWh over the period.
  • Natural gas was cheaper than solar for most of the timeline but was surpassed by both solar and wind by 2018.
  • The stability of natural gas prices is due to fuel costs, infrastructure maintenance, and policy factors.

Overall Trends:

• Solar energy saw the most dramatic cost reduction, making it one of the cheapest electricity sources by 2018.
• Wind energy also experienced a significant drop, becoming the least expensive energy source by 2018.
• Natural gas remained relatively stable, but was no longer the most cost-effective option by the end of the period.

Source: David Bice, data from Lawrence Berkeley Labs [20].

Part of the reason that solar and wind have expanded in recent years has to do with government policies — a number of countries have instituted subsidy and incentive programs that offset a large portion of the construction/installation costs of solar and wind technologies or devise rules that otherwise give advantages to electricity generation from renewables. Subsidies enacted in various countries have included feed-in tariffs (which guarantee an above-market sales price for solar power); rebates (which directly offset capital and installation costs); and favorable tax treatment (which is like an indirect feed-in tariff). Germany has one of the world’s largest Solar PV markets not because it has the best solar resource on earth but because it has been willing to support a generous feed-in tariff on solar power. (For many years the tariff was over 30 cents per kilowatt-hour, or more than five times the average power price in the United States; in recent years the tariff has been reduced.) These government policies have effectively stimulated the growth of these renewable energy resources, which has, in turn, resulted in lower prices.

How Wind Turbines Work

In a conventional power plant (fueled by coal or natural gas), combustion heats water to steam and the steam pressure is used to spin the blades of a turbine. The turbine is then connected to a generator, which is a giant coil of wire turning in a magnetic field. This action induces electric current to flow in the wire. The workings of a wind turbine are much different, except that instead of using a fossil fuel heat to boil water and generate steam, the wind is used to directly spin the turbine blades to get the generator turning and to get electricity produced.

The inner workings of a wind turbine consist of three basic parts, seen in the figure below. The tower is the tall pole on which the wind turbine sits. The nacelle is the box at the top of the tower that contains the important mechanical pieces – the gearbox and generator. The blades are what actually capture the power of the wind and get the gears turning, delivering power to the generator. The direction that the blades are facing can be rotated so that the turbine always faces into the wind, and the pitch of the blades (the angle at which the blades face into the wind) can also be adjusted. Pitch control is important, especially in very windy conditions, to keep the gearbox from getting overloaded.

Modern wind turbines sit upon towers that are typically 80 meters high or taller, with rotating blades that are 50 meters or longer.

Source: Wikipedia: Lamma wind turbine [22] CC BY-SA 3.0 (Creative Commons [23])

The amount of power (in Watts) collected by a wind turbine is explained in the following equations:

The physics of wind power

Click here for a text description of the physics of wind power equation.

This figure explains the physics of wind power. So we begin with this notion of the moving wind having some kinetic energy which is 1/2 m v2. So that is kinetic energy. Power is related to energy in the following way: It is energy per unit of time. So if we want the power that we can get from that moving wind, we have to take the kinetic energy, and then the mass flux rate instead of just the mass. Mass flux rate is how much mass is moving per unit of time. That is dm over dt, change in mass over change in time. And that is equal to the air density times the area swept out by the windmill blades times the velocity, so that velocity and area multiplied together gives you something with the units of measure are cubic meters per second, and then you multiply that by the density and that gives you kilograms per second and that’s the mass flux rate. If you put all that together, you see the wind power is equal to one half times the air density times the area swept by the blade times the velocity cubed. So you see, the velocity is super important in this. Now then it turns out that there is an efficiency limit, something called the “ Betts Limit” that means that the power you can actually collect is 0.3 times the air density times the velocity cubed.

Source: David Bice

The Kinetic Energy (KE) of the wind is:

Where m = mass, and v = velocity of wind.

Power (P) in the wind is the KE per unit time, so we replace the mass(m) with the mass flux rate dm/dt:

Where p = air density, and A = swept area of blades.

So the wind Power(P) is:

If the wind turbine collected all of this power, the wind would have to stop and the blades would stop spinning. If you want the blades to keep spinning, it turns out that you can collect about 60% of the power (called the Betz limit).

So, collectible Power(P) is:

How much power could we get with a turbine whose blades are 100m long, with a wind speed of 10m/s (about 22mpg>, with an air density of 1.2kg/m2?

This is clearly a lot of power! But, mechanical inefficiencies related to the gears and the generator mean that we might only get 30% of this figure, but that is still a lot of power from one turbine.

All wind turbines have a minimum wind speed that differs depending on the size but is typically about 4-5 m/s (10 mph) and maximum wind speed above which they shut down to avoid damage, usually around 20-25 m/s (about 50 mph). Most wind turbines have a maximum spinning rate, reached a bit above the minimum velocity, and when the wind speeds up, the pitch of the blades is adjusted so that the rate of spinning remains more or less constant. The figure below shows a typical "power curve" for a small wind turbine.

Power curve for a 1.5 MW wind turbine

Click here for a text description of the power curve for 1.5 MW wind turbine.

This figure shows the power curve for a 1.5 megawatt wind turbine. So on the Y-axis is the power and the X-axis is the wind speed in miles per hour. And what you can see is that there is sort of a threshold speed that is something like 6 miles per hour wind speed you start to get some power. And as the wind speed increases, the power output rises rapidly until you get to about 30 miles per hour. At that point the power sort of saturates and flattens out and with more wind you don’t get any more power. So it reaches its capacity at 1.5 megawatts and it generates that up until 50 miles per hour and above that the power drops off rapidly because the wind turbine has a shut off mechanism will turn off if the wind gets going to fast because of the turbulence that can cause damage to the wind turbine. So they just shut down if the winds get to great.

Source: US Department of Energy, Idaho Office

The wind, as you may have noticed, is highly variable in any given place, but as a general rule, it is stronger and steadier as you rise up above the ground. This is because friction between the wind and the land surface slows the wind. But there is also a lot of regional variation in the wind velocity. Both of these factors (elevation above the ground and location) can be seen in the maps below, showing the average wind speed in the US at two different heights.

United States - Annual Average Wind Speed at 30 m

Click here for a text description of the U.S. Annual Average Wind Speed at 30 m.

These two maps of the United States show the average annual wind speed at two different heights above the surface. The upper map shows the wind speed at 30 meters height and the one below shows it at about a hundred meters. You can see a couple thing right away. One is that there is just a lot more wind at greater velocities at this higher elevation above the lands surface. You get to 100 meters and there are a lot of places in the central part of the US where you get wind speed from 8 to 10 meters per second, which is really moving along quit fast. And you also see this lower map of 100 meter of wind speeds of the offshore regions everywhere on the west coast and the east coast and around the Gulf of Mexico there are very high wind speeds. Also the Great Lakes are like this. The primary reasons these offshore regions have such high wind speeds and also why higher up you have such wind speeds are because there are less friction in those settings. So you go higher up from the surface there is less friction from the air and all the trees and the roughness of the land surface. That roughness slows the wind down and as you rise above that to 100 meters you get away from that disturbance and have higher wind velocities. You can also see that in the mid-continent region, both the 30 meter and the 100 meter heights, that’s the area with the greatest wind potential. You have these annual average wind speeds that are quit high and this is primarily because this is flat part of the country. There are not a whole lot of topography in those areas so the winds can really get going and be maintained. They do not encounter mountains and valleys and the sort of complexity that you see in other areas where further out west the wind speeds are not that high. So you can look at this and see right away that if you wanted to develop wind power, the best places are in the middle of the continent and at a high elevation 100 meters above the surface. That is why you see so many tall wind turbines to get up that high.

Credit: National Renewable Energy Laboratory (NREL) [24]

United States - Land-based and Offshore Annual Average Wind Speed at 100 m

Click here for a text description of the U.S. Land-based and Offshore Annual Average Wind Speed at 100 m.

These two maps of the United States show the average annual wind speed at two different heights above the surface. The upper map shows the wind speed at 30 meters height, and the one below shows it at about a hundred meters. You can see a couple thing right away. One is that there is just a lot more wind at greater velocities at this higher elevation above the land's surface. You get to 100 meters and there are a lot of places in the central part of the US where you get wind speed from 8 to 10 meters per second, which is really moving along quite fast. And you also see this lower map of 100 meter of wind speeds of the offshore regions everywhere on the west coast and the east coast and around the Gulf of Mexico there are very high wind speeds. Also, the Great Lakes are like this. The primary reasons these offshore regions have such high wind speeds and also why higher up you have such wind speeds are because there are less friction in those settings. So you go higher up from the surface, there is less friction from the air and all the trees and the roughness of the land surface. That roughness slows the wind down and as you rise above that to 100 meters you get away from that disturbance and have higher wind velocities. You can also see that in the mid-continent region, both the 30 meter and the 100-meter heights, that’s the area with the greatest wind potential. You have these annual average wind speeds that are quite high, and this is primarily because this is a flat part of the country. There are not a whole lot of topography in those areas, so the winds can really get going and be maintained. They do not encounter mountains and valleys and the sort of complexity that you see in other areas, where further out west the wind speeds are not that high. So you can look at this and see right away that if you wanted to develop wind power, the best places are in the middle of the continent and at a high elevation 100 meters above the surface. That is why you see so many tall wind turbines to get up that high.

Credit: National Renewable Energy Laboratory (NREL) [24]

The graphs above show annual average wind speeds in the US at 2 different heights above the ground surface. For reference, 10 m/s is 22.3 mph. You can see that the wind speeds at 100 m are far greater than at 30 m — this is the friction effect of the land surface (which is minimal above large water bodies). As you can see, the Great Plains have great wind potential, as do the Great Lakes and offshore areas on both coasts.

The area covered by the turbine’s blades is another important factor in determining power output. While wind turbines are available in a wide variety of capacities, from a few kilowatts to many thousands of kilowatts, it’s the larger turbine sizes that are being deployed most rapidly in wind farms. Several years ago the image on the right side of the figure below of a Boeing 747 superimposed on a wind turbine gave an astonishing representation of the scale of the state-of-the-art wind technology. Now, turbine rotor diameters are approaching the size of the Washington Monument!

Over the past decade, wind turbine blades have grown from being about the size of the wingspan of a jumbo jet to being about as long as an American football field.

Click for a text description of the Wind Turbine graph.

The image is a graph that illustrates the progression of rotor diameters of wind turbines over time, comparing them to the wing span of an Airbus A380.

• The x-axis represents the years from 1985 to 2010 and beyond, with specific years marked: '85, '87, '90, '91, '93, '95, '97, '99, '01, '03, '05, '10, and an estimated future point labeled as "1ˢᵗ year of operation" with a capacity range of 8 to 10 MW.
• The y-axis represents the rotor diameter in meters (m), ranging from 15 meters to 250 meters.
• The graph shows a series of circles, each representing the rotor diameter of wind turbines at different points in time. These circles increase in size as the timeline progresses, indicating the growth in rotor diameter over the years.
• Each circle is labeled with its corresponding rotor diameter:
  • 1985: 15 m
  • 1987: 30 m
  • 1990: 40 m
  • 1991: 50 m
  • 1993: 60 m
  • 1995: 70 m
  • 1997: 80 m
  • 1999: 90 m
  • 2001: 100 m
  • 2003: 110 m
  • 2005: 120 m
  • 2010: 130 m
  • Future (8-10 MW): 250 m
• A red line runs through the centers of these circles, showing the trend of increasing rotor diameter over time.
• On the right side of the graph, there is an illustration of an Airbus A380 with a wing span of 80 meters for comparison. An arrow points from the Airbus A380 to the largest circle (250 m), suggesting a comparison between the wing span of the airplane and the rotor diameter of future wind turbines.
• The background of the graph is light blue, and the circles are shaded in orange with red outlines.

This graph visually demonstrates the significant increase in wind turbine rotor diameters over the years, projecting into the future with much larger sizes compared to current standards.

Credit: UpWind: Design Limits and Solutions for Very Large Wind Turbines [25], 2011. European Wind Energy Association

Activate Your Learning

Given that the area of wind captured by the turbine is proportional to the square of the radius (essentially the length of the blade), if you were to double the length of a wind turbine's blade, how much more power would that turbine generate? Assume that wind speed and all other variables remain the same.

Click for the answer.

ANSWER: The area of a circle is given by A=πr², where r is the radius of the circle. If the length of the blade, which defines the radius of the circular area over which wind is captured, was increased by a factor of 2, then the area would increase by a factor of 2². Therefore, if all other variables were held constant, then according to the wind power equation above, doubling the blade length will produce 4 times as much energy.

Market Deployment of Wind Energy

Over the last 20 years, growth in the total installed capacity of wind energy generation across the globe has been growing rapidly. Germany was the first country to lead the development of wind power, but the US and China have dominated the growth since 2010. China is especially impressive in terms of its recent growth.

The growth in wind power capacity over the last 20 years. Both China and the US are growing exponentially.

Click here for a text description of the growth in wind power capacity over the last 20 years graph.

The image is a line graph titled "Cumulative installed wind energy capacity, gigawatts," which shows the growth in installed wind energy capacity from 1997 to 2016 for several countries. The y-axis represents the capacity in gigawatts (GW), ranging from 0 to 140 GW. The x-axis represents the years from 1997 to 2016.

• China (green line) shows the most significant growth, starting from near 0 GW in 1997 and rising sharply to over 140 GW by 2016.
• United States (red line) starts with a low capacity in 1997 but increases steadily, reaching around 80 GW by 2016.
• Germany (blue line) also shows steady growth, starting from a low base and reaching approximately 45 GW by 2016.
• Spain (orange line) has a moderate increase, peaking at around 25 GW.
• India (purple line) starts from almost 0 GW and grows to about 30 GW by 2016.
• United Kingdom (light blue line), France (dark blue line), and Italy (yellow line) all show growth, but at a slower pace compared to the top countries, with capacities below 20 GW by 2016.

