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20 September 2020

Transitioning All Energy in 74 Metropolitan Areas, Including 30 Megacities, to 100% Clean and Renewable Wind, Water, and Sunlight (WWS)

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Atmosphere/Energy Program, Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA
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Author to whom correspondence should be addressed.
Energies2020, 13(18), 4934;https://doi.org/10.3390/en13184934
This article belongs to the Special Issue Accelerating Renewable Energy Transition Post Major World Events
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Abstract

To date, roadmaps and policies for transitioning from fossil fuels to clean, renewable energy have been developed for nations, provinces, states, cities, and towns in order to address air pollution, global warming, and energy insecurity. However, neither roadmaps nor policies have been developed for large metropolitan areas (aggregations of towns and cities), including megacities (metropolitan areas with populations above 10 million). This study bridges that gap by developing roadmaps to transition 74 metropolitan areas worldwide, including 30 megacities, to 100% wind, water, and sunlight (WWS) energy and storage for all energy sectors by no later than 2050, with at least 80% by 2030. Among all metropolitan areas examined, the full transition may reduce 2050 annual energy costs by 61.1% (from $2.2 to $0.86 trillion/yr in 2013 USD) and social costs (energy plus air pollution plus climate costs) by 89.6% (from $8.3 to $0.86 trillion/yr). The large energy cost reduction is due to the 57.1% lower end-used energy requirements and the 9% lower cost per unit energy with WWS. The air pollution cost reduction of ~$2.6 (1.5–4.6) trillion/yr is due mostly to the saving of 408,000 (322,000–506,000) lives/yr with WWS. Global climate cost savings due to WWS are ~$3.5 (2.0–7.5) trillion/yr (2013 USD). The transition may also create ~1.4 million more long-term, full-time jobs than lost. Thus, moving to 100% clean, renewable energy and storage for all purposes in metropolitan areas can result in significant economic, health, climate, and job benefits.

1. Introduction

Megacities and metacities are defined as metropolitan areas with populations above 10 and 20 million, respectively [1]. A metropolitan area (or metropolis) is a “major city together with its suburbs and nearby cities, towns, and environs over which the major city exercises a commanding economic and social influence” [2]. An area must have a population of at least 100,000, with at least 50,000 in the urban portion, to be considered a metropolitan area [2].
In 1950, the only megacities in the world were the New York–Newark and Tokyo metropolitan areas [1]. By 2020, this count had risen to 34, including nine metacities [3]. The largest of these were Tokyo (37.4 million), Delhi (30.3 million), Shanghai (27.1 million), and São Paulo (22.0 million) [3]. Based on current trends from [3], the number of megacities is expected to grow substantially by 2050. Furthermore, the physical expansion of megacities has been rapid. For example, between 2000 and 2009, the urban extent of Beijing quadrupled [4] and those of Delhi and Los Angeles increased by ~80% and ~23%, respectively [5]. Such increases in urban extent, even before considering concomitant changes in emissions, had notable impacts on air pollution and meteorology [4,5].
The addition of people to a megacity increases overall energy consumption, thereby increasing overall megacity emissions. However, this increase in energy consumption is not necessarily linear. For example, Facchini et al. [6] found that per capita energy consumption decreased with increasing population density according to a power law characterized by a −3/4 scaling. Emissions from energy consumption also depend on emission control technologies and the efficiencies of appliances and machines used.
Addressing climate and pollution problems requires policies implemented at national, regional, and local levels. To that point, by late 2020, 165 U.S. cities and towns [7] and at least 250 international cities [8] had passed resolutions or ordinances committing to being powered by 100% renewable electricity. Fifty of these international cities had committed to 100% renewables in more than one sector (e.g., transport, building heating/cooling, etc., in addition to electricity) [8].
Several previous studies have analyzed or reviewed some of the components necessary to transition individual cities or islands to clean, renewable energy (e.g., [9,10,11,12,13,14,15,16]). Many studies have also examined the ability of 100% or near 100% renewable energy to keep the electric power grid stable in one or multiple countries (e.g., [17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48]).
However, to date, no roadmap has been developed for a metropolitan area, let alone a megacity, to transition all energy sectors (electricity, transport, building heating/cooling, industry, agriculture/forestry/fishing, and the military) to 100% clean, renewable energy and storage. Moreover, the benefits to air pollution health and climate resulting from a transition to 100% clean, renewable energy remain wholly unexplored for metropolitan areas.
The goal of this paper is to provide such roadmaps for 74 metropolitan areas worldwide (including 30 megacities) to transition to 100% clean, renewable energy for all purposes by no later than 2050 (and ideally sooner), with at least 80% transition by 2030. These cities, collectively, represent about 9% of the projected 2050 world population. This paper builds upon a previous study that developed roadmaps for 53 individual towns and cities (rather than metropolitan areas) solely in North America [15].
The roadmaps here assume that all energy sectors will use electricity or direct heat. All electricity and direct heat will be generated with 100% wind, water, and sunlight (WWS). Some electricity will be used to produce hydrogen, primarily for transportation. The direct heat will come from either solar or geothermal sources. Electric heat pumps will provide remaining low-temperature heat. Less total energy will be needed because electrification of all energy sectors will lower energy demand. Because several WWS generators are intermittent, some electricity, heat, cold, and hydrogen will need to be stored. Finally, transmission lines will be needed to transmit electricity short and long distances.
Each roadmap provides a clean, renewable energy scenario for a metropolitan area to meet annual average all-purpose energy loads in 2050. This study assumes that each metropolitan area is connected to the heat and electricity grids of the country or region wherein the metropolitan area resides. The study does not attempt to quantify the energy mix needed, the storage needed, or the additional transmission/distribution needed to meet minute-by-minute energy demand. However, the study does provide an estimate of the additional levelized cost of energy (LCOE) needed to match such demand continuously; thus, it accounts for the cost of WWS supply, storage, and transmission/distribution needed to keep the grid stable. This estimate is based on results from a previous study focused on meeting demand with supply and storage in 24 world regions encompassing 143 countries [33]. All metropolitan areas examined here reside in one of those countries.

