2-Mark Z. Jacobson analiza los tipos de generación de energía más limpios y más sucios

El estudio realiza una comparativa entre doce tipos de combustible considerando su impacto en consumo de agua, uso de tierras, ecosistemas, disponibilidad de recursos, fiabilidad, contaminación térmica, contaminación del agua, proliferación nuclear y problemas de alimentos para el mundo. Además, los revisa en cuanto a su eficiencia con respecto a los tipos de motores para automóviles que se están desarrollando.

Los tipos de energía que acaban siendo los recomendados por el estudio son la energía eólica, la solar de concentración, la geotérmica, la maremotriz, la fotovoltaica, la hidroeléctrica y la undimotriz (generada por las olas).

Lo que más llama la atención es lo mal parados que quedan los llamados biocombustibles. El especialista los coloca como peor opción que, incluso, la energía nuclear y el carbón (uso de carbón para producir energía eléctrica, pero capturando y almacenando el dióxido de carbono que produce). Esto no sólo por el hecho de que la producción de biocombustibles aumentaría los costos de la tierra, de los alimentos, y que por cultivarlos, se podrían perder grandes extensiones de selvas y bosques, también porque tomando en cuenta todo su ciclo de producción, desde el cultivo, transporte, fabricación y uso, en algunos casos se acabaría produciendo más dióxido de carbono en comparación a las gasolinas, y en los otros casos la disminución no es significativa, inferior al 3 por ciento en condiciones optimas.


Parte 2

4d. Effects of nuclear energy on nuclear war and terrorism damage
Because the production of nuclear weapons material is occurring only in countries that have developed civilian nuclear energy programs, the risk of a limited nuclear exchange between countries or the detonation of a nuclear device by terrorists has increased due to the dissemination of nuclear energy facilities worldwide. As such, it is a valid exercise to estimate the potential number of immediate deaths and carbon emissions due to the burning of buildings and infrastructure associated with the proliferation of nuclear energy facilities and the resulting proliferation of nuclear weapons. The number of deaths and carbon emissions, though, must be multiplied by a probability range of an exchange or explosion occurring to estimate the overall risk of nuclear energy proliferation. Although concern at the time of an explosion will be the deaths and not carbon emissions, policy makers today must weigh all the potential future risks of mortality and carbon emissions when comparing energy sources.
Here, we detail the link between nuclear energy and nuclear weapons and estimate the emissions of nuclear explosions attributable to nuclear energy. The primary limitation to building a nuclear weapon is the availability of purified fissionable fuel (highly-enriched uranium or plutonium).68 Worldwide, nine countries have known nuclear weapons stockpiles (US, Russia, UK, France, China, India, Pakistan, Israel, North Korea). In addition, Iran is pursuing uranium enrichment, and 32 other countries have sufficient fissionable material to produce weapons. Among the 42 countries with fissionable material, 22 have facilities as part of their civilian nuclear energy program, either to produce highly-enriched uranium or to separate plutonium, and facilities in 13 countries are active.68 Thus, the ability of states to produce nuclear weapons today follows directly from their ability to produce nuclear power. In fact, producing material for a weapon requires merely operating a civilian nuclear power plant together with a sophisticated plutonium separation facility. The Treaty of Non-Proliferation of Nuclear Weapons has been signed by 190 countries. However, international treaties safeguard only about 1% of the world’s highly-enriched uranium and 35% of the world’s plutonium.68 Currently, about 30 000 nuclear warheads exist worldwide, with 95% in the US and Russia, but enough refined and unrefined material to produce another 100 000 weapons.69
The explosion of fifty 15 kt nuclear devices (a total of 1.5 MT, or 0.1% of the yields proposed for a full-scale nuclear war) during a limited nuclear exchange in megacities could burn 63–313 Tg of fuel, adding 1–5 Tg of soot to the atmosphere, much of it to the stratosphere, and killing 2.6–16.7 million people.68 The soot emissions would cause significant short- and medium-term regional cooling.70 Despite short-term cooling, the CO2 emissions would cause long-term warming, as they do with biomass burning.62 The CO2 emissions from such a conflict are estimated here from the fuel burn rate and the carbon content of fuels. Materials have the following carbon contents: plastics, 38–92%; tires and other rubbers, 59–91%; synthetic fibers, 63–86%;71 woody biomass, 41–45%; charcoal, 71%;72 asphalt, 80%; steel, 0.05–2%. We approximate roughly the carbon content of all combustible material in a city as 40–60%. Applying these percentages to the fuel burn gives CO2 emissions during an exchange as 92–690 Tg CO2. The annual electricity production due to nuclear energy in 2005 was 2768 TWh yr−1. If one nuclear exchange as described above occurs over the next 30 yr, the net carbon emissions due to nuclear weapons proliferation caused by the expansion of nuclear energy worldwide would be 1.1–4.1 g CO2 kWh−1, where the energy generation assumed is the annual 2005 generation for nuclear power multiplied by the number of yr being considered. This emission rate depends on the probability of a nuclear exchange over a given period and the strengths of nuclear devices used. Here, we bound the probability of the event occurring over 30 yr as between 0 and 1 to give the range of possible emissions for one such event as 0 to 4.1 g CO2 kWh−1. This emission rate is placed in context in Table 3.
4e. Analysis of CO2e due to converting vehicles to BEVs, HFCVs, or E85 vehicles
Here, we estimate the comparative changes in CO2e emissions due to each of the 11 technologies considered when they are used to power all (small and large) onroad vehicles in the US if such vehicles were converted to BEVs, HFCVs, or E85 vehicles. In the case of BEVs, we consider electricity production by all nine electric power sources. In the case of HFCVs, we assume the hydrogen is produced by electrolysis, with the electricity derived from wind power. Other methods of producing hydrogen are not analyzed here for convenience. However, estimates for another electric power source producing hydrogen for HFCVs can be estimated by multiplying a calculated parameter for the same power source producing electricity for BEVs by the ratio of the wind-HFCV to wind-BEV parameter (found in ESI ). HFCVs are less efficient than BEVs, requiring a little less than three times the electricity for the same motive power, but HFCVs are still more efficient than pure internal combustion (ESI ) and have the advantage that the fueling time is shorter than the charging time for electric vehicle (generally 1–30 h, depending on voltage, current, energy capacity of battery). A BEV-HFCV hybrid may be an ideal compromise but is not considered here.