The graph is sourced from the BP Statistical Review of Global Energy and is provided by Our World in Data. Each country's line is color-coded for easy differentiation, with a legend on the right side of the graph identifying each color with its respective country. The overall trend indicates a global increase in wind energy capacity over the years, with China leading significantly.

Credit: BP Statistical Review of Global Energy, from Our World in Data [26] (CC BY 4.0 [27])

Part of the reason for this growth is the steady decline in the cost of wind energy, as discussed in the previous section on solar energy. But government policies are another important factor. The United States has one of the most volatile markets for wind energy in the world, while those in Europe and China have been among the most stable. This is due in part to differences in how governments in these countries treat wind energy. In many parts of Europe, wind energy (and other renewable generation technologies) enjoy subsidies and incentives known as feed-in tariffs. The feed-in tariff is essentially a long-term guarantee of the ability to sell output from a specific power generation resource to the grid at a specified price (typically higher than the prices received in the market by other generation resources). The United States, on the other hand, has favored a system of tax incentives called the “Production Tax Credit” (PTC) to encourage renewable energy deployment. In theory, a tax incentive should not work much differently than a feed-in tariff (both are just payments based on how many kilowatt-hours are generated). But the PTC has historically needed to be re-authorized frequently by the US Congress – this “on-off” policy strategy has been a major factor in the volatility of wind energy investment in the US as shown in the figure below. It is worth noting that the PTC was recently renewed for 2013, but will lapse again at the end of 2019, so it is difficult to say what impact it will have on wind investment going forward.

US wind energy annual installations, showing the relationship between lapses in the Production Tax Credit (PTC) and declines in new installations.

Click here for a text description of the US wind energy annual installations graph.

The image is a bar graph titled "Annual U.S. Wind Power Installation," which shows the amount of wind power installed in the United States each year from 1998 to 2018, measured in megawatts (MW).

• The y-axis represents the installed wind power capacity in MW, ranging from 0 to 14,000 MW.
• The x-axis represents the years from 1998 to 2018.

Key points from the graph:

• From 1998 to 2004, the installation of wind power was relatively low, with figures below 2000 MW each year. There is a notable annotation "PTC lapse" pointing to the years 1999, 2000, 2001, and 2003, indicating periods where the Production Tax Credit (PTC) lapsed, leading to lower installations.
• Starting in 2005, there is a noticeable increase, with installations generally above 2000 MW, peaking around 2008-2009 with over 10,000 MW.
• Another significant peak occurs in 2012, reaching over 12,000 MW, followed by a sharp decline in 2013, again marked with a "PTC lapse" annotation.
• From 2014 to 2018, the installations fluctuate but remain relatively high, with values generally between 6,000 MW and 8,000 MW, except for another peak in 2015.

The bars are colored in shades of red, with darker shades representing higher values. The graph visually represents the impact of the PTC lapses on the annual installation of wind power, showing significant drops in those years.

Credit: David Bice, data from American Wind Energy Association (AWEA) [28]

The above clarifies that government policies are important to the growth of renewable energy production (both wind and solar). In a very real way, you can think about these policies (feed-in tariffs or tax credits) as a form of investment. Governments can also provide investments in the form of funding for basic research related to these technologies. In general, these investments do not add up to a huge amount when seen in the context of a country's gross domestic product (GDP), which is a measure of the size of the economy, as seen in the figure below.

A comparison of some leading countries in terms of the percentage of their gross domestic product (GDP) is committed to the development of renewable energy technologies.

Click here for a text description of the graph of renewable energy investment (% of GDP) for 2015.

The image is a horizontal bar chart titled "Renewable Energy Investment (% of GDP), 2015," which shows the percentage of each nation's gross domestic product (GDP) invested in renewable energy in 2015. The data source is Bloomberg New Energy Finance and the World Bank, provided by Our World in Data.

• Chile has the highest investment at 1.4% of GDP.
• South Africa also invests 1.4% of its GDP in renewable energy.
• China follows with 0.9% of GDP.
• Japan, UK, and India each invest 0.8% of their GDP.
• Brazil invests 0.4% of its GDP.
• Germany and Mexico both invest 0.3% of their GDP.
• United States has the lowest investment at 0.2% of GDP.

The bars are colored in shades of blue, with the length of each bar corresponding to the percentage of GDP invested in renewable energy. The percentages are labeled at the end of each bar for clarity. The chart visually emphasizes the variation in investment levels across different countries.

Credit: Bloomberg New Energy Finance; World Bank, from Our World in Data [26] (CC BY 4.0 [27])

The Potential Wind Energy Resource

A quick look at an annually-averaged wind map of the world (below) shows the regions of the world that are best suited for the production of wind energy in colors ranging from yellows to red (where the average winds are at least 9.75 m/s or 20 mph). The offshore regions are clearly the best in terms of the energy potential, but not all of these offshore regions are close to where people live. Even for onshore portions of the world, the wind energy potential does not always coincide with where the people are concentrated. This points to the necessity of new transmission lines to deliver this wind energy to major population centers.

The global distribution of onshore and offshore wind resources, showing the annually-averaged wind speed at a height of 100 m. For reference, the blue regions have speeds of 2.5-4 m/s (too low for good wind energy), green regions have velocities in the range of 5-6 m/ (also a bit too low for big turbines), yellow regions have speeds of 6.5 m/s (about 15 mph), which is enough to get most large modern turbines spinning, orange areas range in speed from 7-8.5 m/s, and the red areas range from 8.5 to more than 9.75 m/s, which is plenty of speed to generate wind energy at the full capacity of big turbines.

Credit: Global Wind Atlas [29], CC BY 4.0 [30]

So, just how much energy could be produced by the wind? In 2009, a group of scientists makes some calculations to estimate the potential for the world and the US, using wind data and some assumptions about the size and spacing of the turbines. They assumed 2.5 MW turbines on land, and 3.5 MW turbines offshore, which were big for that time. They assumed that you could only place the turbines in unforested, ice-free, nonmountainous areas away from any towns and that the turbines had to be spaced by several hundred meters so they do not interfere with their neighbors. They further assumed that each turbine generated just 20% of its rated capacity to account for mechanical problems and intermittent winds. What they came up with is summarized in the table below, and it is pretty remarkable. The units here are exajoules (EJ = 1 x 10¹⁸ Joules) of energy over the course of a year. For reference, in 2018, the US total energy consumption (not just electrical energy) was 106 EJ and the global consumption was about 600 EJ. So, with just onshore wind energy, the potential is more than twice what we consume in the US, and more than 4 times the global consumption. But getting there is a matter of installing a lot of wind turbines!

Now let's consider a more practical question — how much wind energy have we managed to produce, and can we somehow project the past trends into the future? The figure below shows the global history of wind energy (solar is plotted too just for comparison), and you can see that it is growing fast.

The history of wind and solar energy production for the world have both grown dramatically over the past 20 years or so. Both curves are following an exponential growth trajectory, increasing by an average of 25% per year.

Click for a text description of the Global Solar and Wind Energy Generation History graph.

The image is a line graph titled "Global Solar and Wind Energy Generation History," depicting the growth in energy generation from solar and wind sources from 1985 to 2020, measured in exajoules (EJ) per year.

• The y-axis represents the energy generated per year in EJ, ranging from 0 to 14 EJ.
• The x-axis represents the years from 1985 to 2020.

Two lines are plotted on the graph:

• Solar energy generation is represented by an orange line. It shows a very gradual increase from 1985, remaining almost flat until around 2005. After 2005, there is a noticeable uptick, with a significant rise starting around 2010, reaching approximately 7 EJ by 2020.
• Wind energy generation is represented by a green line. Similar to solar, wind energy generation starts from a low base in 1985, with minimal growth until around 2000. From 2000 onwards, there is a steep increase, particularly sharp after 2010, reaching around 12 EJ by 2020.

The graph visually demonstrates the exponential growth in both solar and wind energy generation over the years, with wind energy showing a more pronounced increase compared to solar. The data points are marked with small dots along the lines, and a legend in the center of the graph identifies the colors associated with solar (orange) and wind (green).

Credit: David Bice, data from BP Statistical Review of Energy, 2018

Both of these curves are growing exponentially, and the history so far suggests a growth of about 25% per year on average. If we assume that they continue to grow in the further following this exponential growth, we can project where we'll be at any time in the future. Below, we see where we might be in the year 2030, just eleven years from now. What you see is that we end up with vast amount of wind energy by 2030 — if it grows at the same rate it has been growing at, we end up with almost 300 EJ per year, about half of the current global energy consumption, and if it grows at a smaller rate of 20% per year, we still end up being able to supply about 20% of the total global energy demand.

The history of wind energy production for the world projected into the future, increasing by an average of 25% per year and 20% per year.

Click here for a written description of the Global wind energy generation history and projection graph.

The image is a line graph titled "Global Wind Energy Generation History and Projection," which illustrates the historical data and projected growth of global wind energy generation from 1985 to 2030, measured in exajoules (EJ) per year.

• The y-axis represents the energy generated per year in EJ, ranging from 0 to 300 EJ.
• The x-axis represents the years from 1985 to 2030.

The graph features two lines:

1. Historical Data (blue line) - This line shows the actual wind energy generation from 1985 to around 2020. The generation starts from nearly 0 EJ in 1985 and shows a gradual increase over the years, with a noticeable acceleration starting around 2005, reaching approximately 15 EJ by 2020.
2. Projections - There are two projection lines for future growth:
   • 20% per year growth (yellow line) - This projection starts from the point where the historical data ends (around 2020) and shows a steep increase, reaching about 100 EJ by 2030.25% per year growth (orange line) - This projection also starts from the end of the historical data and shows an even steeper increase, reaching around 250 EJ by 2030 

The graph visually represents the exponential growth expected in wind energy generation if the growth rates continue at 20% or 25% per year. The lines are color-coded with labels indicating the growth rates, and the overall trend suggests a significant future increase in wind energy generation.

Credit: David Bice, data from BP Statistical Review of Energy, 2018

Barriers to Additional Wind Energy Development

It is worth noting that, as with solar, wind investments are not always happening in the windiest areas. The reality is that there are a large number of factors that influence the development of wind energy globally. As the technology for wind energy has improved, other factors have also come together to create market drivers for wind power. These drivers include:

• Declining Wind Costs
• Fuel Price Uncertainty
• Federal and State Policies
• Economic Development
• Public Support
• Green Power
• Energy Security
• Carbon Risk

We have already mentioned the US Production Tax Credit, which is responsible for a good amount of the trend in US wind energy investment – both up and down! A decline in wind investment in 2010 and 2011 was due in part to the global financial crisis. A drop in natural gas/wholesale electricity prices has made some planned projects less competitive than originally expected and halted development. There has also been a slump in the overall demand for energy. Another factor that limits the growth of wind power capacity is the constraint on the transmission infrastructure. As can be seen in the wind capacity map on the previous page, many of the locations that experience the windiest conditions are not close to coastal population centers. The cost of upgrading this infrastructure is significant — perhaps $30 to $90 billion in the US by the year 2030 according to some estimates. This seems like a huge amount, but consider that our government spends about \$20 billion each year in direct subsidies to the fossil fuel industry, which would sum up to \$200 billion by the year 2030. In light of that, the upgrade cost for better transmission lines is a bargain!

Generating Electricity from Geothermal Energy

Remember how your basic steam turbine works in a power plant that uses fossil fuels: Fuel is burned to heat water in a boiler, to create steam. The steam is used to drive a turbine, which generates electricity. What if you could get all that steam without burning a single ounce of coal, oil or natural gas? That is the appeal of geothermal electricity production. In certain locations (primarily near active or recently active volcanoes) there are very hot rocks deep under the earth’s surface. In these "geothermal" regions, the temperature may rise by 40-50°C every kilometer of depth, so just 3 km, the temperature could be 120 to 150°C, well above the boiling point for water. The rocks in these regions will typically have pore spaces filled with water, and the water may still be in the form of liquid water since the pressure is so high down there (in some very hot areas, the water is actually in the form of steam trapped in the rocks). If you drill a deep well into one of these "geothermal reservoirs", the water will rise up and as it approaches the surface, the pressure decreases and it turns to steam. This steam can then be used to drive a turbine that is attached to a generator to make electricity. In some regards, this is very much like a coal or natural gas electrical plant, except that with geothermal, no fossil fuels are burned, which means no carbon emissions.

There are three basic types of geothermal power plants, depending on the type of hydrothermal reservoir:

• Dry steam plants, which draw steam directly from deep underground (a la Old Faithful);
• Flash steam plants, which draw hot water under high pressure up towards the surface. As the pressure decreases, the water boils, which generates steam to power the turbine;
• Binary steam plants, which utilize hot water (perhaps around 150 degrees Celsius) to vaporize another fluid (one with a lower boiling point). This hot vapor then drives the turbine, generating electricity.

The oldest geothermal plant (1904) in the world is Lardarello, in Italy, which is a dry steam plant. The Geysers, in California, is the largest geothermal installation in the world and the only accessible dry-steam area in the United States (other than Old Faithful and the rest of Yellowstone, which is off-limits). Most modern geothermal plants are “closed-loop” systems, which means that the water (or steam) brought up from the surface is re-injected back into the earth, as shown in the figure below. If the water is not replaced, then eventually, the geothermal reservoir will dry up and cease function.

Closed-loop system of a flash steam geothermal power plant.

Click for a text description of the Binary Cycle Power Plant diagram.

The image is a diagram titled "Binary Cycle Power Plant," illustrating the operation of a binary cycle geothermal power plant.