2. Methodology

This section describes the methodology for developing year 2050 roadmaps to transition each metropolitan area to 100% WWS among all energy sectors. First, country-specific data were obtained from [33], who developed all-sector energy roadmaps for 143 countries. Such data included 2016 business-as-usual (BAU) end-use energy consumption data for all energy sectors (residential, commercial, transport, industrial, agriculture/forestry/fishing, and military), for each energy type (oil, natural gas, coal, electricity, waste heat, solar and geothermal heat, and biofuels and waste), for each of 143 countries [49]. These data were projected for each country, sector, and fuel type from 2016 to 2040 using “BAU reference scenario” projections for the same sectors and fuel types for 16 world regions from [50]. The projections for a given country were assigned from those of the region in which the country resided. The reference scenario is one of moderate economic growth and accounts for policies in different countries, population growth, economic and energy growth, the growth of some renewable energy, modest energy efficiency measures, and reduced energy use. Consumption of each fuel type in each sector in each country was then extrapolated in [33] from 2040 to 2050 using a 10-year moving linear extrapolation.
In [33], the 2050 BAU energy for each fuel type in each sector and country was then transitioned to 2050 WWS electricity and heat. WWS electricity generators included onshore and offshore wind turbines, rooftop and utility-scale solar photovoltaics (PV), concentrated solar power (CSP) plants, tidal and wave devices, geothermal electric power plants, and existing hydroelectric power plants (no new reservoirs were assumed). WWS heat generators included solar and geothermal heat.
Thus, for example, the source of building heat was converted from fossil fuels or bioenergy to air- and ground-source heat pumps running on WWS electricity and direct solar thermal or geothermal heat. Building cooling was also provided by heat pumps.
Fossil fuel and biofuel vehicles were transitioned primarily into battery electric (BE) vehicles and some hydrogen fuel cell (HFC) vehicles, where the hydrogen in that case was produced using WWS electricity (i.e., green hydrogen). BE vehicles were assumed to dominate short- and long-distance light-duty ground transportation, construction machines, agricultural equipment, short- and moderate-distance trains (except where powered by electric rails or overhead wires), ferries, speedboats, short-distance ships, and short-haul aircraft traveling under 1500 km. HFC vehicles were assumed to make up all long-distance, heavy payload transport by road, rail, water, and air.
High-temperature industrial processes were electrified with electric arc furnaces, induction furnaces, resistance furnaces, dielectric heaters, and electron beam heaters.
Next, in each country, a mix of WWS resources was estimated to meet the all-sector annual-average end-use energy demand. The mix was determined after a WWS resource analysis was performed for each country. Air pollution and climate damage in 2050 were estimated for each country, and the social cost benefits of reducing such damage with WWS were then calculated. Energy costs between BAU and WWS were also calculated, as were the required land areas and changes in the number of jobs.
In [33], country populations were projected to 2050 with data from [51]. Here, metropolitan area populations are extrapolated linearly to 2050 from 2000–2020 population data [3]. Here, the ratio of metropolitan area-to-country population in 2050 is then used to scale down all country energy data from [33] to the metropolitan area level. While this is a simplistic method that does not account for the fact that urban energy consumption decreases with increasing population density [6], the country-level analysis that it relies on is detailed. In addition, urban energy consumption includes energy used to transport people, goods, heat, and electricity to and from urban areas, which is not accounted for if energy consumption is scaled by urban population. As such, the overestimate of urban energy consumption based on linear population scaling may be at least partly offset by the underestimate of energy consumption due to transport to and from a metropolitan area.