In 2007, 24.55% of CO2 emissions in the US were due to direct exhaust from onroad vehicles. An additional 8.18% of total CO2 was due to the upstream production and transport of fuel (ESI ). Thus, 32.73% is the largest possible reduction in US CO2 (not CO2e) emissions due to any vehicle-powering technology. The upstream CO2 emissions are about 94.3% of the upstream CO2e emissions.58
Fig. 2 compares calculated percent changes in total emitted US CO2 emissions due to each energy-vehicle combination considered here. It is assumed that all CO2e increases or decreases due to the technology have been converted to CO2 for purposes of comparing with US CO2 emissions. Due to land use constraints, it is unlikely that corn or cellulosic ethanol could power more than 30% of US onroad vehicles, so the figure also shows CO2 changes due to 30% penetration of E85. The other technologies, aside from hydroelectric power (limited by land as well), could theoretically power the entire US onroad vehicle fleet so are not subject to the 30% limit.
Converting to corn-E85 could cause either no change in or increase CO2 emissions by up to 9.1% with 30% E85 penetration (ESI , I37). Converting to cellulosic-E85 could change CO2 emissions by +4.9 to −4.9% relative to gasoline with 30% penetration (ESI , J16). Running 100% of vehicles on electricity provided by wind, on the other hand, could reduce US carbon by 32.5–32.7% since wind turbines are 99.2–99.8% carbon free over a 30 yr lifetime and the maximum reduction possible from the vehicle sector is 32.73%. Using HFCVs, where the hydrogen is produced by wind electrolysis, could reduce US CO2 by about 31.9–32.6%, slightly less than using wind-BEVs since more energy is required to manufacture the additional turbines needed for wind-HFCVs. Running BEVs on electricity provided by solar-PV can reduce carbon by 31–32.3%. Nuclear-BEVs could reduce US carbon by 28.0–31.4%. Of the electric power sources, coal-CCS producing vehicles results in the least emission reduction due to the lifecycle, leakage, and opportunity-cost emissions of coal-CCS.
5. Effects on air pollution emissions and mortality
Although climate change is a significant driver for clean energy systems, the largest impact of energy systems worldwide today is on human mortality, as indoor plus outdoor air pollution kills over 2.4 million people annually (Introduction), with most of the air pollution due to energy generation or use.
Here, we examine the effects of the energy technologies considered on air pollution-relevant emissions and their resulting mortality. For wind, solar-PV, CSP, tidal, wave, and hydroelectric power, air-pollution relevant emissions arise only due to the construction, installation, maintenance, and decommissioning of the technology and as a result of planning-to-operation delays (Section 4b). For corn and cellulosic ethanol, emissions are also due to production of the fuel and ethanol-vehicle combustion. For non-binary geothermal plants (about 85% of existing plants) emissions also arise due to evaporation of NO, SO2, and H2S. The level of direct emissions is about 5% of that of a coal-fired power plant. For binary geothermal plants, such emissions are about 0.1% those of a coal-fired power plant. For nuclear power, pollutant emissions also include emissions due to the mining, transport, and processing of uranium. It is also necessary to take into the account the potential fatalities due to nuclear war or terrorism caused by the proliferation of nuclear energy facilities worldwide.
For coal-CCS, emissions also arise due to coal combustion since the CCS equipment itself generally does not reduce pollutants aside from CO2. For example, with CCS equipment, the CO2 is first separated from other gases after combustion. The remaining gases, such as SOx, NOx, NH3, and Hg are discharged to the air. Because of the higher energy requirement for CCS, more non-CO2 pollutants are generally emitted to the air compared with the case of no capture when a plant’s fuel use is increased to generate a fixed amount of electric power for external consumption. For example, in one case, the addition of CCS equipment for operation of an IGCC plant was estimated to increase fuel use by 15.7%, SOx emissions by 17.9%, and NOx emissions by 11%.32 In another case, CCS equipment in a pulverized coal plant increased fuel use by 31.3%, increased NOx emissions by 31%, and increased NH3 emissions by 2200% but the addition of another control device decreased SOx emissions by 99.7%.32
In order to evaluate the technologies, we estimate the change in the US premature death rate due to onroad vehicle air pollution in 2020 after converting current onroad light- and heavy-duty gasoline vehicles to either BEVs, HFCVs, or E85 vehicles. Since HFCVs eliminate all tailpipe air pollution when applied to the US vehicle fleet19,18 as do BEVs, the deaths due to these vehicles are due only to the lifecycle emissions of the vehicles themselves and of the power plants producing electricity for them or for H2 electrolysis. We assume lifecycle emissions of the vehicles themselves are similar for all vehicles so do not evaluate those emissions. We estimate deaths due to each electricity-generating technology as one minus the percent reduction in total CO2e emissions due to the technology (Table 3) multiplied by the total number of exhaust- plus upstream-emission deaths (gas and particle) attributable to 2020 light- and heavy-duty gasoline onroad vehicles, estimated as 15 000 in the US from 3-D model calculations similar to those performed previously.73 Thus, the deaths due to all BEV and HFCV options are attributed only to the electricity generation plant itself (as no net air pollution emanates from these vehicles). Because the number of deaths with most options is relatively small, the error arising from attributing CO2e proportionally to other air pollutant emissions may not be so significant. Further, since CO2e itself enhances mortality through the effect of its temperature and water vapor changes on air pollution,73 using it as a surrogate may be reasonable.
For nuclear energy, we add, in the high case, the potential death rate due to a nuclear exchange, as described in Section 4d, which could kill up to 16.7 million people. Dividing this number by 30 yr and the ratio of the US to world population today (302 million : 6.602 billion) gives an upper limit to deaths scaled to US population of 25 500 yr−1 attributable to nuclear energy. We do not add deaths to the low estimate, since we assume the low probability of a nuclear exchange is zero.