• Production Well: On the left side of the diagram, there is a vertical pipe labeled "Production well" which goes down into the ground through various rock layers. This well extracts hot geothermal fluid from beneath the Earth's surface.
• Heat Exchanger: The hot geothermal fluid from the production well is directed into a heat exchanger, represented by a rectangular component with internal structures suggesting heat transfer. Inside the heat exchanger, the geothermal fluid transfers its heat to a secondary working fluid without mixing with it.
• Turbine: Above the heat exchanger, there is a turbine, depicted with blades inside a cylindrical housing. The secondary working fluid, now heated, expands and turns the turbine, converting thermal energy into mechanical energy.
• Generator: Connected to the turbine is a cylindrical component labeled "Generator." The mechanical energy from the turbine is converted into electrical energy by the generator.
• Injection Well: After passing through the heat exchanger, the cooled geothermal fluid is returned to the Earth through another vertical pipe labeled "Injection well," which also goes down through the rock layers.
• Load: On the right side of the diagram, the electrical energy generated is shown being used to power a light bulb, representing the "Load" or the end use of the generated electricity.
• Flow of Fluids: The flow of the geothermal fluid is indicated by arrows, showing movement from the production well, through the heat exchanger, and back into the injection well. The flow of the secondary working fluid is shown entering the turbine.

The diagram uses simple, clear lines and labels to illustrate the process of converting geothermal heat into electricity using a binary cycle system, where the geothermal fluid and the working fluid do not mix.

Credit: Binary Cycle Power Plant [44]. The U.S. Energy Information Administration (EIA) (Public Domain).

Geothermal Potential

On a global scale, the potential for geothermal energy is quite large. The IPCC estimates that even though just a fraction of the total heat within the Earth can be used to generate geothermal power, we could nevertheless generate about 90 EJ of energy per year, and this is energy that is constantly renewed from within the Earth. Keep in mind that at present, we generate just over 2 EJ per year, so this energy source can definitely expand, but by itself it cannot meet the total global energy demand of 600 EJ.

To harness geothermal energy to generate electricity using any conventional technology (dry steam, flash steam or binary steam), you’ve got to be in the right place, where there is just the right amount of hot fluid or steam in an accessible reservoir. Unfortunately, those places are few and far between. The figure below shows a map of geothermal resources in the U.S., with identified conventional sites marked with dots on the map. All are located in just a handful of western states, plus Alaska.

Geothermal resource map of the United States. Hydrothermal sites are marked with dots on the map, while contours represent potential conventional/enhanced geothermal resources.

Click for a text description of the Geothermal resource map of the United States.

This is a geothermal resource map of the United States, showing the locations of identified hydrothermal sites and the favorability of Deep Enhanced Geothermal Systems (EGS). It illustrates where geothermal energy potential is highest in the U.S., particularly in the western states, using color gradients to indicate favorability for Enhanced Geothermal Systems (EGS). It also highlights identified hydrothermal sites where underground reservoirs exceed 90°C.

Map Key & Color Coding:

• Dark Red – Most favorable areas for deep EGS.
• Orange & Yellow Shades – Areas with decreasing geothermal favorability.
• Light Yellow – Least favorable geothermal areas.
• Gray Areas – No data available.
• Black Dots – Identified hydrothermal sites (with temperatures above 90°C).

Geothermal Distribution:

• Western U.S. (California, Nevada, Idaho, Oregon, Utah, and parts of Arizona & New Mexico) has the highest geothermal favorability.
• Eastern U.S. has limited areas with geothermal potential, except for some parts of the Appalachian region.
• Alaska contains numerous identified hydrothermal sites.

Text on the Right Side of the Image:

"Map does not include shallow EGS resources, undiscovered hydrothermal resources, or geopressured resources. EGS resource favorability is based on a combination of depth, temperature, and thermal conductivity. The analysis assumes that permeability enhancement can be achieved anywhere the necessary thermal conditions exist. Identified hydrothermal sites are those with measured or estimated reservoir temperatures greater than 90°C. This map was produced by the National Renewable Energy Laboratory for the U.S. Department of Energy, October 13, 2009. Author: Billy J. Roberts."

Credit: Geothermal Resource for the United States. National Renewable Energy Laboratory. U.S. Department of Energy [45] (DOE) (Public Domain). Accessed February 10, 2025.

Enhanced Geothermal

Most places do not have that right combination of an accessible, large reservoir of underground heat. Instead, reservoirs are more dispersed, in geologic formations with less permeability (this naturally inhibits the flow of hot fluid towards the surface). Engineers have discovered how to alter the subsurface to create man-made reservoirs of hot water that could be tapped to produce electricity, in either a flash steam or (with higher potential) a binary steam technology configuration. The process of engineering a geothermal reservoir underground is known as “enhanced geothermal systems” or EGS. As the resource map in Figure 2 shows, EGS could be done in a lot more places than conventional geothermal. Hundreds of thousands of gigawatts of power, basically enough to run the United States several times over, could potentially be harnessed through EGS.

The basic idea behind EGS is to fracture hot rocks deep within the earth to create channels or networks through which water could flow. When water is injected into these networks, the heat from the rocks boils the water directly, or the now-hot water is transported to the surface where it is used to boil a working fluid, much like a binary steam plant. Fracturing of the rock occurs via “hydraulic fracturing,” under which water is injected into the rock formation at high pressures, causing the rock to fracture. This is actually very similar to the way that natural gas and oil is being extracted from shale. So we can “frack” for geothermal in much the same way that we frack for oil and gas.

Barriers to Adoption of Geothermal Power Generation

Only a few countries use geothermal resources as a major source of electricity production –Iceland, El Salvador, and the Philippines all use geothermal for more than 25% of total electricity generation within those countries. New Zealand is the next (but distant) largest at 10%. Where hydrothermal resources are easy to access, they have often been utilized. The trouble is, there just aren’t that many Old Faithfuls in the world.

EGS represents the most significant potential for geothermal electricity production, but other than a few small military or pilot projects, the systems have not really caught on commercially. One of the big reasons is cost – like many low-carbon electricity technologies, EGS is inexpensive to run but very costly to build. Drilling geothermal wells is much more expensive than drilling conventional oil or gas wells, so electricity prices would probably need to increase by 25% or more (relative to current averages) to make EGS a financially viable technology.

Perhaps a more serious challenge for EGS is “induced seismicity,” which is a fancy term for causing earthquakes. EGS wells that were drilled below Basel, Switzerland caused over 10,000 small tremors (less than 3.5 on the Richter scale) within just a few days following the start of the hydraulic fracturing process. In Oregon, a test EGS well is being monitored for induced seismic activity – you can see some neat real-time earthquake data at Induced Seismicity [48] (U.S. Department of Energy: Energy Efficiency and Renewable Energy.

Induced seismicity occurs whenever hydraulic fracturing (related to EGS or developing a natural gas well) takes place, but in most cases, the earthquakes are so small they are not felt. However, if the hydraulic fracturing occurs near pre-existing faults (which are often not visible at the surface), then larger earthquakes can and do occur, and some of these are strong enough to cause minor damage to buildings nearby.

Conventional Hydroelectric Dams

There are three main types of conventional hydropower technologies: impoundment (dam), diversion, and pumped storage.

Impoundment is the most common type of hydroelectric power plant. An impoundment facility, typically a large hydropower system, uses a dam to store river water in a reservoir. Water released from the reservoir flows through a turbine, spinning it, which in turn activates a generator to produce electricity. Generation may be used fairly flexibly to meet baseload as well as peak load demands. The water may also be released either to meet changing electricity needs or to maintain a constant reservoir level. The layout of a typical impoundment hydropower facility is shown below in the first figure. One of the world’s most famous impoundment dams, the Hoover Dam, is shown in the second figure (although it’s worth noting that on a global scale, the Hoover Dam is more famous than it is large).

Conventional Impoundment Dam

Click for a text description of the Conventional Impoundment Dam diagram.

The image is a labeled diagram of a hydroelectric dam, illustrating how it generates electricity.

• Reservoir: At the top left of the diagram, there is a large body of water labeled as "Reservoir," which stores water at a higher elevation.
• Intake: On the left side of the dam, there is an opening labeled "Intake," where water from the reservoir is directed into the system.
• Penstock: From the intake, water flows through a large pipe called the "Penstock," which channels the water down towards the powerhouse. This pipe is shown running through the dam structure.
• Powerhouse: Inside the dam, there is a structure labeled "Powerhouse," where the main components for electricity generation are housed.
• Turbine: Within the powerhouse, there is a "Turbine" depicted. The water from the penstock is directed to spin this turbine.
• Generator: Above the turbine, there is a "Generator," which is connected to the turbine. The mechanical energy from the spinning turbine is converted into electrical energy by the generator.
• River: At the bottom right of the diagram, there is a body of water labeled "River," into which the water exits after passing through the turbine.
• Long Distance Power Lines: Extending from the powerhouse, there are lines labeled "Long Distance Power Lines," which carry the generated electricity away from the dam to distant locations. These lines are shown leading to a structure that looks like a power distribution station.

The diagram uses simple, clear lines and labels to show the flow of water from the reservoir through the intake and penstock, into the turbine within the powerhouse, and then out to the river. It also illustrates how the mechanical energy from the water's movement is converted into electrical energy by the generator, which is then transmitted via power lines.

Credit: Hydroelectric Dam [49] by Tennessee Valley Authority from Wikimedia Commons (Public Domain [50]). Accessed Feb. 25, 2025.

Hoover Dam

Credit: Hoover Dam from air [51] by LICKO from Wikimedia (Public Domain). Accessed Feb. 25, 2025.

A diversion, sometimes called run-of-river, facility channels a portion of a river through a canal or penstock. It may not require the use of a dam but also has limited flexibility to follow peak variation in power demand. Thus, it will mainly be useful for baseload capacity. This scenario results in limited flooding and changes to river flow. In the United States, many of the dams in the Pacific Northwest (on the Columbia and Snake Rivers) are diversion or run-of-river dams, with limited or no storage reservoir behind the dam. The figure below shows a picture of a diversion hydropower facility. Compare what that facility looks like with the picture of Hoover Dam, the impoundment facility shown above.

Diversion or “run-of-river” dam

Credit: Tazimina Dam [52]. The National Oceanic and Atmospheric Administration (NOAA) (Public Domain [53]).

A “pumped storage” hydro dam combines a small storage reservoir with a system for cycling water back into the reservoir after it has been released through the turbine, thus “re-using” the same water to generate electricity at a later time. When the demand for electricity is low (typically at night), a pumped storage facility stores energy by pumping water from a lower reservoir to an upper reservoir. During periods of high electrical demand (typically during the day), the water is released back to the lower reservoir to generate electricity. The figure below shows a schematic of a pumped storage hydro facility. Pumped storage facilities are typically smaller in terms of generation capacity than their impoundment or diversion counterparts, but are sometimes combined with impoundment or diversion facilities to increase peak power output or flexibility.

Schematic of a pumped-storage hydro facility

Click for a text description of the pumped-storage hydro facility diagram.

The image is a cross-sectional diagram of a "Pumped-Storage Plant," illustrating the various components and the overall operation of the facility.

• Reservoir: At the top right of the diagram, there is a large body of water labeled "Reservoir," which is at a higher elevation.
• Intake: Water from the reservoir is directed into the system through an opening labeled "Intake."
• Switchyard: To the far right, above the reservoir, there is a structure labeled "Switchyard," which is involved in the distribution of electricity.
• Visitors Center: Near the top of the diagram, there is a building labeled "Visitors Center," located on the surface above the main infrastructure.
• Elevator: A vertical line labeled "Elevator" runs from the surface down to the underground sections, providing access between levels.
• Main Access Tunnel: A horizontal tunnel labeled "Main Access Tunnel" extends from the base of the elevator, leading to various underground chambers.
• Surge Chamber: Connected to the main access tunnel is a vertical structure labeled "Surge Chamber," which helps manage water pressure fluctuations.
• Powerplant Chamber: Below the surge chamber, there is a large room labeled "Powerplant Chamber," where the main machinery for generating electricity is housed.
• Breakers: Adjacent to the powerplant chamber, there is a section labeled "Breakers," which are electrical switches used to control, protect, and isolate electrical equipment.
• Transformer Vault: Below the breakers, there is another section labeled "Transformer Vault," where transformers are located to step up or step down voltage levels for efficient power transmission.
• Discharge: At the bottom left of the diagram, there is an area labeled "Discharge," where water exits after passing through the powerplant, flowing back into a lower body of water or river.

The diagram uses color coding (blue for water flow, brown for earth) and clear labels to show the path of water from the reservoir through the intake, down through the system, and how it's used to generate electricity in the powerplant chamber before being discharged. The various components are interconnected, illustrating the flow of water and electricity in a pumped-storage hydroelectric facility.

Credit: Raccoon Mountain Pumped-storage Plant [54]by Tennessee Valley Authority from Wikipedia (Public Domain). Accessed Feb. 25, 2025.

Wave and Tidal Energy

Water in the oceans is constantly in motion due to waves and tides, and energy can be harvested from these kinds of motions. Waves, driven by the winds, make the water oscillate in roughly circular orbits extending to a depth of one half of the wavelength of the wave (distance between peaks). Tides, related to the gravitational pull of the Moon and Sun on the oceans, are like very long-wavelength waves that can produce very strong currents in some coastal areas due to the geometry of the shoreline. In terms of power generation technologies, wave and tidal power have both similarities and differences. Both refer to the extraction of kinetic energy from the ocean to generate electricity (again, by spinning a turbine just as hydroelectric dams or wind farms do), but the locations of each and the mechanisms that they use for generating power are slightly different.

Wave energy projects extract energy from waves on the surface of the water, or from wave motion a bit deeper (a few 10s of meters) in the ocean. Surface wave energy technologies capture the kinetic energy in breaking waves – these provide periodic impulses that spin a turbine. The US Department of Energy [55] has a nice description of different types of surface wave projects as follows:

• Oscillating Water Columns: Oscillating water columns consist of a partially submerged concrete or steel structure that has an opening to the sea below the waterline. It encloses a column of air above a column of water. As waves enter the air column, they cause the water column to rise and fall. This alternately compresses and depressurizes the air column. As the wave retreats, the air is drawn back through the turbine as a result of the reduced air pressure on the ocean side of the turbine.
• Tapchans: Tapchans, or tapered channel systems, consist of a tapered channel that feeds into a reservoir constructed on cliffs above sea level. The narrowing of the channel causes the waves to increase in height as they move toward the cliff face. The waves spill over the walls of the channel into the reservoir, and the stored water is then fed through a turbine.
• Pendular Devices: Pendular wave-power devices consist of a rectangular box that is open to the sea at one end. A flap is hinged over the opening, and the action of the waves causes the flap to swing back and forth. The motion powers a hydraulic pump and a generator.