3. Results and Discussion

3.1. Resulting End-Use Demand and Nameplate Capacities of New Generators

Table 1 provides the resulting BAU and WWS end-use power demand (load) in 2050 for each metropolitan area. In 2016, the 74 metropolitan area all-purpose, end-use load was ~1730 GW (15,100 TWh/yr). Under BAU, the all-purpose end-use load is estimated to increase to ~2540 GW in 2050 (Table 1). A move to 100% WWS by 2050 reduces the 74-metropolitan-area end-use load by ~57.1%, down to ~1090 GW (~9550 TWh/yr) (Table 1), with the largest percentage reduction (37.5%) due to the efficiency of WWS heat pumps, battery electric vehicles, hydrogen fuel cell vehicles, and industrial heat, when compared with their business-as-usual equivalents. An additional 12.9% reduction is due to eliminating the energy needed to extract, transport, and refine fossil fuels and uranium. The remaining 6.7% reduction is due to end-use energy efficiency improvements and reduced energy use beyond those under BAU. Megacities with the greatest all-purpose end-use WWS load needed in 2050 include Shanghai (80.7 GW), Tokyo (70.1 GW), Beijing (63.0 GW), New York City (45.5 GW), Seoul (36.3 GW), Shenzhen (35.6 GW), and Moscow (35.2 GW).
Table 1. Business-as-usual (BAU) and wind, water, and sunlight (WWS) end-use energy load by sector and city. First row for each city: Estimated 2050 total annually averaged end-use load (GW) and percent of the total load by sector if conventional fossil fuel, nuclear, and biofuel use continue from today to 2050 under a BAU trajectory. Second row for each city: Estimated 2050 total end-use load (GW) and percent of total load by sector if 100% of BAU end-use all-purpose delivered load in 2050 is instead provided by WWS. The last four columns show the percent reductions in total 2050 BAU load due to switching from BAU to WWS, including the effects of (a) energy use reduction due to the higher work-to-energy ratio of electricity over combustion, (b) eliminating energy use for the upstream mining, transporting, and/or refining of coal, oil, gas, biofuels, bioenergy, and uranium, and (c) policy-driven increases in end-use efficiency and demand reduction beyond those in the BAU case.
Table 2 summarizes the 2050 percent of annual-average end-use load summed among all metropolitan areas (from Table 1) to be met by each energy generator type. It also provides the new plus existing nameplate capacities of each generator type needed to meet such load, the nameplate capacities of existing generators of each type, and the capital cost of the new nameplate capacities, all summed among the metropolitan areas.
Table 2. (a) Percent of 2050 all-purpose end-use load met by each energy generator, averaged among all metropolitan areas. (b) Estimated nameplate capacities of WWS generators needed to meet annual average all-purpose energy demand. (c) Nameplate capacities of WWS generators existing in 2018. (d) Percent of 2050 needed nameplate capacity existing in 2018, which equals Column (c) divided by Column (b). (e) Capital cost of new generators needed to meet annual average power by 2050.
The average mix of generators in Table 2 is the end-use-load-weighted average mix of generators in each metropolitan area, obtained from Table 3. The total new plus existing nameplate capacity is the sum of values among each metropolitan area (Table 4). Nameplate capacities for each area are determined from the end-use WWS load for the metropolitan area (Table 1), the mix of generators for the area (Table 3), and the product of the capacity factor and the transmission and distribution efficiency of each generator type in each area (Table 5).