The 2020 premature death rates due to corn- and cellulosic-E85 are calculated by considering 2020 death rate due to exhaust, evaporative, and upstream emissions from light- and heavy-duty gasoline onroad vehicles, the changes in such death rates between gasoline and E85. Changes in deaths due to the upstream emissions from E85 production were determined as follows. Fig. 3 shows the upstream lifecycle emissions for multiple gases and black carbon from reformulated gasoline (RFG), corn-E90, and cellulosic-E90.58 The upstream cycle accounts for fuel dispensing, fuel distribution and storage, fuel production, feedstock transmission, feedstock recovery, land-use changes, cultivation, fertilizer manufacture, gas leaks and flares, and emissions displaced. The figure indicates that the upstream cycle emissions of CO, NO2, N2O, and BC may be higher for both corn- and cellulosic E90 than for RFG. Emissions of NMOC, SO2, and CH4 are also higher for corn-E90 than for RFG but lower for cellulosic-E90 than for RFG. Weighting the emission changes by the low health costs per unit mass of pollutant from Spadaro and Rabl74 gives a rough estimate of the health-weighed upstream emission changes of E90 versus RFG. The low health cost, which applies to rural areas, is used since most upstream emissions changes are away from cities. The result is an increase in the corn-E90 death rate by 20% and the cellulosic-E90 death rate by 30% (due primarily to the increase in BC of cellulosic-E90 relative to corn-E90), compared with RFG. Multiplying this result by 25%, the estimated ratio of upstream emissions to upstream plus exhaust emissions (Section 4e) gives death rate increases of 5.0% and 7.5% for corn- and cellulosic-E90, respectively, relative to RFG. The changes in onroad deaths between gasoline and E85 were taken from the only study to date that has examined this issue with a 3-D computer model over the US.75 The study found that a complete penetration of E85-fueled vehicles (whether from cellulose or corn) might increase the air pollution premature death rate in the US by anywhere from zero to 185 deaths yr−1 in 2020 over gasoline vehicles. The emission changes in that study were subsequently supported.76

An additional effect of corn- and cellulosic ethanol on mortality is through its effect on undernutrition. The competition between crops for food and fuel has reduced the quantity of food produced and increased food prices. Other factors, such as higher fuel costs, have also contributed to food price increases. Higher prices of food, in particular, increase the risk of starvation in many parts of the world. WHO1 estimates that 6.2 million people died in 2000 from undernutrition, primarily in developing countries. Undernutrition categories include being underweight, iron deficiency, vitamin-A deficiency, and zinc deficiency. As such, death due to undernutrition does not require starvation. When food prices increase, many people eat less and, without necessarily starving, subject themselves to a higher chance of dying due to undernutrition and resulting susceptibility to disease. Here, we do not quantify the effects of corn-E85 or cellulosic-E85 on mortality due to the lack of a numerical estimate of the relationship between food prices and undernutrition mortality but note that it is probably occurring.
Fig. 4 indicates that E85 may increase premature deaths compared with gasoline, due primarily to upstream changes in emissions but also due to changes in onroad vehicle emissions. Cellulosic ethanol may increase overall deaths more than corn ethanol, although this result rests heavily on the precise particulate matter upstream emissions of corn- versus cellulosic-E85. Due to the uncertainty of upstream and onroad emission death changes, it can be concluded that E85 is unlikely to improve air quality compared with gasoline and may worsen it.
Fig. 4 also indicates that each E85 vehicle should cause more air-pollution related death than each vehicle powered by any other technology considered, except to the extent that the risk of a nuclear exchange due to the spread of plutonium separation and uranium enrichment in nuclear energy facilities worldwide is considered. This conclusion holds regardless of the penetration of E85. For example, with 30% penetration, corn-E85 may kill 4500–5000 people yr−1 more than CSP-BEVs at the same penetration. Because corn- and cellulosic-E85 already increase mortality more than any other technology considered, the omission of undernutrition mortality due to E85 does not affect the conclusions of this study. Emissions due to CCS-BEVs are estimated to kill more people prematurely than any other electric power source powering vehicles if nuclear explosions are not considered. Nuclear electricity causes the second-highest death rate among electric power sources with respect to lifecycle and opportunity-cost emissions. The least damaging technologies are wind-BEV followed by CSP-BEV and wind-HFCV.
6. Land and ocean use
In this section, the land, ocean surface, or ocean floor required by the different technologies is considered. Two categories of land use are evaluated: the footprint on the ground, ocean surface, or ocean floor and the spacing around the footprint. The footprint is more relevant since it is the actual land, water surface, or sea floor surface removed from use for other purposes and the actual wildlife habitat area removed or converted (in the case of hydroelectricity) by the energy technology. The spacing area is relevant to the extent that it is the physical space over which the technology is spread thus affects people’s views (in the case of land or ocean surface) and the ability of the technology to be implemented due to competing uses of property. For wind, wave, tidal, and nuclear power, the footprint and spacing differ; for the other technologies, they are effectively the same.
In the case of wind, wave, and tidal power, spacing is needed between turbines or devices to reduce the effect of turbulence and energy dissipation caused by one turbine or device on the performance of another. One equation for the spacing area (A, m2) needed by a wind turbine to minimize interference by other turbines in an array is A = 4D × 7D, where D is the rotor diameter (m).11 This equation predicts that for a 5 MW turbine with a 126 m diameter rotor, an area of 0.44 km2 is needed for array spacing. Over land, the area between turbines may be natural habitat, open space, farmland, ranch land, or used for solar energy devices, thus it is not wasted. On ridges, where turbines are not in a 2-D array but are lined up adjacent to each other, the spacing between the tips of turbine rotors may be one diameter, and the space required is much smaller since the array is one- instead of two-dimensional. Over water, wind turbines are also frequently closer to each other in the direction perpendicular to the prevailing wind to reduce local transmission line lengths.
6.1. Wind
The footprint on the ground or ocean floor/surface of one large (e.g., 5 MW) wind turbine (with a tubular tower diameter, including a small space around the tube for foundation, of 4–5 m) is about 13–20 m2. Temporary dirt access roads are often needed to install a turbine. However, these roads are generally not maintained, so vegetation grows over them, as indicated in photographs of numerous wind farms. When, as in most cases, wind farms are located in areas of low vegetation, vehicle access for maintenance of the turbines usually does not require maintained roads. In some cases, turbines are located in more heavily vegetated or mountainous regions where road maintenance is more critical. However, the large-scale deployment of wind will require arrays of turbines primarily in open areas over land and ocean. In such cases, the footprint of wind energy on land is effectively the tower area touching the ground. Wind farms, like all electric power sources, also require a footprint due to transmission lines. Transmission lines within a wind farm are always underground. Those between the wind farm and a nearby public utility electricity distribution system are usually underground, but long distance transmission usually is not. In many cases, a public utility transmission pathway already exists near the wind farm and the transmission capacity needs to be increased. In other cases, a new transmission path is needed. We assume such additional transmission pathways apply roughly equally to all most electric power sources although this assumption may result in a small error in footprint size.
6.2. Wave
For surface wave power, the space between devices is open water that cannot be used for shipping because of the proximity of the devices to one another. The footprint on the ocean surface of one selected 750 kW device is 525 m2 (ESI ), larger than that of a 5 MW wind turbine. However, the spacing between wave devices (about 0.025 km2, ESI ) is less than that needed for a wind turbine.
6.3. Tidal
Many tidal turbines are designed to be completely underwater (e.g., resting on the ocean floor and not rising very high) although some designs have a component protruding above water. Since ocean-floor-based turbines do not interfere with shipping, the ocean area they use is not so critical as that used by other devices. However, some concerns have been raised about how sea life might be affected by tidal turbines. The footprint area of one sample ocean-floor-based 1 MW tidal turbine is about 288 m2 (ESI ) larger than the footprint area of a larger, 5 MW wind turbine. The array spacing of tidal turbines must be a similar function of rotor diameter as that of a wind turbine since tidal turbines dissipate tidal energy just as wind turbines dissipate wind energy. However, because tidal turbine rotor diameters are smaller than wind turbine rotors for generating similar power (due to the higher density of water than air), the spacing between tidal turbines is lower than that between wind turbines if the equation A = 4D × 7D is used for tidal turbines.