Offshore wave energy systems are typically placed deeper in the ocean, though not too deep – perhaps a few hundred feet below the ocean’s surface. The periodic wave activity at this depth is typically used to power a pump that feeds into a turbine, generating electricity.

Tidal energy projects typically work by forcing water through a turbine or a “tidal fence” that looks like a set of subway turnstiles. The systems depend on regular tidal activity to generate power. Because this tidal activity is predictable (each coast sees at least one tidal cycle per day – high tide and low tide – and some areas actually see two tidal cycles on a daily basis), tidal energy projects have the advantage of being able to provide a fairly predictable source of electricity. The use of tidal power, globally, has been quite limited because there are only a few sites in the world that see sufficiently large variations in tides to produce enough power, as shown in the table below.

In-River Hydro-kinetics

When rivers are utilized to produce electricity, that is usually accomplished by building some sort of hydroelectric dam, like the three we discussed earlier. It doesn’t have to be that way, however. Many of the technologies used to extract energy from the tides (or similar technologies) could be deployed in freshwater river systems rather than the saltwater ocean, effectively acting as very small run-of-river facilities. These “hydrokinetic” power generation systems are typically individually small (each generating about 100 kilowatts or less of power) and could be situated in two ways. First, a propeller-like or turnstile-like turbine could be deployed directly into the riverway, operating much like a small-scale tidal power system. Second, a “micro-hydro” type of system could be employed, where river water is channeled to a turbine housing via a channel or pipeline, as shown in the figure below.

Schematic for a Micro-Hydro System

Click for a text description of the Schematic for a Micro-Hydro System.

The image is a diagram illustrating the components of a run-of-the-river hydroelectric power system set in a hilly landscape.

• Intake: At the top right of the diagram, there is a structure labeled "Intake" located in a river, where water is diverted from the natural flow.
• Canal: From the intake, water is channeled through a man-made waterway labeled "Canal," which runs along the contour of the land.
• Forebay: The canal leads to a wider section labeled "Forebay," which serves as a small reservoir or settling basin to regulate water flow before it enters the penstock.
• Penstock: Water from the forebay is then directed into a large pipe labeled "Penstock," which slopes downward, carrying water under pressure to the power station.
• Powerhouse: At the bottom left of the diagram, there is a building labeled "Powerhouse," where the penstock delivers water to turbines. This is where the conversion of water energy into electrical energy occurs.
• River: The natural river continues to flow beside the canal and penstock, with the powerhouse situated near the riverbank. The river is depicted winding through the landscape, with some water being diverted for power generation.
• Landscape: The background includes hills and trees, indicating a natural setting. There's also a small house near the river, suggesting human habitation in the vicinity.

The diagram uses simple lines and labels to show the flow of water from the river through the intake, canal, forebay, and penstock to the powerhouse, illustrating how run-of-the-river hydroelectric systems work by utilizing the natural flow of the river with minimal storage.

Credit: Microhydropower System Components [56]. The United States Department of Energy (DOE) (Public Domain).

Global Use of Hydroelectricity

Globally, hydroelectricity is a major electricity resource, accounting for more than 16% of all electricity produced on the planet. More electricity is produced globally using hydropower than from plants fueled by nuclear fission or petroleum (natural gas and coal do produce more electricity globally than hydropower does). More than 150 countries produce some hydroelectricity, although around 50% of all hydropower is produced by just four countries: China, Brazil, Canada, and the United States. China is by far the largest hydropower producer on the planet, as shown in the figure below. Hydroelectricity production in China has tripled over the past decade, with the completion of some of the world’s largest dam projects, in particular, the Three Gorges Dam (the world’s largest), which could produce nearly enough electricity to power all of New England during a typical summer and left an area roughly the size of San Francisco flooded underwater.

Global hydroelectric power generation in 2011

Click the link to expand for a text description of the Hydroelectric Generation by Country, 2011 Pie Chart

The image is a pie chart titled "Hydroelectric Generation by Country, 2011 (Billion Kilowatt-hours)," which shows the distribution of hydroelectric power generation across different countries for the year 2011. The total hydroelectric generation is 3,496 billion kilowatt-hours.

• China is the largest contributor, represented by the biggest slice of the pie chart, generating 694 billion kilowatt-hours.
• Brazil follows, with a slice showing 430 billion kilowatt-hours.
• Canada is next, depicted with a slice for 377 billion kilowatt-hours.
• United States has a slice for 328 billion kilowatt-hours.
• Russia is shown with 165 billion kilowatt-hours.
• India has a slice for 132 billion kilowatt-hours.
• Norway is represented with 122 billion kilowatt-hours.
• Japan has a smaller slice for 85 billion kilowatt-hours.
• Venezuela is shown with 64 billion kilowatt-hours.
• Sweden has the smallest individual country slice, with 66 billion kilowatt-hours.

There is also a large section labeled Other, which collectively represents 1,016 billion kilowatt-hours from countries not individually listed.

Each country's contribution is color-coded in the pie chart for visual distinction, with labels indicating the amount in billion kilowatt-hours. The source of the data is BP, and it is provided by the Earth Policy Institute. The total generation figure is prominently displayed at the bottom right of the chart.

Data source is BP Statistical Review of World Energy. Image is from Earth Policy Institute.

Once hydroelectric dams are built, they run very cheaply and generally provide reliable supplies of electricity except during times of extreme drought. Developed countries that have substantial hydro resources have, by and large, already utilized those resources to produce electricity. In these countries, hydropower dominates the electricity supply system as shown in the chart below. Norway leads the pack here – the amount of hydropower that it produces is not large in an absolute sense (it is the world’s seventh-largest producer) but nearly all electricity generated in Norway comes from hydro-power. Brazil and Canada are also highly dependent on hydropower. Other large hydro producers, such as China and the United States, produce much less hydroelectricity relative to the size of their overall power sectors.

Share of hydro-power among the top ten hydro-producing countries

Click link to expand for a text description of Hydro-power graph

The image is a horizontal bar chart titled "Share of Electricity from Hydropower in Top Generating Countries, 2011." It displays the percentage of electricity generated from hydropower in various countries for the year 2011. The data source is the Earth Policy Institute (EPI) from BP.

• Norway has the highest share, with a bar extending to nearly 100%, indicating almost all of its electricity comes from hydropower.
• Brazil follows, with a bar reaching approximately 80%.
• Venezuela is next, with a share around 70%.
• Canada has a bar showing about 60%.
• Sweden shows a share of roughly 50%.
• Russia has a bar extending to about 20%.
• China is depicted with a bar at around 15%.
• India has a share of about 12%.
• Japan shows a bar at approximately 8%.
• United States has the lowest share among the listed countries, with a bar extending to about 7%.

Each country is listed on the y-axis, with corresponding bars extending horizontally to the right to represent the percentage on the x-axis, which ranges from 0 to 100%. The bars are colored in blue for visual distinction. The source of the data is noted at the bottom right of the chart.

Data source is BP Statistical Review of World Energy. Image is from Earth Policy Institute.

Hydroelectric Potential

It is often said that developed countries like the United States have little potential for growth in hydroelectric power generation – the US, in particular, has dammed so many rivers, that what could possibly be left? In some areas of the Pacific Northwest, the US is removing some dams that produce electricity due to environmental concerns. It is certainly the case that there is relatively little potential for new hydro mega-projects in the US. This does not mean, however, that there is nowhere left to build new hydroelectric projects. There are, in fact, several hundred megawatts of planned hydroelectric generation in the Mid-Atlantic US alone (see the map at PJM [57]) [58], though most of the projects would be small pumped storage facilities) We’ll walk briefly through a few examples of the hydro resource potential in the United States before taking a more global look.

First, not all dams in the US are equipped with turbines to generate electricity. There are, actually, quite a few that aren’t (see the interactive map at Energy.gov [59] – potentially enough power generation to supply more than ten million homes. Many of these are located along major shipping routes, like the Ohio and Mississippi Rivers. Others are located in areas where development might not make economic sense because the power would need to be shipped across large and expensive transmission lines. Another unconventional technology – hydro-kinetics – could potentially supply enough electricity to power the state of Virginia, although these resources are highly concentrated in the Lower Mississippi River and in more remote areas such as Alaska.

Globally, the picture is very different. Developing nations with abundant hydro resources, like China, Brazil, and other South American countries, are rushing headlong into planning and building new dams. So globally, hydroelectricity is alive and well, and growing rapidly (no pun intended) – although this growth comes in fits and starts since new dams each represent a big chunk of capacity and take a long time from project start to finish. Nearly half of the world’s fifteen largest dams were built since the year 2000, with only one of those in a country other than China or Brazil (the Sayano Shuskenskaya dam in Russia was recently upgraded, although the original went into place in the 1980s).

Energy from hydropower has been growing at a steady annual rate of 0.3 EJ per year since the year 2000, faster than the previous decades, but overall, hydro still accounts for just 16 EJ of the total 580 EJ we used in 2018. Some estimates suggest that if we really developed all of the economically viable hydroelectric sites, we might be able to generate as much as 50 EJ of hydroelectric energy — still a far cry from the +600 we will need in the near future. But even though hydro cannot solve all of our energy problems, it is nevertheless very important in that it supplies a relatively low-emissions, dispatchable (on-demand) energy source that can help smooth out the variability in wind and solar energy production.

Challenges to Further Hydroelectric Deployment

While hydro development is still growing in several regions of the world, many countries, including the United States, will not likely pursue larger hydro projects due to two main factors — first, we have already built hydroelectric dams in most of the best places, and secondly, there are concerns over the environmental and societal impacts of building more dams. These environmental impacts have even been used to justify dam removal in some cases, though weighing those environmental impacts against the societal benefits (such as irrigation, flood control, recreation, and so forth…not just electricity) has always been controversial. Some of these specific environmental and societal impacts include:

• Impacts on fish migration – fish migrating up or downstream may find passages blocked by dams or may get killed going through turbines.
• Reduced water quality – changes in natural stream-flow may, in some cases, muddy waters. This affects the river ecosystems that aquatic plants and animals utilize.
• Land inundation – reservoirs behind dams can flood large areas. There is not necessarily a relationship between the size of the dam and the amount of area flooded behind the dam. Two impacts can arise here. First, building large hydro projects often involves the displacement of many people who used to live in the area surrounding the river. The Three Gorges Dam in China involved the relocation of more than one million people.
• Methane release to the atmosphere — plant life can decay in flooded areas, which over time releases large quantities of methane into the atmosphere – enough that it can potentially offset the avoided CO₂ emissions from many years worth of fossil fuel use. A recent estimate places the global emissions of methane high enough to make hydropower be just a little bit less than natural gas in terms of CO2 (equivalent) per unit of energy generated.

How Nuclear Energy Works

Maggie Koerth-Baker has a really great article on how nuclear power plants work, with a focus on the nuclear fission reaction and what mechanisms in a nuclear power plant keep the reaction from spinning out of control. It was written right after the incident at Fukushima Daichi. Before continuing on, please have a look at the article, and pay some attention not only to how plants work, but how the nuclear reactions inside the plants are controlled. The article also has a really nice description of how reactions at nuclear power plants can keep cascading even after the plant has been “shut down,” which is basically what causes meltdowns like those that happened in the Three Mile Island and Chernobyl power plants.

The basics of a nuclear power plant aren’t actually all that complicated. In fact, there is a remarkable similarity to fossil fuel plants, in that what ultimately happens in a nuclear power plant is that steam is produced, to drive a turbine inside a generator, which produces electricity. But unlike fossil fuel plants, which heat water by burning fuel, the water in nuclear power plants is heated through an atomic reaction.

There are two basic types of atomic reactions. The first is nuclear fusion, with which we are all intimately familiar, whether we know it or not. It is nuclear fusion that keeps the sun hot. In nuclear fusion, atoms are joined together. The word “joined” here is a bit of scientific jargon. In reality, the energy is released when atoms collide together at really high speeds. If you have ever seen two cars collide at high speed, you have some idea of how energy could be released when things hit each other. Despite years of research into nuclear fusion, scientists have never been able to engineer a controllable reaction in a laboratory environment. If they could, most of the world’s energy problems would basically be solved overnight, since the amount of energy released through a fusion reaction would be massive. But for now, fusion goes in the “maybe someday” pile.

The second type of nuclear reaction is fission, which is the opposite of fusion – atoms are broken apart, which also releases energy. U-235 is naturally radioactive, meaning that the nucleus is unstable, and it will eventually give off some energy and parts of its nucleus to get to a stable atom, but this takes a long time — the half-life is 700 million years.  The figure below illustrates roughly how this works. An atom (in the case of a nuclear power plant, a uranium-235 atom) is bombarded with neutrons, some of which are absorbed by the nucleus, so the U-235 becomes U-236 — this makes it even more unstable, so the atom splits apart into two lighter atoms called the daughter products.  U-236 splits into krypton (Kr-92) and barium (Ba-141), and it also releases energy in the form of heat, gamma radiation (bad for us) and 3 neutrons. (Note that if you add up the weight of the daughter products and the neutrons,  92+141+3, you get 236, the weight of the U-236 that split apart).  These neutrons come hurtling out of the original atom and smash into other uranium-235 atoms, triggering 3 more U-235 fission reactions, each of which generates 3 more neutrons.  As you can see, before long, there are a lot of neutrons and thus a lot of reactions and thus a lot of heat, which heat the water surrounding the fuel rods, creating steam, spinning the turbine — just like many of the other systems for making electricity.