Table 3. Percent of the annually averaged 2050 metropolitan area all-purpose end-use WWS load (not nameplate capacity) in Table 1 to be met with the given type of electric power generator. Each row sum to 100%.
Table 4. Existing plus new nameplate capacities (MW) needed for each WWS electricity generation source in each metropolitan area to meet 2050 metropolitan area all-purpose end-use WWS load in the annual average. These capacities are determined by taking the product of end-use WWS load (Table 1) and the fraction of load met by each generator (Table 3), all divided by the product of the capacity factor and transmission/distribution efficiency (Table 5).
Table 5. 2050 product of capacity factor and transmission/distribution efficiency for each energy generating technology and metropolitan area. Values are derived for each country in [33]. Capacity factors for onshore and offshore wind account for the competition among wind turbines for limited kinetic energy (array losses). A “--” indicates no installed generators.
WWS generators are not constrained to exist within a metropolitan area due to land and renewable resource limitations in such areas. Nonetheless, all rooftop PV is proposed to exist within each metropolitan area. Table 6 provides estimated 2050 metropolitan area residential and commercial/government rooftop areas suitable for PV. It also shows the potential PV nameplate capacity in each area and the proposed installed nameplate capacity for each area (which is consistent with values in Table 4). Rooftop PV areas include existing plus new building roof areas plus elevated canopy areas above parking lots, highways, and structures. Table 6 indicates that only 22.3% of potential residential rooftop PV and 58.9% of potential commercial/government rooftop PV nameplate capacities are proposed for installation among all metropolitan areas. As such, rooftop area is not a limiting factor in transitioning to 100% WWS in these roadmaps.
Table 6. Year 2050 (a,e) rooftop areas suitable for photovoltaics (PV) panels, (b,f) potential nameplate capacities of suitable rooftop areas, (c,g) proposed nameplate capacities for 2050, and (d,h) percent of potential capacity to be installed (proposed capacity divided by potential capacity) for both residential and commercial/government buildings.
Unlike PV, concentrated solar power is viable only in countries with significant direct sunlight. Thus, CSP penetration is limited to metropolitan areas in countries exposed to significant sunlight. As such, no CSP is proposed for use in Russia, Canada, Norway, Germany, Switzerland, Ukraine, or Mongolia.
Onshore wind is available in every country. Offshore wind, wave, and tidal power are assumed to be available only in metropolitan areas located in countries with ocean or substantial lake coastlines. Thus, for example, no offshore wind is available in Ethiopia, Nigeria, Uzbekistan, Mongolia, Austria, or Switzerland.
Table 2 indicates that ~8% of the 2050 nameplate capacity required for a 100% all-purpose WWS system among all metropolitan areas was already installed as of 2018 end. Table 2 also provides the nameplate capacities of new plus existing generators needed to meet annual average all-purpose energy demand in each metropolitan area. In most areas, additional generators, storage, transmission lines, and distribution lines are needed to keep the electricity and heat grids stable continuously due to the intermittency of WWS generators. The estimated costs of such equipment are accounted for in the following section.