6.4. Nuclear
In the case of nuclear power, a buffer zone around each plant is needed for safety. In the US, nuclear power plant areas are divided into an owner-controlled buffer region, an area restricted to some plant employees and monitored visitors, and a vital area with further restrictions. The owner-controlled buffer regions are generally left as open space to minimize security risks. The land required for nuclear power also includes that for uranium mining and disposal of nuclear waste. Estimates of the lands required for uranium mining and nuclear facility with a buffer zone are 0.06 ha yr GWh−1 and 0.26 ha yr GWh−1, respectively, and that for waste for a single sample facility is about 0.08 km231 For the average plant worldwide, this translates into a total land requirement per nuclear facility plus mining and storage of about 20.5 km2. The footprint on the ground (e.g., excluding the buffer zone only) is about 4.9–7.9 km2.
6.5. Solar-PV and CSP
The physical footprint and spacing of solar-PV and CSP are similar to each other. The area required for a 160 W PV panel and walking space is about 1.9 m2 (ESI ), or 1.2 km2 per 100 MW installed, whereas that required for a 100 MW CSP plant without storage is 1.9–2.4 km2 (ESI ). That with storage is 3.8–4.7 km2 (ESI footnote S42). The additional area when storage is used is for additional solar collectors rather than for the thermal storage medium (which require little land). The additional collectors transfer solar energy to the storage medium for use in a turbine at a later time (e.g., at night), thereby increasing the capacity factor of the turbine. The increased capacity factor comes at the expense of more land and collectors and the need for storage equipment. Currently, about 90% of installed PV is on rooftops. However, many PV power plants are expected in the future. Here, we estimate that about 30% of solar-PV will be on rooftops in the long term (with the rest on hillsides or in power plants). Since rooftops will exist regardless of whether solar-PV is used, that portion is not included in the footprint or spacing calculations discussed shortly.
6.6. Coal-CCS, geothermal, hydroelectric
The land required for coal-CCS includes the lands for the coal plant facility, the rail transport, and the coal mining. A 425 MW coal-CCS plant requires a total of about 5.2 km2 (ESI ), or about 1.2 km2 per 100 MW. The land required for a 100 MW geothermal plant is about 0.34 km2 (ESI ). A single reservoir providing water for a 1300 MW hydroelectric power plant requires about 650 km2 (ESI ), or 50 km2 per 100 MW installed.
6.7. Footprint and spacing for onroad vehicles
Here, we compare the footprint and spacing areas required for each technology to power all onroad (small and large) vehicles in the United States. All numbers are derived in ESI . Wind-BEVs require by far the least footprint on the ground over land or ocean (1–2.8 km2). Tidal-BEVs do not consume ocean surface or land area but would require about 121–288 km2 of ocean floor footprint. Wave devices would require about 400–670 km2 of ocean surface footprint to power US BEVs. Corn ethanol, on the other hand, would require 900 000–1 600 000 km2 (223–399 million acres) just to grow the corn for the fuel, which compares with a current typical acreage of harvested corn in the US before corn use for biofuels of around 75 million.77 Cellulosic ethanol could require either less or more land than corn ethanol, depending on the yield of cellulosic material per acre. An industry estimate is 5–10 tons of dry matter per acre.78 However, a recent study based on data from established switchgrass fields gives 2.32–4.95 tons acre−1.79 Using the high and low ends from both references suggests that cellulosic ethanol could require 430 000–3 240 000 km2 (106–800 million acres) to power all US onroad vehicles with E85.
Fig. 5 shows the ratio of the footprint area required for each technology to that of wind-BEVs. The footprint area of wind-BEVs is 5.5–6 orders of magnitude less than those of corn- or cellulosic-E85, 4 orders of magnitude less than those of CSP- or PV-BEVs, 3 orders of magnitude less than those of nuclear- or coal-BEVs, and 2–2.5 orders of magnitude less than those of geothermal-, tidal-, or wave-BEVs. The footprint for wind-HFCVs is about 3 times that for wind-BEVs due to the larger number of turbines required to power HFCVs than BEVs. As such, wind-BEVs and wind-HFCVs are by far the least invasive of all technologies over land. The relative ranking of PV-BEVs with respect to footprint improves relative to that shown in the figure (going ahead of CCS-BEV) if >80% (rather than the 30% assumed) of all future PV is put on rooftops.

Fig. 6 compares the fractional area of the US (50 states) required for spacing (footprint plus separation area for wind, tidal, wave, nuclear; footprint area for the others) needed by each technology to power US vehicles. The array spacing required by wind-BEVs is about 0.35–0.7% of all US land, although wind turbines can be placed over land or water. For wind-HFCVs, the area required for spacing is about 1.1–2.1% of US land. Tidal-BEVs would not take any ocean surface or land area but would require 1550–3700 km2 of ocean floor for spacing (5–6% that of wind) or the equivalent of about 0.017–0.04% of US land. Wave-BEVs would require an array spacing area of 19 000–32 000 km2 (about 50–59% that of wind), or an area equivalent to 0.21–0.35% of US land. Solar-PV powering US BEVs requires 0.077–0.18% of US land for spacing (and footprint), or 19–26% of the spacing area required for wind-BEVs. Similarly, CSP-BEVs need about 0.12–0.41% of US land or 34–59% of the spacing required for wind-BEV.

A 100 MW geothermal plant requires a land area of about 0.33 km2. This translates to about 0.006–0.008% of US land for running all US BEVs, or about 1.1–1.6% the array spacing required for wind-BEVs. Powering all onroad vehicles in the US with nuclear power would require about 0.045–0.061% of US land for spacing, or about 9–13% that of wind-BEVs. The land required for CCS-BEVs is 0.03–0.06% of the US, or about 7.4–8.2% of the array spacing required for wind-BEVs. The land required for hydro-BEVs is significant but lower than that for E85. Hydro-BEV would require about 1.9–2.6% of US land for reservoirs. This is 3.7–5.4 times larger than the land area required for wind-BEV spacing. Corn and cellulosic ethanol require by far the most land of all the options considered here. Running the US onroad vehicle fleet with corn-E85 requires 9.8–17.6% of all 50 US states, or 2.2–4.0 States of California. Cellulosic-E85 would require from 4.7–35.4% of US land, or 1.1–8.0 States of California, to power all onroad vehicles with E85.