The nuclear fission reaction described above is an example of a positive feedback mechanism that will naturally tend to speed up until all of the fuel (the U-235) is used up.  This means that it has a tendency to create more and more heat, and if left unchecked, this would cause the water in the reactor vessel to get too hot and build up too much pressure for the reactor to contain — then you would have a big steam explosion, such as happened at Chernobyl.  To control this reaction, the reactor core has a series of control rods, made of materials that absorb the neutrons emitted during a fission reaction.  So the control rods allow the operators to adjust the rate of the reaction and thus the rate of heat production.

Fission of 235-U is induced by bombardment of neutrons.  The fission reaction produces heat, radiation, daughter products, and more neotrons that induce additional fission reactions.

Click for a text description of Induced Fission Reaction diagram

The image is a diagram illustrating the nuclear fission process of Uranium-235 (U-235) leading to the production of energy in the form of heat and radiation.

• Uranium-235 (235-U): At the top left, there is a yellow circle labeled "235-U," representing Uranium-235.
• Uranium-236 (236-U): An arrow from 235-U leads to an orange star-like shape labeled "236-U," indicating Uranium-236, which is an intermediate excited state formed when Uranium-235 absorbs a neutron.
• Fission Products: From 236-U, the diagram shows two main arrows splitting off:
  • One arrow leads to a purple star labeled "92-Kr," representing Krypton-92.
  • The other arrow leads to a blue star labeled "141-Ba," representing Barium-141.
• Heat and Radiation: Between the fission products, there is a large yellow starburst labeled "heat and radiation," indicating that the fission process releases energy in the form of heat and radiation.
• Additional Neutrons: Small blue circles at the ends of additional arrows coming from the heat and radiation starburst represent neutrons that are also produced during the fission process.

The diagram uses color coding and shapes to visually represent the transformation of Uranium-235 into Uranium-236, followed by its fission into Krypton-92 and Barium-141, along with the release of heat, radiation, and additional neutrons.

Source: David Bice

Pressurized Water Reactor.

Click for a text description of the Pressurized Water Reactor.

The image is a schematic diagram of a nuclear power plant, illustrating the main components and the flow of energy and fluids within the system. Here is a detailed description of each part:

• Containment Structure: The entire setup is enclosed within a large grey structure labeled "Containment Structure," which provides safety and containment for the nuclear reactions.
• Reactor Vessel: On the left side within the containment structure, there is a red and yellow structure labeled "Reactor Vessel." This is where nuclear fission occurs, generating heat.
• Control Rods: Inside the reactor vessel, there are grey rods labeled "Control Rods," which are used to control the rate of the nuclear reaction by absorbing neutrons.
• Pressurizer: Above the reactor vessel, there is a yellow component labeled "Pressurizer," which maintains the necessary pressure in the reactor coolant system to prevent boiling at operational temperatures.
• Steam Generator: Connected to the reactor vessel by red and blue pipes, there is a light blue structure labeled "Steam Generator." Here, heat from the reactor vessel is transferred to water in a secondary loop, turning it into steam.
• Turbine: To the right of the steam generator, there is a green component labeled "Turbine." The steam generated in the steam generator expands and spins this turbine, converting thermal energy into mechanical energy.
• Generator: Attached to the turbine, there is a grey cylindrical component labeled "Generator." The mechanical energy from the turbine is converted into electrical energy here.
• Condenser: Below the turbine, there is a blue structure labeled "Condenser," where the steam is cooled and condensed back into water after passing through the turbine.
• Flow of Fluids: The diagram shows the flow of water and steam with arrows:
  • Red arrows indicate hot water or steam moving from the reactor vessel to the steam generator.
  • Blue arrows show the flow of cooler water from the condenser back to the steam generator and reactor vessel 
• City and Power Lines: In the background, there is a silhouette of a city skyline, indicating the end use of the generated electricity. Power lines extend from the generator to a power transmission tower, symbolizing the distribution of electricity to the city.

The diagram uses color coding to differentiate between hot and cold components (red for hot, blue for cold), and simple shapes to represent each part of the nuclear power plant's operation, showing the energy conversion process from nuclear to electrical energy.

Credit: Public Domain. See Wikipedia Pressurized Water Reactor [60]

Boiling Water Reactor.

Click for a text description of the Boiling Water Reactor.

The image is a labeled diagram of a nuclear power plant, showing the main components and the flow of various fluids and electricity within the system. Here is a detailed description of each labeled part:

1. Reactor Vessel - This is a large cylindrical container at the left side of the diagram, colored in red at the top and blue at the bottom, representing the containment vessel for the nuclear reaction.
2. Fuel Assembly Element - Inside the reactor vessel, there are red vertical structures labeled as fuel assembly elements where the nuclear fission occurs.
3. Control Rod Element - Also inside the reactor vessel, there are grey rods labeled as control rod elements, used to control the rate of the nuclear reaction.
4. Circulation Pumps - At the bottom of the reactor vessel, there are small grey structures labeled as circulation pumps, which help circulate coolant within the reactor.
5. Control Rod Motors - Below the circulation pumps, there are small grey components labeled as control rod motors, which move the control rods in and out of the reactor core.
6. Steam - A red pipe labeled "steam" exits from the top of the reactor vessel, indicating the steam produced from the heat of the nuclear reaction.
7. Inlet Circulation Water - A blue pipe labeled "inlet circulation water" enters the reactor vessel, representing the water that cools the reactor and turns into steam.
8. High Pressure Turbine - The steam from the reactor vessel flows into a green component labeled as the high pressure turbine, where the steam's energy is converted into mechanical energy.
9. Low Pressure Turbine - After the high pressure turbine, the steam moves into a larger purple component labeled as the low pressure turbine, continuing the conversion of steam energy into mechanical energy.
10. Electric Generator - Connected to the turbines, there is a yellow component labeled "electric generator," which converts the mechanical energy from the turbines into electrical energy.
11. Electrical Generator - Another electric generator is shown in yellow, connected to the low pressure turbine, indicating the generation of electricity.
12. Steam Condenser - Below the turbines, there is a grey structure labeled "steam condenser," where the steam is cooled and condensed back into water.
13. Cold Water - A blue pipe labeled "cold water" leads from the condenser to a body of water outside the plant, indicating the cooling water source.
14. Pre-water for Condenser - A blue pipe labeled "pre-water for condenser" shows water being directed towards the condenser.
15. Water Circulation Pump - Connected to the pre-water for condenser, there is a grey component labeled "water circulation pump," which helps circulate water through the condenser.
16. Condenser Cold Water Pump - Another pump, labeled "condenser cold water pump," is shown in grey, which pumps cold water into the condenser.
17. Concrete Chamber - The entire setup is housed within a large grey structure labeled "concrete chamber," providing containment and protection.
18. Connection to Electricity Grid - On the right side, there is a grey line labeled "connection to electricity grid," showing where the generated electricity is sent out for distribution.

The diagram uses color coding (red for steam, blue for water, green and purple for turbines, yellow for generators, and grey for various structural and mechanical components) to illustrate the flow of steam, water, and electricity through the nuclear power plant's system. Arrows indicate the direction of flow for steam, water, and electricity.

Source: Robert Steffens (alias RobbyBer 8 November 2004), SVG: Marlus_Gancher, Antonsusi (talk) using a file from Marlus_Gancher. See File talk: Schema Siedewasserreaktor.svg#License history GFDL [61] via Wikimedia Commons [62]

There are two basic types of nuclear power plants that are in operation today. The first, and most common, is the Pressurized Water Reactor (PWR), which is illustrated in the animation below. In a PWR, hot water passes through the reactor core (where it absorbs the heat from the nuclear fission reactions) and is then pumped through a heat exchanger, where it heats another fluid that produces steam, powering the turbine. The primary advantage to this type of design is that the water in the primary loop (which passes through the core) does not actually come into contact with the fluid in the steam generator, so unless pipes or valves break there is no risk of contamination or radioactive water leaking from the plant. The Boiling Water Reactor (BWR), illustrated in the next figure, utilizes a somewhat simpler design, where the water that runs through the core is allowed to vaporize to steam, thus powering the turbine to generate electricity. While the design is simpler, it does mean that the steam entering the turbine can be radioactive.

Whether one design is inherently more advantageous than another is difficult to say. Both types have been involved in major nuclear power plant incidents. The reactor at Three Mile Island was a PWR while the reactor at Fukushima was a BWR, so the potential exists for problems at either type of plant. It is perhaps worth mentioning that the Three Mile Island incident was likely due as much to human error and poor design of the reactor’s control system at least as much as to the reactor design itself. The reactor at Chernobyl was an unusual Soviet design called a “light water graphite reactor” that was not really designed for use as a commercial nuclear power plant but was adapted for that use anyway. The World Nuclear Association [63] has a nice description of the Chernobyl plant technology with a description of what went wrong (here too, human error played a central role).

Advanced PWRs have been developed that use more passive designs to keep the reactor from overheating, without any pumps or offsite power required. Westinghouse has developed one such design, the AP1000, which is currently being deployed in China. For those who are interested, more information on passive PWR designs can be found at Westinghouse Nuclear [64].

The Nuclear Fuel Cycle

Nuclear fuel rods typically last for 3-5 years, and when a rod is "spent" it still contains some fissionable 235-U along with a host of other radioactive elements. So, what do we do with these spent rods? Many people would argue that recycling is a good thing. In the nuclear energy industry, recycling of spent nuclear fuel is a somewhat contentious topic. Many countries, including those European countries that still use nuclear energy, recycle spent fuel into new fuel for re-use. The United States does not do this, preferring a "once-through" fuel cycle for reasons of security as well as economics. Understanding the pros and cons of recycling nuclear fuel requires some understanding of how fuel for nuclear power plants is mined and fabricated.

Nuclear Fuel Cycle.

Click for a text description of the Nuclear Fuel Cycle diagram.

The image is a circular flowchart illustrating the nuclear fuel cycle, showing the various stages from uranium extraction to electricity generation and waste management. Each stage is represented by a blue arrow pointing to the next, forming a continuous loop. Here is a detailed description of each stage:

1. Mining: The first stage, located at the bottom left, shows an image of a mining operation where uranium ore is extracted from the earth.
2. Milling: Moving clockwise, the next stage is milling, depicted with an image of a milling facility where the uranium ore is processed into uranium oxide (yellowcake).
3. Conversion: Following milling, the conversion stage is shown with an image of industrial equipment, representing the process where uranium oxide is converted into uranium hexafluoride gas.
4. Enrichment: The enrichment stage, illustrated with an image of centrifuges, involves increasing the concentration of the uranium-235 isotope in the uranium hexafluoride gas.
5. Fuel Fabrication: Next, fuel fabrication is depicted with an image of fuel rods being assembled, where enriched uranium is formed into fuel rods for use in reactors.
6. Power Plant: This stage shows an image of a nuclear power plant, where the fuel rods are used to generate heat through nuclear fission, which then produces steam to drive turbines.
7. Electricity Generation: Following the power plant, electricity generation is illustrated with an image of power lines and a city skyline, indicating the distribution of electricity generated from the nuclear power.
8. Spent Fuel Storage: After electricity generation, spent fuel storage is shown with an image of storage casks, where used nuclear fuel is temporarily stored.
9. Reprocessing: Moving back into the cycle, reprocessing is depicted with an image of a facility where spent fuel can be treated to extract usable materials and reduce waste.
10. High Level Waste Storage: This stage, shown with an image of a storage facility, deals with the storage of high-level radioactive waste that results from reprocessing.
11. Final Disposal: The final disposal stage is illustrated with an image of a deep geological repository, where high-level waste is permanently disposed of.
12. Recycle: The cycle can loop back to the enrichment stage if the materials from reprocessing are recycled into new fuel, indicated by an arrow pointing back to "Enrichment."

Additionally, there is a note indicating "FOR NATURAL URANIUM FUELS" between the conversion and enrichment stages, suggesting this part of the cycle applies specifically to natural uranium fuel processing.

The flowchart uses images to visually represent each stage, with arrows indicating the progression and potential recycling within the cycle.

Source: International Atomic Energy Agency

The figure above outlines the many steps necessary to get uranium out of the ground and into a nuclear power plant. After extraction and processing (“milling”), uranium ore is transported to conversion facilities to remove impurities. The next step in the nuclear fuel cycle is enrichment. Owing to security concerns, all enrichment for the US commercial nuclear industry takes place at one government-owned gas diffusion facility in Paducah, Kentucky. Enriched uranium is then transported to one of several commercial fuel fabrication facilities where the fuel rods are manufactured. In the U.S., fuel fabrication is a competitive industry; private firms compete to provide finished fuel to nuclear power plants. Nuclear fuel rods are generally not purchased directly from the government. Nuclear fission and disposal of spent fuel rods constitute the final steps of the nuclear fuel cycle in the US

The US is heavily dependent on the global market for uranium and nuclear fuel. n 2017, 90% of uranium oxide supplies used to develop nuclear fuel in the US come from outside of the country. The main suppliers for the US are Canada (24%), Kazahkstan (20%), Australia (18%), and Russia (13%). Proposals to open new uranium mines in both the western and eastern United States have been met with resistance, primarily on environmental grounds.

Current US policy prohibits the reprocessing of spent nuclear fuel, for two primary reasons. First is economics – the fuel costs for nuclear power plants are already among the lowest of any non-renewable power generation resource. Once nuclear power plants are built, if they are well-run they cost very little to operate. While the recycling of spent nuclear fuel would eliminate the need for virgin uranium ore to be mined or for additional fuel to be purchased on the world market, it is not at all clear whether the benefits of doing so outweigh the costs of reprocessing. The other reason is nuclear security. The process of recycling nuclear fuel involves the separation of uranium and plutonium from the spent fuel rods. There have been concerns regarding plutonium falling into the wrong hands and contributing to the proliferation of nuclear weapons.