3.2. Energy Costs

Table 7 shows the BAU levelized costs of energy in 2015 and projected for 2050, in each metropolitan area. The LCOEs include those of keeping the BAU electricity and heat grids stable. The LCOEs were derived for the electric power sector only, but are assumed, for simplicity, to equal the LCOEs for all BAU energy. Because of the large (57.1%) reduction in end-use energy that occurs upon converting from BAU to WWS (Table 1), the uncertainty in the LCOE of non-electricity versus electricity BAU energy is small, so makes no difference in the conclusions drawn here.
Table 7. (a) Mean year 2050 capital cost estimate for new generators to meet annual average WWS electric power demand after electrification of all energy sectors (this does not include the additional generators beyond those needed for annual average power in Table 2). (b) Mean values of the private levelized cost of energy (LCOE) for conventional fuels (BAU) in the electricity sector in 2015, which is assumed to be the LCOE for all BAU energy. LCOE estimates do not include externality costs and are assumed to account for meeting continuous load (thus accounting for grid stability). (c) Same as (b), but for 2050. (d) Same as (b), but for WWS averaged over all energy sectors in 2050 and for generators to meet annual average load. (e) Same as (b) but for WWS averaged over all energy sectors in 2050 and for generators, storage, transmission/distribution, and demand response to meet continuous load (thus accounting for grid stability). (f) Mean private energy cost savings per person per year due to switching from BAU to WWS in all energy sectors in 2050. (g) Mean estimates by metropolitan area of 2050 air pollution health and non-health cost savings per person per year due to switching to WWS. (h) Mean estimates of climate cost savings to the world per person per year due to switching to WWS. (i) Mean estimates of private energy plus health plus climate cost savings per person per year in the metropolitan area due to switching to 100% WWS. All costs are in 2013 USD.
Table 7 also shows the capital cost of the WWS infrastructure needed to meet annual average end-use power demand (load), the 2050 WWS LCOE needed to meet annual average load, and the 2050 WWS LCOE needed to meet continuous load (thus to keep the electric and heat grids stable). Footnote (e) of Table 7 describes the methodology for deriving the LCOE of WWS needed to meet continuous load. Finally, Table 7 provides the private and social cost savings of using WWS instead of BAU energy.
The total capital cost of all WWS infrastructure needed to meet annual average power for all metropolitan areas is $7.25 trillion (Table 7, 2013 USD) for 3903 GW of new WWS generators (Table 2). This results in a capital cost of ~$1.86 million per MW. Shanghai requires the greatest capital input ($513 billion), followed by Tokyo ($443 billion), then Beijing ($401 billion).
The LCOE accounts for capital, land, operating, maintenance, fuel, short- and long-distance transmission, distribution, and decommissioning costs. Table 7 indicates that the mean BAU LCOE in 2013 USD increased only ~1.9% between 2015 and 2050 (from 9.72 to 9.9 ¢/kWh), increasing in many locations but decreasing in others. However, the 2050 WWS LCOE (9.0 ¢/kWh) for meeting continuous end-use load, averaged over all metropolitan areas, was about 9.1% less than the 2050 BAU LCOE (9.9 ¢/kWh) due to the projected drop in WWS generator cost due to both economies of scale and improvements in WWS technologies.
The 2050 LCOE needed to meet continuous load with WWS (9.0 ¢/kWh) was about 18% higher than that required for meeting annual average load with WWS (7.6 ¢/kWh) (Footnote (e) of Table 7). The difference (1.4 ¢/kWh) is similar to the 1.35 ¢/kWh difference found among 139 countries in [32] and the 1.39 ¢/kWh difference found among 143 countries in [33]. The higher cost of meeting continuous load than annual average load with WWS was due to (1) the need to overbuild WWS to meet continuous load, (2) the need for more electricity, heat, cold, and hydrogen storage to meet continuous load, and (3) the need for more transmission and distribution lines to meet continuous load.
Combining the 57.1% lower energy requirement (Table 1) with the 9% lower LCOE (Table 7) in the WWS case gives a 61.1% lower annual energy cost ($0.86 instead of $2.2 trillion/yr, in 2013 USD) with WWS (Table 8). This energy cost savings translates to a benefit of ~$1500 per person per year in 2050 (Table 7). The annual health and climate cost savings per person due to converting to WWS are even larger, an average of $2500 and $4300 per person per year, respectively (Table 7). The average energy plus air pollution health plus climate cost (i.e., the total social cost) savings of WWS over BAU is thus $8200 per person per year (Table 7), or $7.4 trillion/yr among all people in all metropolitan areas (Table 8).
Table 8. (a) BAU annual energy cost, (b) BAU annual air pollution cost (from mortalities, morbidities, and non-air pollution effects) due to energy, (c) BAU annual climate cost due to energy, (d) BAU annual total social (energy+air pollution+climate) cost, (e) WWS annual social cost (= energy cost), and percent reduction in (f) energy cost and (g) social cost due to transitioning from WWS to BAU. All costs are in 2013 USD.
The social cost savings is greatest in locations with high CO2 emissions per capita. Social costs here do not include the insurance cost against nuclear accidents, the costs of conflicts over fossil fuel resources, groundwater pollution costs, lower land values due to mining and drilling operations, or costs of road repair due to road transport of fossil fuel extraction equipment and the fuels themselves.