In sum, technologies with the least spacing area required are, in increasing order, geothermal-BEVs, tidal-BEVs, wave-BEVs, CCS-BEVs, nuclear-BEVs, PV-BEVs, CSP-BEVs, wave-BEVs, and wind-BEVs. These technologies would all require <1% of US land for spacing. Corn-E85 and cellulosic-E85 are, on the other hand, very land intensive. The spacing area required for wind-BEVs is about 1/26 that required for corn-ethanol (E85) and 1/38 that required for cellulosic ethanol (E85), on average. The spacing area for PV-BEVs is about 1/3 that of wind-BEVs.
7. Water supply
Water shortages are an important issue in many parts of the world and may become more so as air temperatures rise from global warming. Here, energy technologies are examined with respect to their water consumption (loss of water from water supply) when the technologies are used to power US vehicles. Results are summarized in Fig. 7 and derived in ESI .
7.1. Corn-E85
For corn-E85, water is used for both irrigation and ethanol production. Most water for corn comes from rainfall, but in 2003, about 13.3% (9.75 million out of the 73.5 million acres) of harvested corn in the US was irrigated. With 1.2 acre-ft of irrigation water per acre of land applied to corn,80 an average of 178 bushels per acre,80 and 2.64 gallons of ethanol per bushel, the water required for growing corn in 2003 was about 832 gallons per gallon of ethanol produced from irrigated land, or 102.3 gal-H2O gal-ethanol−1 for all (irrigated plus nonirrigated) corn. In Minnesota ethanol factories, about 4.5 L of water were required to produce one liter of 100% ethanol in 2005.81 Much of the water consumed is from evaporation during cooling and wastewater discharge. Thus, the irrigation plus ethanol-factory water requirement for corn ethanol in the US is about 107 gal-H2O gal-ethanol−1, on average. This compares with an estimate for an earlier year with a higher fraction of irrigated corn of 159 gal-H2O gal-ethanol−1.82
7.2. Cellulosic-E85
The use of switchgrass to produce ethanol would most likely reduce irrigation in comparison with use of corn. However, since agricultural productivity increases with irrigation (e.g., irrigated corn produced 178 bushels per harvested acre in the US in 2003, whereas irrigated+nonirrigated corn produced 139.7 bushels per harvested acre77), it is likely that some growers of switchgrass will irrigate to increase productivity. Here, it is assumed that the irrigation rate for switchgrass will be half that of corn (thus, around 6.6% of switchgrass crops may be irrigated).
7.3. Hydroelectric
Hydroelectric power consumes water as a result of evaporation from the surface of reservoirs. Since reservoirs are also designed to conserve water and provide flood control, irrigation, navigation and river regulation, salinity control in delta regions, and domestic water supply, not all evaporation can be attributable to hydroelectricity. An estimate of water consumption through evaporation from reservoirs by hydroelectric power that accounted for river and stream evaporation but not for loss to the ocean or for other uses of reservoir water is 18 gal kWh−1.83 We multiply this number by the fraction of a reservoir’s use attributable to hydroelectricity. Although several big reservoirs were built primarily for power supply, they are currently used for the purposes described above. As such, their fraction attributable to hydroelectricity should be less than or equal to their capacity factor (25–42%, Table 1), which gives the fraction of their turbines’ possible electrical output actually used. The main reason capacity factors are not near 100% is because water in the dam is conserved for use at different times during the year for the purposes listed. We thus estimate the water consumption rate as 4.5–7.6 gal kWh−1.
7.4. Nuclear
Nuclear power plants, usually located near large bodies of surface water, require more water than other fossil-fuel power plants84 but less water than ethanol production. Water is needed in a nuclear plant to produce high-pressure steam, which is used to turn a turbine to drive a generator. Most water is returned at higher temperature to its source, but some of the water is lost by evaporation. The water consumption (from evaporation) in a nuclear power plant ranges from 0.4–0.72 gal kWh−1, depending on the type of cooling technology used.84
7.5. Coal-CCS
Carbon capture and sequestration projects result in water consumption due to the coal plant, estimated as 0.49 gal kWh−1.85 The increased electricity demand due to the CCS equipment is accounted for by the fact that more kWh of electricity are required, thus more water is consumed, when CCS equipment is used.
7.6. CSP
Concentrated solar power with parabolic trough technology requires the heating of water to produce steam. However, since the process is closed-loop, this water is generally not lost. However, the steam needs to be recondensed for water reuse. This is generally done by combining the steam with cooler water in a cooling tower or by air cooling in a heat exchanger. In the case of water cooling, water is lost by evaporation. Water is also needed to clean mirrors. One estimate of the water consumption for parabolic-trough CSP during is 0.74 gal-H2O kWh−1 for water cooling and 0.037 gal-H2O kWh−1 for mirror cleaning.86 The water consumption for central-tower receiver CSP cooling and cleaning is 0.74 gal-H2O kWh−1.86 If air cooling is used, water use decreases significantly, but efficiency also decreases. We assume here that CSP will be water cooled to maximize efficiency. For parabolic dish-shaped reflectors, only water for cleaning is needed.
7.7. Geothermal, wind, wave, tidal, solar-PV
Geothermal plants consume some water during their construction and operation. One estimate of such consumption is 0.005 gal kWh−1.27 Wind turbines, wave devices, and tidal turbines do not consume water, except in the manufacture of the devices. An estimate of water consumption due to wind is 0.001 gal-H2O kWh−1.85 We assume the same for wave and tidal device manufacturing. Solar-PV requires water for construction of the panels and washing them during operation. We estimate the water consumption during panel construction as 0.003 gal-H2O kWh−1 and that during cleaning the same as that for CSP, 0.037 gal-H2O kWh−1, for a total of 0.04 gal-H2O kWh−1.
7.8. Comparison of water consumption
Fig. 7 compares the water consumed by each technology when used to power all US onroad vehicles. When wind or any other electric power source is combined with HFCVs, additional water is required during electrolysis to produce hydrogen (through the reaction H2O + electricity H2 + 0.5 O2). This consumption is accounted for in the wind-HFCVs bar in the figure. The lowest consumers of water among all technologies are wind-BEVs, tidal-BEVs, and wave-BEVs, followed by geo-BEVs, PV-BEVs, and wind-HFCVs. The largest consumer is corn-E85, followed by hydro-BEVs and cellulosic-E85. If all US onroad vehicles were converted to corn-E85, an additional 8.2–11.4% of the total water consumed for all purposes in the US in 2000 would be needed. For cellulosic-E85, an additional 4.3–5.9% would be needed (subject to the uncertainty of the irrigation rate). Since hydroelectricity is unlikely to expand significantly rather than be used more effectively to provide peaking power, its additional water consumption is not such an issue. Further, because new dams built for the joint purposes of water supply and hydroelectricity will enhance the availability of water in dry months, an additional advantage exists to hydroelectric power with respect to water supply that is not captured in Fig. 7.