One very serious concern with nuclear power has to do with the highly radioactive waste from the process. Much of the waste needs to be isolated for at least 10,000 years. All civilian nuclear waste was intended to be stored permanently at a repository in Yucca Mountain, Nevada. Yucca Mountain was chosen as a waste repository site back in 1987 and we have spent over $15 billion investigating the site and developing 65 km of tunnels deep underground to store the waste. Currently, it could hold 65,000 tons of waste, but we have 94,000 tons of radioactive waste in temporary storage at nuclear plants. The Yucca Mountain facility is not currently operational and significant uncertainties exist as to whether it will ever be used. In the interim, spent nuclear waste will continue to be stored on-site at the power plants.

Global Use of Nuclear Energy

There are currently several hundred operating nuclear power plants in the world, spread over a few dozen countries, with over a hundred more “proposed” nuclear power plants (these may or may not get built, depending on economic and political factors in the relevant countries). The US still has the largest number of plants, with about 100 currently operating. France’s economy is the most dependent on nuclear energy, with more than 75% of electricity in that country coming from nuclear power plants. Countries with fleets of nuclear power are primarily wealthier nations, such as the US and European countries, but developing nations are really the biggest growth area, particularly China. Prior to the Fukushima incident, other Asian nations besides China had plans to grow their nuclear fleets, but whether that growth will materialize is highly uncertain. In response to concerns regarding the safety of nuclear power plants and waste disposal/management issues, some European countries have enacted various policies mandating the phase-out of nuclear energy, including Austria, Sweden, Germany, Italy, and Belgium. Other countries, including Spain and Switzerland, have imposed a moratorium on the construction of new nuclear power plants. Of the countries that have decided to phase out nuclear energy, Germany has been among the most aggressive following the Fukushima incident. Because of concerns over electricity supply and costs, however, some countries have delayed or back-stepped on plans to phase out nuclear energy.

Review of Energy Units

Before going ahead, we need to make sure we all have a clear picture of the various units we use to measure energy.

Joule — the joule (J) is the basic unit of energy, work done, or heat in the SI system of units; it is defined as the amount of energy, or work done, in applying a force of one Newton over a distance of one meter. One way to think of this is as the energy needed to lift a small apple (about 100 g) one meter. An average person gives off about 60 J per second in the form of heat. We are going to be talking about very large amounts of energy, so we need to know about some terms that are used to describe larger sums of energy:

In recent years, we humans have consumed about 518 EJ of energy per year, which is something like 74 GJ per person per year.

British Thermal Unit— the btu is another unit of energy that you might run into. One btu is the amount of energy needed to warm one pound of water one °F. One btu is equal to about 1055 joules of energy. Oddly, some branches of our government still use the btu as a measure of energy.

Watt— the watt (W) is a measure of power and is closely related to the Joule; it is the rate of energy flow, or joules/second. For instance, a 40 W light bulb uses 40 joules of energy per second, and the average sunlight on the surface of Earth delivers 343 W over every square meter of the surface.

Kilowatt hours— when you (or you parents maybe for now) pay the electric bill each month, you get charged according to how much energy you used, and they express this in the form of kilowatt hours — kWh. If you use 1000 Watts for one hour, then you have used one kWh. This is really a unit of energy, not power:

$$\text{1[kWh]=1000[W]}\times \text{1[hr]=1000}\left[\frac{J}{s}\right]\times \text{3600[s]=3,600,000[J]}$$

In other words, one kilowatt hour is 1000 joules per second (kW) summed up over one hour (3600 seconds), which is the same as 3.6 MJ or 3.6 x 10⁶J or 3.6e6 J.

Global Energy Sources

The energy we use to support the whole range of human activities comes from a variety of sources, but as you all know, fossil fuels (coal, oil, and natural gas) currently provide the majority of our energy on a global basis, supplying about 81% of the energy we use:

Figure 1. The current contributions to our global energy from different sources shows that fossil fuels account for 81% of our energy. Data from International Energy Agency (iea.org)

Click for a text description of the Sources of Global Energy chart.

The image is a pie chart titled "Sources of Global Energy," showing the distribution of different energy sources globally. The chart is divided into segments, each representing a different energy source with corresponding percentages:

• Oil: The largest segment, colored in blue, represents 33% of global energy sources.
• Coal: The second largest segment, colored in red, accounts for 27% of global energy.
• Gas: Represented by a green segment, gas makes up 21% of the energy mix.
• Solar, Wind, Other: This segment is yellow and constitutes 11% of the energy sources.
• Hydro: A light blue segment representing 2% of global energy.
• Nuclear: The smallest segment, colored in purple, accounts for 6% of the energy sources.

Each segment is labeled with the energy source and its percentage, providing a clear breakdown of the global energy composition.

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

The non-fossil fuel sources include nuclear, hydro (dams with electrical turbines attached to the outflow), solar (both photovoltaic and solar thermal), and a variety of other sources. These non-fossil fuel sources currently supply about 19% of the total energy.

The percentages of our energy provided by these different sources have clearly changed over time and will certainly change in the future as well. The graph below gives us some sense of how dramatically things have changed over the past 210 years:

Figure 2. This plot shows the history of global energy production from different sources. Note that as time goes on, we are getting our energy from more sources. Data from Smil (2010).

Click for a text description of the Global Energy Consumption by Source graph.

The image is a line graph titled "Global Energy Consumption by Source," showing the consumption of various energy sources from the year 1800 to 2000. The y-axis represents energy consumption in exajoules (EJ), ranging from 0 to 160 EJ. The x-axis represents the years, marked at intervals from 1800 to 2000.

The graph includes data for five different energy sources, each represented by a different colored line:

• Biofuels: Represented by a light blue line, biofuel consumption starts at around 10 EJ in 1800 and shows a slight increase over time, peaking around 20 EJ by 2000.
• Coal: Represented by a red line, coal consumption starts near 0 EJ in 1800, begins to rise significantly around 1850, and continues to increase sharply, reaching approximately 120 EJ by 2000.
• Crude Oil: Represented by a green line, crude oil consumption starts near 0 EJ in 1850, increases steadily from around 1900, and rises sharply post-1950, reaching about 140 EJ by 2000.
• Natural Gas: Represented by a purple line, natural gas consumption starts near 0 EJ in 1900, with a notable increase starting around 1950, reaching around 100 EJ by 2000.
• Hydro Electricity: Represented by a dark blue line, hydroelectricity consumption starts near 0 EJ around 1900, with a gradual increase over time, reaching about 30 EJ by 2000.
• Nuclear Electricity: Represented by an orange line, nuclear electricity consumption starts near 0 EJ around 1950, with a sharp increase from that point, reaching around 30 EJ by 2000.

Key observations:

• Coal and crude oil show the most significant increases in consumption over the period.
• Natural gas consumption also rises sharply, particularly after 1950.
• Biofuels show a relatively flat trend, with a minor increase.
• Hydro and nuclear electricity consumption start later, but show steady growth over time.
• By 2000, crude oil has the highest consumption, followed by coal, natural gas, hydroelectricity, nuclear electricity, and biofuels in that order.

A legend in the top-left corner of the graph identifies the colors associated with each energy source.

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

There are a couple of interesting features to point out about this graph. For one, note that the total amount of energy consumed has risen dramatically over time — this is undoubtedly related to both population growth and the industrial revolution. The second point is that shifting from one energy source to another takes a long time. Oil was being pumped out of the ground in 1860, and even though it has a greater energy density and is more versatile than coal, it did not really make its mark as an energy source until about 1920, and it did not surpass coal as an energy source until about 1940. Of course, you might argue that the world changed more slowly back then, but it is probably hard to avoid the conclusion that our energy supply system has a lot of inertia, resulting in sluggish change.

Global Energy Uses

We are all aware of some of the ways we use energy — heating and cooling our homes, transporting ourselves via car, bus, train, or plane — but there are many other uses of energy that we tend not to think about. For instance, growing food and getting it onto your plate uses energy — think of the farming equipment, the food processing plant, the transportation to your local store. Or, think of manufactured items — to make something like a car requires energy to extract the raw materials from the earth and then assembling them requires a great deal of energy. So, when you consider all of the different uses of energy, we see a dominance of industrial uses:

Figure 3. Most of our energy is used in industrial applications, mainly in the form of electricity. We are generally the most aware of our use of energy in transportation because we pay for it on a regular basis. Data from International Energy Agency (iea.org)

Click for a text description of the Global Energy End Use chart.

The image is a pie chart titled "Global Energy End Use," showing the distribution of global energy consumption across different sectors. The chart is divided into four segments, each representing a different sector with corresponding percentages:

• Industry: The largest segment, colored in blue, represents 52% of global energy end use.
• Transport: The second largest segment, colored in red, accounts for 26% of the energy consumption.
• Residential: Represented by a purple segment, this sector uses 14% of the global energy.
• Commercial: The smallest segment, colored in green, constitutes 8% of the energy end use.

Each segment is labeled with the sector name and its percentage, providing a clear breakdown of how global energy is utilized across these sectors.

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

Global Energy Consumption

Since we are going to be modeling the future of global energy consumption, we should first familiarize ourselves with the recent history of energy consumption.

Figure 4. This plot shows the history of global energy production from different sources. Note that as time goes on, we are getting our energy from more sources. Data from Smil (2010).

Click for a text description of the History of Global Energy Consumption graph.

The image is a stacked area chart titled "History of Global Energy Consumption," showing the consumption of various energy sources from 1800 to 2000. The y-axis represents energy consumption in exajoules (EJ), ranging from 0 to 500 EJ. The x-axis represents the years, marked at intervals from 1800 to 2000.

The chart includes data for six different energy sources, each represented by a different colored area:

• Biofuels: Represented by a red area at the bottom of the stack, biofuel consumption starts at around 10 EJ in 1800 and shows a gradual increase, peaking around 50 EJ by 2000.
• Coal: Represented by a green area above biofuels, coal consumption starts near 0 EJ in 1800, begins to rise significantly around 1850, and continues to increase sharply, reaching approximately 150 EJ by 2000.
• Crude Oil: Represented by a yellow area above coal, crude oil consumption starts near 0 EJ around 1880, with a notable increase starting around 1900, reaching about 150 EJ by 2000.
• Natural Gas: Represented by a light blue area above crude oil, natural gas consumption starts near 0 EJ around 1900, with a sharp increase post-1950, reaching around 100 EJ by 2000.
• Hydro Electricity: Represented by an orange area above natural gas, hydro electricity consumption starts near 0 EJ around 1900, with a steady increase over time, reaching about 30 EJ by 2000.
• Nuclear Electricity: Represented by a dark blue area at the top, nuclear electricity consumption starts near 0 EJ around 1950, with a rapid increase from that point, reaching around 30 EJ by 2000.

Key observations:

• The total energy consumption shows a steep rise starting around the mid-20th century.
• Coal and crude oil have the largest contributions to the total energy consumption, especially from the late 19th century onwards.
• Natural gas becomes significant post-1950.
• Hydro and nuclear electricity start later but show steady growth.
• Biofuels have a consistent but smaller share throughout the period.

A legend on the right side of the chart identifies the colors associated with each energy source.

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

Question: Why has our energy consumption increased over this time period?

Here, we will explore a few possibilities, the first of which is global population increase — more people on the planet leads to a greater total energy consumption. To evaluate this, we need to plot the global population and the total energy consumption on the same graph to see if the rise in population matches the rise in energy consumption.

Figure 5. Data from Smil (2010), and UN (population).

Click for a text description of the Energy Consumption and Population graph.

The image is a line graph titled "Energy Consumption and Population," showing the relationship between global energy consumption and global population from the year 1800 to 2000.

• Axes:
  • The x-axis represents the years, ranging from 1800 to 2000.
  • The left y-axis represents energy consumption in exajoules (EJ), ranging from 0 to 500 EJ.
  • The right y-axis represents population in billions, ranging from 0.800 to 6.800 billion


• Data Series:
  • Energy Consumption: Represented by blue squares connected by a line, this series shows the trend of global energy consumption over time. It starts at a low level around 10 EJ in 1800 and increases steadily, with a significant rise starting around 1950, reaching approximately 450 EJ by 2000.
  • Population: Represented by red circles connected by a line, this series shows the trend of global population growth. It starts at around 1 billion in 1800 and grows gradually, with a sharp increase post-1950, reaching about 6.8 billion by 2000
• Trends:
  • Both energy consumption and population show a similar trend of gradual increase until around 1950, after which both exhibit exponential growth.
  • The correlation between the two trends is evident, with both lines rising sharply in the latter half of the 20th century, indicating a strong relationship between population growth and energy consumption


• Key Points:
  • Around 1800, energy consumption is very low, and the population is just above 1 billion.
  • By 1900, energy consumption has risen to about 30 EJ, and the population has grown to approximately 1.6 billion.
  • Post-1950, there is a dramatic increase in both metrics, with energy consumption reaching nearly 450 EJ and the population reaching 6.8 billion by 2000

The graph uses two different scales to represent energy consumption and population, with the right y-axis for population being in billions and the left y-axis for energy consumption being in exajoules. The visual representation highlights the parallel growth of these two variables over the 200-year period.

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

The two curves match very closely, suggesting that population increase is certainly one of the main reasons for the rise in energy consumption. But is it as simple as that — more people equals more energy consumption?

If the rise in global energy consumption is due entirely to population increase, then there should be a constant amount of energy consumed per person — this is called the per capita energy consumption. To get the per capita energy consumption, we just need to divide the total energy by the population (in billions) — so we’ll end up with Exajoules of energy per billion people.

Figure 6. The globally averaged per capita energy consumption, broken down by energy source. Data from Smil (2010), and UN (population).

Click for a text description of the History of Per Capita Energy Consumption graph.

The image is a stacked area chart titled "History of Per Capita Energy Consumption," showing the consumption of various energy sources per capita from 1800 to 2000. The y-axis represents energy consumption in exajoules per billion people, ranging from 0 to 80 EJ per billion. The x-axis represents the years, marked at intervals from 1800 to 2000.