3.3. Air Pollution Cost Reductions due to WWS

Air pollution contributes to death from heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory tract infection, lung cancer, and asthma. Common types of COPD are chronic bronchitis and emphysema. Common types of lower respiratory tract infections are the flu, bronchitis, and pneumonia [52]. In 2016, 56.9 million people died worldwide from all causes [53]. Air pollution may cause between 24% and 45% of the deaths for each of five out of the six leading causes of death [53]. About 4.5 million people died prematurely from outdoor air pollution and 7.1 million died from indoor plus outdoor air pollution in 2016 [53]. Thus, about 12.5% of all deaths worldwide in 2016 were due to indoor plus outdoor air pollution, making it the second leading cause of death after heart disease. The authors of [33] estimated that, in the 143 countries examined, 6.8 million people died prematurely due to air pollution in 2016, and 5.3 million may die prematurely per year in 2050. The reduction is due to some BAU improvements in emission control technologies.
Scaling the 2050 individual country numbers from [33] by population to each metropolitan area gives approximately 408,000 (322,000–506,000) premature deaths per year in these areas in the BAU case (or avoided deaths in the WWS case) (Table 9). The greatest numbers of premature deaths occur in Delhi (45,200/yr), Shanghai (38,500/yr), Beijing (30,100/yr), Lagos (25,600/yr), Dhaka (23,700/yr), and Mumbai (23,300/yr).
Table 9. (a) Year 2050 estimated population by metropolitan area (bold indicates a megacity, whose population exceeds 10 million). Year 2050 (b) high, (c) mean, and (d) low avoided air pollution premature mortalities by metropolitan area due to transitioning to 100% WWS. (e) Mean avoided air pollution cost (from avoided mortalities, morbidities, and non-air pollution effects) per unit BAU-energy from all sectors due to converting each metropolitan area to 100% WWS for all energy purposes. (f) 2017 estimated percent of global energy-related carbon-dioxide-equivalent (CO2e) emissions due to the metropolitan area. 2050. (g) 2050 mean avoided climate-change costs to the world per unit BAU-energy from all sectors due to converting each metropolitan area to 100% WWS for all energy purposes. All costs are in 2013 USD.
The damage cost due to air pollution from fossil fuel and biofuel burning and evaporative emissions in a metropolitan area is the sum of mortality, morbidity, and non-health costs. Non-health costs include costs from lower visibility and agricultural losses. Mortality, morbidity, and non-health costs are estimated as in [33]. The avoided air pollution cost among all metropolitan areas due to transitioning to 100% WWS is ~$2.6 ($1.5–$4.6) trillion/yr (Table 8), or ~11.5 (6.5–20.5) ¢/kWh-BAU-all-energy (Table 9), which translates to a mean of $2500/yr per person (2013 USD) (Table 7).

3.4. Global-Warming Damage Costs Eliminated

Damage arising from global warming includes damage from higher sea levels (coastal infrastructure losses), reduced crop yields for certain crops, more intense hurricanes, more droughts and floods, more wildfires and air pollution, more migration due to crop losses and famine, more heat stress and heat stroke, more malaria and dengue fever, fishery and coral reef losses, and greater air cooling requirements, among other impacts. These costs are partly offset by fewer extreme cold events and concomitant decreases in illness and mortality, and the increase in agricultural output in some regions.
The damage caused by carbon dioxide equivalent (CO2e) emissions to the global economy through their impacts on climate is quantified with the social cost of carbon (SCC). The SCC is usually expressed in cost per metric tonne-CO2e emissions. The SCC from several recent studies is estimated for 2050 as ~$500 (282–1060)/metric tonne-CO2e in 2013 USD [33]. Multiplying the SCC by estimated 2050 CO2e emissions in each metropolitan area suggests that BAU emissions from the metropolitan areas here may cause $3.5 (2.0–7.5) trillion/yr in climate losses to the world by 2050 (Table 8), or 15.8 (8.9–33.7) ¢/kWh-BAU-all-energy (Table 9), which translates to ~$4300/yr per person (in 2013 USD) (Table 7). Transitioning to 100% WWS will avoid these costs.