8. Effects on wildlife and the environment
The effects of energy technologies on wildlife and natural ecosystems are proportional to the footprint on land or water required by the technology, the air and water pollution caused by the technology, and direct interactions of wildlife with the technology. In this section, we rank the different technologies based on these effects.
The covering of land with a building or paved road, or the surface mining of land effectively destroys habitat. For example, between 1992 and 2002, 381 000 acres (1542 km2) of US forest habitat were destroyed by mountaintop removal due to coal mining.88 With coal-CCS, mountaintop removal will increase as coal consumption expands to meet new energy demand and power CCS equipment.
The conversion of land from natural vegetation to cropland, needed for the production of biofuels, similarly reduces available habitat, particularly when pesticides are used to protect crops. This effect is greatest when rich ecosystems, such as a tropical or other forests are destroyed either directly for biofuel farming or indirectly when biofuel farming in other areas causes cattle ranchers or soy farmers to move and clear rainforest areas. Even when agricultural land is converted from one type of crop to another, biota may be lost. For example, when switchgrass replaces a non-biofuel crop, switchgrass’ lignocellulose is removed to produce ethanol, so microorganisms, which normally process the lignocellulose, cannot replenish soil nutrients, reducing biota in the soil. On the other hand, good selection of land use for growing biofuel crops could reduce impacts of the crops on the local ecosystem.60
Dams for hydroelectric power reduce salmon population by reducing access to spawning grounds. To mitigate this problem, fish ladders are usually installed. Because sediment builds up behind a dam, water leaving a dam contains little sediment.89 This can lead to scavenging of sediment from riverbeds downstream, causing loss of riverbank habitat. On the other hand, the flooding of land with water behind a dam reduces habitat for land-based wildlife but increases it for aquatic wildlife there. Similarly, the addition of structures to the ocean increases the surface area of artificial reefs, increasing the presence of fish life in these areas.90 The use of dams for peaking power also affects the diurnal variation of water flow down a river. This can affect downstream ecosystems negatively in some cases although the effect may vary significantly from river to river.
In ranking the relative impacts of land use change due to the technologies on wildlife, we consider the footprint of the technology on land based on Fig. 5, but take into account whether the land was converted to water, agricultural land, land-based buildings/structures, or ocean-based structures, or mined on its surface and what the previous land use might have been. In the case of solar-PV, for example, the impacts are proportional to the footprint area in Fig. 5 (which already excludes rooftops), but less proportional to footprint than other energy sources since much of PV in the near future will be located in arid regions with less wildlife displaced than for other technologies, which will be situated on more biodiverse land. CSP will similarly be located in more arid land. As a result, the rankings of CSP and PV with respect to wildlife in Table 4 are higher than their respective footprint rankings.
Air-pollution-relevant emissions harm animals as much as they damage humans.91 Such emissions also damage plants and trees by discoloring their leaves, stunting their growth, or killing them.92–94 To account for air pollution effects on wildlife and ecosystems, we use the information from Fig. 4, which shows the effects of the energy technologies on human air pollution mortality, as a surrogate.
The effects on bird and bat deaths due to each energy technology should also be considered. Energy technologies kill birds and bats by destroying their habitat, polluting the air they breathe and the water they drink, and creating structures that birds and bats collide with or are electrocuted on. Loss of habitat is accounted for here by considering the footprint of each technology on the ground. Fig. 5 indicates that a large penetration of wind turbines for BEVs or HFCVs will result in 2.5 orders-of-magnitude less habitat loss based on footprint than geothermal power and 3 orders-of-magnitude less than Nuc-BEVs or CCS-BEVs. In particular, mountaintop removal during coal mining is historically responsible for the decline in several bird species, including the Cerulean Warbler, the Louisiana Waterthrush, the Worm-Eating Warbler, the Black-and-White Warbler, and the Yellow-Throated Vireo.88 Although CSP and PVs require more footprint than most other technologies, both will be located primarily in deserts or, in the case of PV, also on rooftops, reducing their effects on habitat. The large footprint requirements for corn and cellulosic ethanol will cause the largest loss in bird habitat, such as wetlands, wet meadows, grassland, and scrub.88
With regard to air pollution, the low air pollution emissions and human mortality associated with wind-BEVs (Fig. 4) suggest it will have the least effect on respiratory- and cardiovascular-related bird and bat mortality. Corn- and cellulosic-E85 will have the greatest impact, followed by CCS-BEVs and nuclear-BEVs.
Because significant concern has been raised with respect to the effect of wind turbines on birds and bat collisions, we examine this issue in some detail. With regards to structures, wind turbines in the US currently kill about 10 000–40 000 birds annually, 80% of which are songbirds and 10%, birds of prey.88 For comparison, 5–50 million birds are killed annually by the 80 000 communication towers in the US.88 Birds are attracted by their lights and collide with them or their guy wires during night migration. Also, 97.5–975 million birds are killed by collision with windows and hundreds of millions of birds are killed by cats in the US each year.88 Finally, in 2005, 200 million birds were lost to the Avian Flu worldwide.95 A recent report determined that less than 0.003% of anthropogenic bird deaths in 2003 were due to wind turbines in four eastern US states.96 If 1.4–2.3 million 5 MW wind turbines were installed worldwide to eliminate 100% of anthropogenic CO2 emissions (ESI ), the number of bird deaths worldwide due to wind would be about 1.4–14 million, less than 1% of the global anthropogenic bird loss. However, such a conversion would simultaneously eliminate global warming, air pollution human and animal mortality due to current energy use.
A related issue is the effect of tidal turbine rotors on sea life. Because tidal turbine rotors do not turn rapidly, they should not endanger sea life significantly. Further, with tidal turbine configurations that use a duct to funnel water,97 it may be possible to put a grating in front of the duct to prevent medium- and large-sized fish from entering the duct. The turbines may enhance sea communities by serving as artificial reefs as offshore wind turbines do.90
Some additional effects of energy technologies include thermal and chemical pollution, radioactive waste disposal, and feedbacks of technologies to the atmosphere. Thermal pollution reduces dissolved oxygen in water directly and indirectly by enhancing algae blooms. A reduction in dissolved oxygen harms fish, amphibians, and copepods. Thermal pollution also increases the rate of aquatic life metabolism, increasing competition for food. The energy technologies considered here that impact the temperature of water in lakes and rivers the most are CSP, nuclear, coal-CCS, and ethanol – the first three directly and the last through its lifecycle requirement of coal and nuclear electricity. The remaining technologies affect thermal pollution proportionally to their lifecycle CO2e emissions, most of which come from thermal power plants as well, but such lifecycle energy requirements are small.