The chart includes data for six different energy sources, each represented by a different colored area:

• Biofuels: Represented by a red area at the bottom of the stack, biofuel consumption starts at around 10 EJ per billion in 1800 and shows a gradual increase, peaking around 20 EJ per billion by the mid-20th century before declining slightly towards 2000.
• Coal: Represented by a green area above biofuels, coal consumption starts near 0 EJ per billion in 1800, begins to rise significantly around 1850, and continues to increase, reaching a peak of about 30 EJ per billion around 1950, then declines slightly but remains significant.
• Crude Oil: Represented by a purple area above coal, crude oil consumption starts near 0 EJ per billion around 1880, with a notable increase starting around 1900, reaching about 30 EJ per billion by 1970, then slightly decreases.
• Natural Gas: Represented by a light blue area above crude oil, natural gas consumption starts near 0 EJ per billion around 1900, with a sharp increase post-1950, reaching around 20 EJ per billion by 2000.
• Hydro: Represented by an orange area above natural gas, hydro energy consumption starts near 0 EJ per billion around 1900, with a steady increase over time, reaching about 10 EJ per billion by 2000.
• Nuclear Electricity: Represented by a dark blue area at the top, nuclear electricity consumption starts near 0 EJ per billion around 1950, with a rapid increase from that point, reaching around 10 EJ per billion by 2000.

Key observations:

• The total per capita energy consumption shows a steady increase from 1800, with a significant rise starting around the mid-20th century.
• Coal and crude oil have significant contributions to per capita energy consumption, especially from the late 19th century onwards.
• Natural gas becomes a major contributor post-1950.
• Hydro and nuclear electricity start later but show steady growth, becoming more prominent towards the end of the 20th century.
• Biofuels have a consistent but decreasing share towards the end of the period.

A legend on the right side of the chart identifies the colors associated with each energy source.

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

Today, we use about 3 times as much energy per person than in 1900, which is not such a surprise if you consider that we have many more sources of energy available to us now compared to 1900. Note that at the same time that the population really takes off (see Fig. 5), the per capita energy consumption also begins to rise. This means that the total global energy consumption rises due to both the population and the demand per person for more energy.

Let’s try to understand this per capita energy consumption a bit better. We know that the global average is 74 EJ per billion people, but how does this value change from place to place? There are some huge variations across the globe — Afghans use about 4 GJ per person per year, while Icelanders use 709 GJ per person. Why does it vary so much? Is it due to the level of economic development, or the availability of energy, or the culture, or the climate? You can come up with reasons why each of these factors (and others) might be important, but let’s examine one in more detail — the economic development expressed as the GDP (the gross domestic product, which reflects the size of the economy) per capita.

Figure 7. The per capita energy as a function of the per capita GDP. The axes of this plot are not linear, but logarithmic in order to show more clearly what is going on at the lower values. If you plot this with linear axes, the data mostly form a big cloud in the lower left. The red squares show the global averages in 2013 and about 1950. Data World Bank.

Click for a text description of Relationship Between GDP and Energy Consumption.

The image is a scatter plot graph titled "Relationship Between GDP and Energy Consumption." It illustrates the relationship between per capita GDP (in $) on the x-axis and per capita energy consumption (in GJ/person) on the y-axis for various countries over time. The graph uses a logarithmic scale for both axes.

• Axes:
  • The x-axis is labeled "Per Capita GDP $" and ranges from 1,000 to 100,000.
  • The y-axis is labeled "Per Capita Energy Consumption (GJ/person)" and ranges from 1 to 1,000.
• Data Points:
  • Each data point represents a country, with blue circles indicating data from various years.
  • Specific countries are highlighted with labels:
    • Afghanistan is located at the lower left of the graph, indicating low GDP and low energy consumption.
    • Mexico is positioned towards the middle of the graph.
    • USA is located towards the upper right, indicating higher GDP and energy consumption.
    • Qatar and Iceland are at the far right, with very high GDP and energy consumption, with Iceland having the highest energy consumption
  • Global Averages:
    • Two red squares mark the global averages:
      • One labeled "Global Average 1950" is located lower on the graph, indicating lower GDP and energy consumption.
      • Another labeled "Global Average 2013" is positioned higher, showing an increase in both GDP and energy consumption over time.
    • Trends:
      • There is a general upward trend, suggesting that as per capita GDP increases, so does per capita energy consumption.
      • The spread of data points widens as GDP increases, indicating variability in energy consumption among countries with similar GDP levels.
    • Annotations:
      • Arrows point to the labeled countries and global averages, providing a visual guide to their positions on the graph.

      The graph uses a logarithmic scale to accommodate the wide range of values, and the data points are densely packed, showing the distribution and relationship between GDP and energy consumption across different countries.

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

The obvious linear trend to these data suggests that per capita energy consumption is a function of GDP, while the fact that it is not a tight line tells us that GDP is not the whole story in terms of explaining the differences in energy consumption. Not surprisingly, we are near the upper right of this plot, consuming more than 300 GJ per person per year. Iceland’s economy is not as big per person as ours, and yet they consume vast amounts of energy per person, partly because it is cold and they have big heating demands, but also because they have abundant, inexpensive geothermal energy thanks to the fact that they live on a huge volcano. Many European countries with strong economies (e.g., Germany) use far less energy per person than we do (168 GJ compared to our 301 GJ), in part because they are more efficient than us and in part because they are smaller, which cuts down on their transportation. A big part of the reason they are more efficient than us is that energy costs more over there — for instance, a gallon of gas in Italy is about $8. Our neighbor, Mexico, has a per capita energy consumption that is just about the global average.

Pay attention to the two red squares in Fig. 7 — these show the global averages in terms of GDP and energy consumption per person for two points in time. The trend is most definitely towards increasing GDP (meaning increasing economic development) and increasing energy consumption per person. Economic development is definitely a good thing because it is tied to all sorts of indicators of a higher quality of life — better education, better health care, better diet, increased life expectancy, and lower birth rates. But, economic growth has historically come with higher energy consumption, and that means higher carbon emissions.

Now that we’ve seen what some of the patterns and trends are, we are ready to think about the future.

Creating an Emissions Scenario

There are many ways to meet our energy demands for the future, and each way could include different choices about how much of each energy source we will need. We’re going to refer to these “ways” as scenarios — hypothetical descriptions of our energy future. Each scenario could also include assumptions about how the population will change, how the economy will grow, how much effort we put into developing new technologies and conservation strategies. Each scenario can be used to generate a history of emissions of CO₂, and then we can plug that into a climate model to see the consequences of each scenario.

Emissions per unit energy for different sources

The global emission of carbon into the atmosphere due to human activities is dominated by the combustion of fossil fuels in the generation of energy, but the various energy sources — coal, oil, and gas — emit different amounts of CO₂ per unit of energy generated. Coal releases the most CO₂per unit of energy generated during combustion — about 103.7 g CO₂per MJ (10⁶ J) of energy. Oil follows with 65.7 g CO₂/MJ, and gas is the “cleanest” or most efficient of these, releasing about 62.2 g CO₂/MJ.

At first, you might think that renewable or non-fossil fuel sources of energy will not generate any carbon emissions, but in reality, there are some emissions related to obtaining our energy from these means. For example, a nuclear power plant requires huge quantities of cement, the production of which releases CO₂ into the atmosphere. The manufacture of solar panels requires energy as well, and so there are emissions related to that process because our current industrial world gets most of its energy from fossil fuels. For these energy sources, the emissions per unit of energy are generally estimated using a lifetime approach — if you emitted 1000 g of CO₂ to make a solar panel and over its lifetime, it generated 500 MJ, then its emission rate is 2 g CO₂/MJ. If we average these non-fossil fuel sources together, they release about 5 g CO₂/MJ — far cleaner than the other energy sources, but not perfectly clean.

So, to sum it up, here is a ranking of the emissions related to different energy sources:

*Hydro, Nuclear, Wind, Solar

**This will decrease as the non-fossil fuel fraction increases

Calculating global emissions of carbon

Our recent energy consumption is about 518 EJ (10¹⁸ J). Let’s calculate the emissions of CO₂ caused by this energy consumption, given the values for CO₂/MJ given above and the current proportions of energy sources — 33% oil, 27% coal, 21% gas, and 19% other non-fossil fuel sources. The way to do this is to first figure out how many grams of CO₂ are emitted per MJ given this mix of fuel sources, and then scale up from 1 MJ to 518 EJ. Let’s look at an example of how to do the math here — let r_1-4 in the equation below be the rates of CO₂ emission per MJ given above, and let f_1-4 be the fractions of different fuels given above. So r₁ could be the rate for oil (65.7) and f₁ would be the fraction of oil (.33). You can get the composite rate from:

$$r_c=r_1{f}_1+r_2{f}_2+r_3{f}_3+r_4{f}_4$$

Plugging in the numbers, we get:

$$65.7\times .33+62.2\times .27+103.7\times .21+6.2\times .19=61.4\left[\frac{{\mathrm{gCo}}_2}{\mathrm{MJ}}\right]$$

What is the total amount of CO₂ emitted? We want the answer to be in Gigatons — that’s a billion tons, and in the metric system, one ton is 1000 kg (1e6 g or 10⁶ g), which means that 1Gt = 10¹⁵ g (1e15 g).

$$1[\mathrm{EJ}]=1\mathrm{e}12[\mathrm{MJ}],\text{so},518[\mathrm{EJ}]=518\mathrm{e}12[\mathrm{MJ}]$$

$$518\mathrm{e}12[\mathrm{MJ}]\times 61.4\left[\frac{{\mathrm{gCO}}_2}{\mathrm{MJ}}\right]=31.7\mathrm{e}15\left[{\mathrm{gCO}}_2\right]=31.8$$

So, the result is 31.8 Gt of CO₂, which is very close to recent estimates for global emissions.

It is more common to see the emissions expressed as Gt of just C, not CO₂, and we can easily convert the above by multiplying it by the atomic weight of carbon divided by the molecular weight of CO₂, as follows:

$$31.8\left[{\mathrm{GtCO}}_2\right]\times \frac{12[\mathrm{gC}]}{44\left[{\mathrm{gCO}}_2\right]}=8.7[\mathrm{GtC}]$$

And remember that this is the annual rate of emission.

Let’s quickly review what went into this calculation. We started with the annual global energy consumption at the present, which we can think of as being the product of the global population times the per capita energy consumption. Then we calculated the amount of CO₂ emitted per MJ of energy, based on different fractions of coal, oil, gas, and non-fossil energy sources — this is the emissions rate. Multiplying the emissions rate times the total energy consumed then gives us the global emissions of either CO₂ or just C.

We now see what is required to create an emissions scenario:

1. A projection of global population
2. A projection of the per capita energy demand
3. A projection of the fractions of our energy provided by different sources
4. Emissions rates for the various energy sources

In this list, the first three are variables — the 4^th is just a matter of chemistry. So, the first three constitute the three principal controls on carbon emissions.

Here is a diagram of a simple model that will allow us to set up emissions scenarios for the future:

Figure 8. Stella model of the emissions' calculation part of the model. This looks more complex than it really is due to the addition of 10 converters that enable the user to change the fraction of energy coming from different sources. The key result from this model is Total Emissions, in Gt C per year, which then controls the flow of carbon into the atmosphere of the global carbon cycle part of the model (see Figure 9).

Click for a text description of Figure 8.

The image is a complex systems diagram titled "System Dynamics Model of Energy Consumption and Emissions," which illustrates the relationships and feedback loops between various factors related to energy consumption, population, and emissions. Here's a detailed breakdown:

Components:

1. Population: Represented by a rectangular box labeled "Population," which has arrows indicating influence from and to other components.
2. Pop Limit: A cloud-shaped symbol labeled "Pop Limit" with an arrow pointing to the "Population" box, indicating a limit or constraint on population growth.
3. net change: An arrow labeled "net change" connects from "Population" to a circular node, indicating the net change in population affecting other variables.
4. r: A circular node labeled "r" connected to "Population," representing the growth rate of the population.
5. per capita energy: Connected to "Population" with an arrow, indicating per capita energy consumption.
6. global energy consumption: A circular node connected to "per capita energy," representing the total global energy consumption.
7. Total Emissions: A rectangular box connected to "global energy consumption," representing the total emissions resulting from energy consumption.
8. RC: A central circular node labeled "RC," which seems to be a key regulatory or control factor influencing various energy sources.

Energy Sources and Emissions:

• f_gas: Connected to "RC," representing emissions from gas.
• f_oil: Connected to "RC," representing emissions from oil.
• f_coal: Connected to "RC," representing emissions from coal.
• er_gas: Connected to "f_gas," representing the energy ratio or efficiency for gas.
• er_oil: Connected to "f_oil," representing the energy ratio or efficiency for oil.
• er_coal: Connected to "f_coal," representing the energy ratio or efficiency for coal.
• er_renew: Connected to "RC," representing the energy ratio or efficiency for renewable energy.
• f_renew: Connected to "er_renew," representing emissions from renewable energy sources.

Switches and Reductions:

• Gas Switch: A diamond-shaped decision node connected to "f_gas," "f_change 3," and "gas red time," indicating a decision point for switching to or from gas.
• Oil Switch: Similar to Gas Switch, connected to "f_oil," "f_change 2," and "oil red time," for oil.
• Coal Switch: Connected to "f_coal," "f_change 1," and "coal red time," for coal.
• gas red time: Connected to "Gas Switch," indicating the time frame for gas reduction.
• f_gas reduction: An arrow from "Gas Switch" indicating the reduction in gas emissions.
• oil red time: Connected to "Oil Switch," indicating the time frame for oil reduction.
• f_oil reduction: An arrow from "Oil Switch" indicating the reduction in oil emissions.
• coal red time: Connected to "Coal Switch," indicating the time frame for coal reduction.
• f_coal reduction: An arrow from "Coal Switch" indicating the reduction in coal emissions.