3.5. Impacts of WWS on Job Creation and Loss

Governments are concerned about changes in employment upon transitioning their energy economies to entirely clean, renewable energy ones. Here, the numbers of long-term, full-time jobs created and lost are estimated for each metropolitan area. Job changes may not necessarily occur in the metropolitan area itself, but at least in the state, province, or country wherein the metropolitan area resides.
The calculation is done starting with the 2050 country job production and loss numbers from [33], determined for 143 individual countries for meeting annual average load and, separately, for 24 world regions encompassing the 143 countries, for meeting continuous load. That study relied substantially on results from NREL Jobs and Economic Development Impact (JEDI) Models [56]. Job production and loss for individual countries (after removing jobs created for producing generators beyond those needed to meet annual average load) were scaled by population to job production and loss for individual megacities. Those numbers were then scaled further by the LCOE needed to meet continuous load (Column (e) of Table 7) to that needed to meet annual average load (Column (d) of Table 7). This ratio mostly exceeds unity but is less than unity for some countries or regions (e.g., in Canada, Iceland, New Zealand, and Russia) where the initial number of generators estimated to meet annual average load was too high compared with what was needed to meet continuous load [33]. When the ratio exceeds unity, the additional jobs are for installing and operating additional electricity and heat generators; additional electricity, heat, cold, and hydrogen storage equipment; and additional transmission and distribution lines needed to meet continuous load rather than annual average load.
Jobs created include onsite (direct) jobs, local revenue and supply chain (indirect) jobs, and induced jobs. Indirect jobs include jobs associated with construction material and component suppliers, analysis and attorneys who assess project feasibility and negotiate agreements, banks financing the project, all equipment manufacturers, and manufacturers of blades and replacement parts. Indirect manufacturing jobs are included in the number of construction jobs. Induced jobs result from the reinvestment and spending of earnings from direct and indirect jobs. They include jobs resulting from increased business at local restaurants, hotels, and retail stores, and for childcare providers.
Table 10 suggests that a 100% conversion to WWS across the metropolitan areas may create ~2.3 million new long-term, full-time construction jobs and ~2.3 million new plus existing long-term, full-time operation plus maintenance jobs, totaling ~4.6 million new plus existing long-term, full-time jobs for WWS generators and transmission.
Table 10. Estimated numbers of 2050 new long-term, full-time (a) construction and (b) operation jobs produced due to converting to 100% WWS. (c) Job losses due to the transition. (d) Long-term, full-time construction plus operation jobs produced minus jobs lost. Annual earnings corresponding to new (e) construction and (f) operation jobs produced. (g) Net earnings from new construction plus operation jobs produced minus jobs lost due to converting to 100% WWS. Costs are in 2013 USD.
Job losses due to a transition to WWS will include losses of jobs to extract, transport, and process fossil fuels, bioenergy, and uranium. Job losses will also occur in the BAU electricity generation industry and in the manufacturing of appliances that use combustion fuels. Finally, jobs will be lost upon ceasing the construction of BAU electricity generation plants, petroleum refineries, and oil and gas pipelines.
Overall, shifting to 100% WWS is estimated to result in ~3.2 million jobs lost in the fossil fuel, bioenergy, and nuclear industries by 2050 (Table 10). Subtracting jobs lost from jobs created gives a net of ~1.4 million long-term, full-time jobs created among the metropolitan areas due to replacing fossil fuel, bioenergy, and nuclear generation among all sectors with WWS generation and transmission (Table 10). Job earnings show a net gain of ~$110 billion/yr (2013 USD) (Table 10).
Metropolitan areas in countries with significant fossil extraction may experience net job losses in the energy production sector. Several such metropolitan areas include Abidjan, Addis Ababa, Baghdad, Calgary, Caracas, Edmonton, Kinshasa, Lagos, Moscow, Oslo, Tehran, Toronto, and Yangon. These losses may be offset by the manufacturing, servicing, and exporting of machines and appliances associated with WWS energy (e.g., electric vehicles, fuel cell vehicles, electric heat pump air and water heaters, electric heat pump dryers, induction cooktops, etc.). Neither those jobs produced nor the jobs lost producing the equivalent machines and appliances replacing them were included in the job calculations here.