Chemical waste pollution into surface and groundwater also impacts wildlife. Ethanol factories produce sewage-like effluent containing syrup, ethanol, chloride, copper, and other contaminants, produced during fermentation and distillation.98 Coal-CCS releases acids (SO2 and NOx) and mercury into the air that deposit to lakes and rivers as acid deposition. Some CCS technologies produce liquid wastes that are discharged to lakes or rivers and solid wastes that are incinerated. Both coal- and uranium-mining operations result in the release of chemicals into ground and surface waters. Other energy options are assumed to emit chemical waste proportionally to their lifecycle emissions.
Nuclear power plants produce fuel rods that are usually stored on site for several years in cooling ponds pending transport to a permanent site. The local storage of this high-level waste may preclude the future re-use of some nuclear power plant land for decades to centuries. In the US, a planned permanent site since 1982 has been Yucca Mountain. However, studies are still being carried out to determine whether storage at this site poses a long-term hazard.99 Nuclear power plants also produce low-level waste, including contaminated clothing and equipment.
Finally, a question that frequently arises is the effect of a large penetration of wind turbines on local and global meteorology. This issue can be examined correctly only with high-resolution computer modeling. To date, no resolved study covering the large scale has been performed. The modeling studies that have been performed are too coarse for their results to be relied on. A back-of-the-envelope calculation of the effects that accounts for the upstream and downstream velocity of a turbine and the global mean of measured winds over land indicates that, if 10 million 1.5 MW wind turbines were used to power all the world’s energy (electric plus nonelectric), the combined energy loss from the slower winds among all wakes worldwide in the boundary layer (about 1 km) would be <1%.100
9. Energy supply disruption
Another key question for each energy technology is the extent to which the supply of energy from it can be disrupted by terrorism, war, or natural disaster. The energy technologies that are distributed (e.g., solar PV, wind, wave, and tidal) are least prone to disruption, whereas those that are centralized (e.g., nuclear, coal-CCS, hydroelectric, geothermal, CSP, ethanol factories) are most at risk to disruption.101
Severe weather, earthquake, fire, flood, or terrorist activity can take out some distributed-energy devices, but it is unlikely that an entire wind or solar PV farm could be disrupted by one of these events. With respect to severe weather, the survival wind speed for most wind turbines is around 60–65 m s−1, within range of the wind speeds in a Category 4 hurricane of 58.5–69 m s−1. Most tornados are less than 100 m across. An F4 (92.5–116 m s−1) tornado can reach 0.5–1.6 km wide. An F5 (wind speeds 117–142 m s−1) can reach 1.6–5 km wide. Although the chance that a Category 4–5 hurricane or an F4–F5 tornado hits a wind turbine is small, efforts could be made to strengthen turbines in at-risk areas.
In the case of centralized power sources, the larger the plant, the greater the risk of terrorism and collateral damage. In the case of nuclear power, collateral damage includes radiation release. In the case of hydroelectric power, it includes flooding. In the case of ethanol and coal-CCS, it includes some chemical releases. Whereas, nuclear power plants are designed to withstand tornados and other severe whether, the other power plants are not. However, nuclear power plants are vulnerable to heat waves. Because nuclear power plants rely on the temperature differential between steam and river or lake water used in the condenser, they often cannot generate electricity when the water becomes too hot, as occurred during the European heat wave of 2004, when several nuclear reactors in France were shut down.
Because nuclear power plants are centralized, release radiation if destroyed, and may shut down during a heat wave, we deem them to be the most likely target of a terrorist attack and prone to energy supply disruption among all energy sources. Large hydroelectric power plants are the second-most likely to be targeted by terrorists. Because they are a centralized power source and susceptible to reduced capacity during a drought, they are also considered to be the second-most vulnerable to disruption. Ethanol factories, coal-CCS, geothermal, and CSP plants are all centralized so are also subject to disruption and attack, but less so than nuclear or hydroelectricity. The greater potential for chemical releases from an ethanol plant makes it more risky than the other energy sources. CSP plants are generally smaller than coal-CCS plants, so are less likely to result in a disruption if disabled. The distributed-energy sources are the least likely to be disrupted. Among these, tidal power may be the most protected from severe weather whereas wave power, the most vulnerable. Solar PVs are least likely to be sited in locations of severe storms, so will be disrupted less than wind. Wind-BEV supply is more secure than wind-HFCV supply since fewer turbines are required in the former case.
10. Intermittency and how to address it
Wind, solar, wave, and tidal power at one location and time are naturally intermittent. In other words, at a single location and time, it is not possible to guarantee power from them. Tidal power at a single location and time is more reliable because of the predictability of the tides. Solar intermittency is due to day-night and seasonal transitions of the sun and clouds. Wind intermittency is due to variations in pressure gradients over minutes to seasons to years. With the large-scale deployment of an intermittent resource today, backup generators are needed that can be brought online quickly, increasing stress and maintenance of the system. However, it is shown here that when intermittent energy sources are combined with each other or over large geographical regions, they are much less intermittent than at one location. When combined with storage media, such as batteries or hydrogen, the effect of their intermittency is reduced further or eliminated.
Coal-CCS, nuclear, geothermal, and hydroelectric power are more reliable than the resources listed above but have scheduled and unscheduled outages. For example, nuclear power plants have unscheduled outages during heat waves (Section 9). Further, the average coal plant in the US from 2000–2004 was down 6.5% of the year for unscheduled maintenance and 6.0% of the year for scheduled maintenance.102 This compares with a total down time for modern wind turbines of 0–2% over land and 0–5% over the ocean.90 Solar-PV panels similarly have a downtime of near 0–2%. A difference between the outages of centralized and distributed plants is that when individual solar panels or wind turbines are down, for example, only a small fraction of electrical production is affected, whereas when a nuclear or coal plant is down, a large fraction is affected. Nuclear plants in the US have become more reliable in the last decade. In 2006, the overall capacity factor for nuclear in the US was 89.9%103 compared with 80.8% worldwide (Table 1). Hydroelectric power plants are more reliable than most other centralized plants (e.g., with unscheduled outage rates of <5%;102 however, because they are often used for peaking, their average capacity factors are low (Table 1). Geothermal capacity factors in the US are generally 89–97%,27 suggesting a reliability similar to nuclear power. Like nuclear, the globally-averaged capacity factor of geothermal is lower than its US average (Table 1). The overall outage rate of CSP plants in the Mojave desert have been reported as 3.3–4.0% for 1997–2001, except for 2000 when the outage rate was 7.1%.104
Whether or not intermittency affects the power supply depends on whether effort to reduce intermittency are made. Five methods of reducing intermittency or its effects are (a) interconnecting geographically-disperse naturally-intermittent energy sources (e.g., wind, solar, wave, tidal), (b) using a reliable energy source, such as hydroelectric power, to smooth out supply or match demand, (c) using smart meters to provide electric power to vehicles in such a way as to smooth out electricity supply, (d) storing the electric power for later use, and (e) forecasting the weather to plan for energy supply needs better. These are discussed briefly, in turn.