Feeddack Loops:

• f_change 1, f_change 2, f_change 3: These nodes are connected to the respective switches (Coal, Oil, Gas) and "star," indicating changes or feedback loops affecting the energy mix over time.
• star: A central node labeled "star" with a value of 0.1, connected to "f_change 1," "f_change 2," and "f_change 3," possibly representing a rate of change or a multiplier effect in the system.

Connections:

• Arrows with labels like "er_gas," "er_oil," "er_coal," "er_renew" indicate the flow of influence from energy efficiency ratios to emissions.
• The diagram shows a network of interconnections where changes in one part of the system can influence others, particularly through the "RC" node, which seems to be a regulatory center affecting all energy sources and their emissions.

This diagram visualizes how population growth, energy consumption per capita, and the choice of energy sources (gas, oil, coal, renewable) interact to influence total emissions, with various feedback loops and decision points affecting the dynamics over time.

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

In this model, the per capita energy (a graph that you can change) is multiplied by the Population to give the global energy consumption, which is then multiplied by RC (the composite emissions rate) to give Total Emissions. Just as we saw in the sample calculation above, RC is a function of the fractions and emissions rates for the various sources. Note that the non-fossil fuel energy sources (nuclear, solar, wind, hydro, geothermal, etc.) are all lumped into a category called renew, because they are mostly renewable. The model includes a set of additional converters (circles) that allow you to change the proportional contributions from the different energy sources during the model run.

This emissions model is actually part of a much larger model that includes a global carbon cycle model and a climate model. Here is how it works — the Total Emissions transfers carbon from a reservoir called Fossil Fuels that represents all the Gigatons of carbon stored in oil, gas, and coal (they add up to 5000 Gt) into the atmosphere. Some of the carbon stays in the atmosphere, but the majority of it goes into plants, soil, and the oceans, cycling around between the reservoirs indicated below. The amount of carbon that stays in the atmosphere then determines the greenhouse forcing that affects the global temperature — you’ve already seen the climate model part of this. The carbon cycle part of the model is complicated, but it is a good one in the sense that if we plug in the known historical record of carbon emissions, it gives us the known historical CO₂ concentrations of the atmosphere. Here is a highly schematic version of the model:

Figure 9. Highly simplified sketch of the global carbon cycle part of the model. The global carbon cycle is essentially a set of interconnected reservoirs. Humans are affecting this cycle (red arrows), preventing it from finding a steady state. The fossil fuel burning flow (on right side above) is controlled by the part of the model that calculates the emissions.

Click for a text description of Figure 9.

The image is a flowchart diagram illustrating the global carbon cycle, showing the movement and storage of carbon in various parts of the Earth's system. Units are provided in gigatons of carbon (GT), where one gigaton equals one billion metric tons or 101510^{15}1015 grams. The diagram uses different colors to represent various carbon reservoirs and arrows to indicate the flow of carbon between these reservoirs. Red arrows indicate flows that are sensitive to human activities, while green arrows represent flows that are sensitive to temperature.

Carbon Reservoirs:

• Atmosphere: Contains 750 GT of carbon. It is connected to other parts of the cycle via various processes.
• Land Biota: Contains 610 GT of carbon, involved in processes like photosynthesis and respiration.
• Soil: Contains 1580 GT of carbon, connected to land biota through litter fall.
• Surface Oceans: Contains 970 GT of carbon, involved in ocean-atmosphere diffusion and upwelling & downwelling.
• Deep Oceans: Contains 38,000 GT of carbon, connected to surface oceans through upwelling & downwelling.
• Ocean Biota: Contains 3 GT of carbon, connected to surface oceans.
• Sedimentary Rocks: Contains 1,000,000 GT of carbon, connected to the deep oceans through sedimentation.
• Fossil Fuels: Contains 5000 GT of carbon, influencing the atmosphere through fossil fuel burning.
• Mantle: Connected to sedimentary rocks through subduction.

Carbon Flows (in GT/year):

• Atmosphere to Land Biota:
  • Photosynthesis: 110 GT/year (green arrow, temperature sensitive)
  • Burning: 50 GT/year (red arrow, human activity sensitive)
• Land Biota to Atmosphere:
  • Respiration: 59.4 GT/year (green arrow, temperature sensitive)
  • Burning/Farming: 50 GT/year (red arrow, human activity sensitive)
• Land Biota to Soil: Litter fall: 60 GT/year
• Soil to Atmosphere: Respiration: 60 GT/year (green arrow, temperature sensitive)
• Atmosphere to Surface Oceans: Ocean-atmosphere diffusion: 90 GT/year (green arrow, temperature sensitive)
• Surface Oceans to Atmosphere: Ocean-atmosphere diffusion: 90 GT/year (green arrow, temperature sensitive)
• Surface Oceans to Deep Oceans: Upwelling & downwelling: 105.6 GT/year
• Deep Oceans to Surface Oceans: Upwelling & downwelling: 96.2 GT/year
• Surface Oceans to Ocean Biota: 105 GT/year
• Ocean Biota to Surface Oceans: 105 GT/year
• Deep Oceans to Sedimentary Rocks: Sedimentation: 0.6 GT/year
• Sedimentary Rocks to Mantle: Subduction: 0.6 GT/year
• Fossil Fuels to Atmosphere: Fossil Fuel Burning: 9 GT/year (red arrow, human activity sensitive)
• Volcanic Eruptions: 0.6 GT/year from the mantle to the atmosphere (green arrow, temperature sensitive)

Notes:

• Numbers next to the arrows represent approximate annual flows in gigatons per year (GT/year).
• The diagram highlights the interaction between natural processes and human-induced changes in the carbon cycle, emphasizing the impact of activities like burning fossil fuels and land use changes (farming, burning).

Credit: David Bice @ Penn State is licensed under CC-BY-NC-4.0

Experiments with the Model

Important Instructions

1. In this exercise, we will work with a model of a system that has many parts — carbon cycle, climate model, population model, and energy model. We'll explore how making changes to one part of this system alter the behavior of other parts of the system. This illustrates an important part of what we call Systems Thinking, which is that in complex, connected systems, a change in one part may have consequences that spread throughout the system.
2. After watching the movie above, run the model [90]without making any changes to establish what we will call the “control” case for these experiments. You can return to this control case by hitting the Restore All Devices button.
3. Write down the Total Emissions at the year 2100 — this will be our comparison point in time for later experiments.Look at page 2 of the graph pad, which shows human emissions, which is essentially the same as Total Emissions except that it is limited by the total amount of fossil fuel carbon we have; if we burn through all that carbon, human emissions will drop to 0, and in fact, you’ll see that it drops off to zero about the year 2165 — this is when we run out of fossil fuels. So if we haven’t solved our energy problems by then, we’re in deep trouble!

The table above gives you a set of instructions related to the practice and graded versions of the summative assessment, including which switch to turn on, the fractional reduction, and the time over which this reduction takes place. As one of the fossil fuel sources is reduced, the model increases the renewable fraction so that the total of all the fractions stays at 1.0.

1. How much does switching from one of the fossil fuel sources to renewables decrease the emissions in the year 2100? First, run the model as is when you open it (all switches are in the off position) and take note of the total emissions for the year 2100 on graph #1 (this is our control case), then make the changes prescribed in the table above and find the new emissions in the year 2100 and then calculate the difference from the control case.

Difference = (±2 Gt)

Practice Answer = 11.3

2. Does this change lead to a leveling off of emissions, or do they continue to climb?

1. Levels off
2. Continues to climb [correct answer for practice version]

3. Which has a bigger impact in reducing emissions — limiting population growth to 10 billion, or reducing your fossil fuel fractions as prescribed? Here, make sure all the switches are turned off, and then set the Pop Limit to 10.

1. Population limitation
2. Fossil fuel reduction [correct answer for practice version]

Reset the Pop Limit to 12 when you are done with this one.

4. How much does reducing all of the fossil fuel sources to a fraction of 0.05 decrease the emissions in the year 2100 compared to the control case (set all switches to the off position for the control)? Set the start time to 2020, then turn on all the switches, and set the f reductions so that each fossil fuel source ends up at 0.05 after 30 years. You can check to make sure you’ve done this correctly by looking at the fractions on page 4 of the graph pad.

Set all of the reduction times to 20 years. For the graded version, lower the fossil fuel sources to a fraction of 0.1; leave everything else the same as the practice version.

Difference = (±2 Gt)

Practice Answer = 23.8

Follow these steps:

1. Run the control case (don’t make any changes to the model)
2. Turn on all the switches
3. Set all the reduction times to 20
4. Set f coal reduction to 0.22; f oil reduction to 0.28; f gas reduction to 0.16
5. Run the model again — you should now see a blue curve from the control run and a pink curve from the modified run (looking at graph #1)
6. Run the cursor along the control case curve until you get to the year 2100 and write down the total emissions at that point — it should be 29.57 (the units are Gt C/yr).
7. Run the cursor along the modified case curve (pink one) until you get to the year 2100 and write down the total emissions at that point — it should be 5.74.
8. The question is asking for the difference in emissions, so subtract 5.74 from 29.57 and you get 23.83 Gt C/yr — this is the reduction in emissions we would achieve if we lowered all of the fossil fuels to just 5% of our total energy consumption.

5. Which has the bigger impact in reducing emissions — halting the rise in per capita energy use, or reducing our fossil fuel fractions? For this one, you’ll use your answer to the above question (#4) and compare to one in which you turn off all the switches, and then change the per capita energy graph so that it is more or less a straight line all the way across. You can check to see how well you’ve done this by looking at page 8 of the graph pad after you run the model. So, which has a bigger impact in reducing emissions?

This table refers to the question below — it provides a set of model settings that lead to stabilization of emissions.

Refer to the worksheet to see what your per capita energy graphs should look like for the practice and graded versions.

6. One of the main goals people mention in the context of future global warming is halting the growth of our emissions of CO₂. As you have seen so far, there are a variety of ways to reduce that growth. Now, let’s see what happens when we stabilize emissions. Modify the original model to create the emissions scenario defined by the parameters supplied in the table above — this should result in an emissions history that more or less stabilizes. Then find the emissions in the year 2100.

Total Emissions in 2100 = ±2.0 Gt C/yr

Practice version — 11.3 Gt C/yr

7. Now that you have an emissions scenario that stabilizes (the human emissions of carbon remain more or less constant over most of the time), let’s look at temperature (page 9 of the graph pad). Remember that global temperature change in this model is the warming relative to the pre-industrial world, which is already about 1°C in 2010, the starting time for our model. What is the global temperature change in the year 2100?

Global temperature change = ±0.5 °C

Practice version — 2.6°C

8. Now study the temperature change (graph#9) and the pCO2 atm (the atmospheric concentration of CO₂ in ppm or parts per million — page 10 of the graph pad) for the time period following the stabilization of emissions. Does the stabilization of emissions lead to a stabilization of temperature or atmospheric CO₂ concentration?

1. Fossil fuel reduction [correct answer for practice version]
2. Per capita energy change (i.e., conservation + efficiency)

Reset the model before going to the next question.

9. Now, let’s say we want to keep the warming to less than 2°C, which the IPCC recently decided was a good target — warming more than that will result in damages that would be difficult to manage (we would survive, but it might not be pretty). We have seen by now that it is simply not enough to stabilize emissions at a level similar to or greater than today’s — that leads to continued warming. So we need to reduce emissions relative to our present level, which will be hard with a growing population and economy (and thus a growing per capita energy demand).

So, let’s see what is necessary to stay under that 2° limit, given some constraints. In all cases, we’ll assume that we can get our oil and gas fractions down to 0.1 (i.e., 10% each) over a time period of 30 years with a start time of 2020. We’ll leave population out of it (keep the limit at 12 billion), and for the practice version, we’ll make the assumption that per capita energy demand remains constant at a level of 75 for the whole time period (modify the graph so that it is a horizontal line at a level of 75 on the y-axis). This leaves f coal reduction as our main variable. The time period for reducing coal will be 30 years. You can change four scenarios for coal reduction as follows:

A: Keep the coal fraction unchanged (switch off)

B: Reduce the coal fraction to 10% (so f coal reduction would be .17)

C: Reduce the coal fraction to 5% (set f coal reduction to .22)

D: Reduce the coal fraction to 0% (set f coal reduction to .27)

For the graded version, we will change the per capita energy demand graph so that it drops to 50 by the year 2086 (see worksheet for a picture of what the graph should look like).

Find the coal fraction that keeps the temperature closest to 2°C by the year 2200.

Coal reduction scenario (A,B,C, or D):

Practice version: D is the correct answer

We’re done with this model for now, but you will be coming back to something similar to this later on when you do your capstone projects. You’ll use the model to design an emissions and energy consumption scenario for the future for which you’ll also explore the environmental and economic consequences.

The following questions encourage you to step back and think about what you’ve learned here. Short answers will suffice here.

10. What are the three principal variables that determine how much carbon is emitted from our production of energy? (Hint: look at page 11 of this worksheet)

11. What is the relationship between economic development (growth) and per capita energy consumption? (Hint: look at figure 7 of this worksheet)

12. Among the various sources of our energy, which has the highest rate of CO₂ emitted per unit of energy? (Hint: look at table on page 10 of this worksheet)

13. What happens to the atmospheric concentration of CO₂, and thus the global temperature, if we stabilize (hold constant) the emissions rate? (refer to question #8 above)

14. Can we stay under the 2°C warming limit in the year 2200 by completely eliminating our reliance on fossil fuel energy sources alone (reducing coal, oil, and gas to 0% of our energy supply), or do we also need to reduce our energy consumption per capita? (make appropriate changes and then run the model to figure this out)

1. both stabilize
2. neither stabilizes — both increase [correct answer for practice]
3. neither stabilizes — both decrease
4. CO2 goes up; temperature goes down
5. CO2 goes down; temperature goes up