4. Conclusions

Transitioning 74 metropolitan areas, including 30 megacities, to 100% wind, water, and solar energy and storage for all energy purposes has the potential to prevent ~408,000 (322,000–506,000) premature air-pollution mortalities/yr in 2050. This, along with non-mortality impacts, avoids a 2050 air pollution cost of ~$2.6 (1.5–4.6) trillion/yr, or a mean of 11.5 ¢/kWh-BAU-all-energy (2013 USD). Transitioning also avoids ~$3.5 (2.0–7.5) trillion/yr (a mean of 15.8 ¢/kWh-BAU-all-energy) in 2050 global warming costs, ~$1.35 trillion/yr (a mean of 0.9 ¢/kWh-BAU-all-energy) in 2050 energy costs, and energy plus health and climate costs of ~$7.4 trillion/yr (a mean of 27.3 ¢/kWh-BAU-all-energy). These translate to ~$1500/person/yr in energy cost savings and ~$6700/person/yr in health plus climate cost savings. Finally, transitioning creates ~1.4 million more new long-term, full-time jobs than lost and stabilizes energy prices.
Due to the current severity of air pollution, global warming, and energy insecurity problems worldwide, a transition to 100% WWS should occur no later (and ideally earlier) than 2050, with at least 80% by 2030 [32,33]. Although a natural transition is currently occurring due to decreases in WWS generation and storage costs, such a timeline can be met only with aggressive policies.
Because metropolitan areas consist of a core city surrounded by other towns and cities, effective policies in a metropolitan area are best instituted if the cities and towns making up the area act in a unified manner rather than in piecemeal fashion. In many countries, each town and city in the area must pass its own resolutions and ordinances; nonetheless, such resolutions and ordinances can be proposed in sync or at least with consistent goals. Sometimes, the competition among towns and cities in a metropolitan area can increase the aggressiveness of policies adopted among these entities. Given that transitioning to 100% WWS for all energy purposes presents minimal downside, metropolitan areas and their constituent towns and cities have significant motivation to transition.

Author Contributions

Conceptualization: M.Z.J. methodology: M.Z.J. coordination: A.-K.v.K. data gathering and analysis: M.Z.J., Z.F.M.B., S.J.C., C.J., C.T., D.N., Y.S., and K.D.W. writing: M.Z.J. editing: Z.F.M.B., S.J.C., C.J., A.-K.v.K., A.J.H.N., D.N., M.S., Y.S., C.T., and K.D.W. visualization: A.J.H.N., C.D.W., and M.S. All authors have read and agree to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

We would like to thank Chengliang Fan, Julia M. Leal, and Sabrina Mengrani for assistance with the study. The spreadsheet containing the derivation of all data can be found here: https://web.stanford.edu/group/efmh/jacobson/Articles/I/143Countries-Megacities.xlsx. The roadmaps described here are summarized in infographic maps that area available here: https://sites.google.com/stanford.edu/wws-roadmaps/home.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
BAUBusiness-as-Usual
BEBattery Electric
CO2eCarbon Dioxide Equivalent
COPDChronic Obstructive Pulmonary Disorder
CSPConcentrated Solar Power
EIAEnergy Information Administration
GWGigawatt
HFCHydrogen Fuel Cell
JEDIJobs and Economic Development Impact
LCOELevelized Cost of Energy
LCOEALCOE to meet annual average load
LCOECLCOE to meet continuous load
MWMegawatt
NRELNational Renewable Energy Laboratory
PVPhotovoltaic
SCCSocial Cost of Carbon
TWTerawatt
TWhTerawatt-hour
USDUnited States Dollars
WWSWind, Water, and Sunlight (or Solar)

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