10a. Interconnecting geographically-dispersed intermittent energy sources
Interconnecting geographically-disperse wind, solar, tidal, or wave farms to a common transmission grid smoothes out electricity supply significantly, as demonstrated for wind in early work.105 For wind, interconnection over regions as small as a few hundred kilometers apart can eliminate hours of zero power, accumulated over all wind farms and can convert a Rayleigh wind speed frequency distribution into a narrower Gaussian distribution.106 When 13–19 geographically-disperse wind sites in the Midwest, over a region 850 km × 850 km, were hypothetically interconnected, an average of 33% and a maximum of 47% of yearly-averaged wind power was calculated to be usable as baseload electric power at the same reliability as a coal-fired power plant.107 That study also found that interconnecting 19 wind farms through the transmission grid allowed the long-distance portion of capacity to be reduced, for example, by 20% with only a 1.6% loss in energy. With one wind farm, on the other hand, a 20% reduction in long-distance transmission caused a 9.8% loss in electric power. The benefit of interconnecting wind farms can be seen further from real-time minute-by-minute combined output from 81% of Spain’s wind farms.108 Such figures show that interconnecting nearly eliminates intermittency on times scales of hours and less, smoothing out the electricity supply. In sum, to improve the efficiency of intermittent electric power sources, an organized and interconnected transmission system is needed. Ideally, fast wind sites would be identified in advance and the farms would be developed simultaneously with an updated interconnected transmission system. The same concept applies to other intermittent electric power sources, such as solar PV and CSP. Because improving the grid requires time and expense, planning for it should be done carefully.
10b. Load smoothing or matching with hydroelectric or geothermal power
A second method of reducing the effect of intermittency of wind is to combine multiple renewable energy sources,109 including wind, solar, hydroelectric, geothermal, tidal, and wave power, together, to reduce overall intermittency, and to use hydroelectric or geothermal power to fill in the gaps. This concept is illustrated for California in Fig. 8. Because hydroelectric power, when run in spinning reserve mode, can be increased or decreased within 15–30 s, it is an ideal source of peaking power. Hydroelectric power is used significantly for peaking rather than baseload power today, so enhancing its use for peaking should not be a large barrier. Geothermal power is used primarily as a baseload source. However, geothermal plants can be designed to follow load as well.110
10c. Using smart meters to provide electric power for vehicles at optimal times
A third method of smoothing intermittent power is to upgrade smart meters112 to provide electricity for electric vehicles when wind power supply is high and to reduce the power supplied to vehicles when wind power is low. Utility customers would sign up their electric vehicles under a plan by which the utility controlled the night-time (primarily) or daytime supply of power to the vehicles. Since most electric vehicles would be charged at night, this would provide primarily a night-time method of smoothing out demand to meet supply.
10d. Storage
A fourth method of dealing with intermittency is to store excess intermittent energy in batteries (e.g., for use in BEVs), hydrogen gas (e.g., for use in HFCVs), pumped hydroelectric power, compressed air (e.g., in underground caverns or turbine nacelles), flywheels, or a thermal storage medium (as done with CSP). One calculation shows that the storage of electricity in car batteries, not only to power cars but also to provide a source of electricity back to the grid (vehicle-to-grid, or V2G), could stabilize wind power if 50% of US electricity were powered by wind and 3% of vehicles were used to provide storage.113 The only disadvantage of storage for grid use rather than direct use is conversion losses in both directions rather than in one.
10e. Forecasting
Finally, forecasting the weather (winds, sunlight, waves, tides, precipitation) gives grid operators more time to plan ahead for a backup energy supply when an intermittent energy source might produce less than anticipated. Forecasting is done with either a numerical weather prediction model, the best of which can produce minute-by-minute predictions 1–4 d in advance with good accuracy, or with statistical analyses of local measurements. The use of forecasting reduces uncertainty and improves planning, thus reduces the relevance of intermittency.
We rank each energy technology combination in terms of intermittency based on the scheduled and unscheduled downtime of the electric power source, whether the downtime affects a large or small fraction of electric power generation, the natural intermittency of the electric power source, and whether the technology combination includes a storage medium. For example, all cases considered involve combinations of the technology with either BEVs, HFCVs, or E85. Since BEVs are charged over a several-hour period, the instantaneous electricity production is not so important when the aggregate production over the period is guaranteed. With HFCVs, the hydrogen fuel is produced by electrolysis and can be stored for months to years. Thus, neither instantaneous nor weekly or seasonal fluctuations are necessarily disadvantageous. Since E85 can be stored, intermittency of its production is similarly not so much of an issue. Based on the low downtime of wind turbines, the fact that downtime affects only a small portion of the source, and the fact that intermittency is irrelevant for the production of hydrogen, we rank wind-HFCVs as the most reliable of all potential energy technology combinations. Because of the low outage rate and the ability to turn hydroelectric power on and off when it is in spinning reserve mode within 15–30 s, hydro-BEVs are ranked the second-most reliable of all energy technology combinations.
Because E85 can be stored, its production is generally independent of short-term intermittency. However, because ethanol plants are subject to fluctuations in crop supplies due to variations in weather and are more susceptible than hydroelectric power or wind turbines to planned or unplanned outages, corn- and cellulosic-E85 are tied for third. The remaining combinations involve production of electricity for BEVs. CSP-BEVs are ranked fifth because of CSP’s ability to store energy in thermal storage media on-site and their low overall outage rate (<5%). Although geothermal, nuclear, and coal-CCS can supply electricity in winter better than CSP-BEVs, the outage rates for the former technologies are higher, thus they are ranked 6th–8th, respectively. Tidal power is somewhat predictable, thus tidal-BEVs are ranked 9th. Wind-BEVs, PV-BEVs, and wave-BEVs are more intermittent.114,115 If wind peaks at night, such as over land in many places, PV can match daytime peak loads better than wind114 (e.g., Fig. 8). However, for powering BEVs, most demand will be at night. Further, offshore wind and wave power generally peak during the time of peak demand. As such, we rank PV-BEVs, wind-BEVs, and wave-BEVs the same in terms of reliability. As discussed, the reliability of the intermittent technologies can be improved or ensured with the four methods discussed in this section; the rankings do not reflect such potential improvements.