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

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.


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, 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 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.
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).
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.
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. 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.

Metropolitan
Area Scenario  All values are summed or averaged over all metropolitan areas. "Annual average power" is annual average all-purpose energy demand divided by the number of hours per year. The percent of annual-average power demand met by each device type, shown in Column (a), is a demand-weighted average among the mixes given for all metropolitan areas. f No increase in the number of dams or in the peak discharge rate of hydropower is assumed. g The solar PV panels used for this calculation are SunPower E20 panels. CSP is assumed to have storage with a maximum charge to discharge rate (storage size to generator size ratio) of 2.62:1. See the footnotes to Table S7 of [31] for more details.  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.       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 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.

Energy Costs
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).
The social cost savings is greatest in locations with high CO 2 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. 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 [33]. Such BAU costs include all-distance transmission, distribution, and pipeline costs, but they exclude health and climate costs. This LCOE is assumed to apply to all BAU sectors. (c) Same as (b), but for the 2050 BAU case and using 2050 LCOEs for each generator as derived in [33]. The 2050 BAU case includes some existing WWS (mostly hydropower) plus future increases in WWS electricity in the BAU case, as well as energy efficiency measures. The cost of keeping the grid stable in the BAU case is conservatively assumed to be made possible by BAU generators, and this is accounted for in the BAU costs. This LCOE is assumed to apply to all BAU sectors. (d) The 2050 LCOE of WWS for meeting load in the annual average is found by combining the 2050 mix of WWS generators among all energy sectors by metropolitan area from Table 3 with the 2050 mean LCOEs for each WWS generator by country from [33]. (e) The 2050 LCOE of WWS for meeting continuous load is the sum of the LCOE from meeting annual average load plus the difference in cost between meeting continuous and annual average load in each metropolitan region. This difference is determined from data in [33]. That study calculated the LCOEs to meet annual average load (LCOEA) with 100% WWS in 143 countries and the LCOEs to meet continuous load (LCOEC) with 100% WWS in 24 world regions encompassing the 143 countries. The LCOEAs for each country were first averaged (weighted by end-use WWS load) to find average LCOEAs for each region. The difference between the LCOEC and LCOEA for each region was then assigned to each country in the region. The difference for each metropolitan area was then assigned as the difference in the country that the metropolitan area resided in. This difference was then added to the LCOEA from Table 7, Column (d) to obtain the value in Column (e). Note that, for some regions (Canada, Iceland, New Zealand, and Russia), the cost of keeping the grid stable was less than the estimated cost of meeting annual average load. The reason is that the number of generators estimated to meet annual average load was a rough estimate. However, the WWS resource strength (usually wind) in these countries was stronger when calculated with a weather prediction model used to predict continuous WWS supply than when estimated for determining the number of generators to meet annual average power in [33]. (f) The 2050 mean private energy cost savings per capita per year due to switching from BAU to WWS retail electricity is calculated as the cost of all energy use in the BAU case (the product of BAU end-use power from    The 2050 BAU annual energy cost is the 2050 BAU LCOE from Table 7 multiplied by the 2050 BAU end-used load from Table 1 and 8760 h per year. The 2050 BAU air pollution cost per year is the 2050 air pollution cost from energy in the country each metropolitan area resides in, from [33], multiplied by the metropolitan area-to-country population ratio. The 2050 BAU climate cost per year is derived by multiplying the 2050 climate cost to the world from energy emissions in the country that each metropolitan area in, from [33], multiplied by the metropolitan area-to-country population ratio. The climate cost due to the country's emissions assume a 2050 mid-value of the social cost of carbon (SCC) from Table S18 of [33] of $500/tonne-CO 2 e.

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.
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). 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 (CO 2 e) 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.   Metropolitan area populations between 2000 and 2020 were obtained from [3]. The full trend was then extrapolated to 2050. Avoided air pollution mortalities are calculated from country values determined in [33], then scaled by the metropolitan area-to-country population ratio. Mean ¢/kWh-BAU-all-energy equals the mean avoided annual air pollution cost from Table 8 divided by the total (all-sector) BAU end-use energy in 2050 (which equals the annual-average end-use BAU power demand from Table 1 multiplied by 8760 h/year). CO 2 e emissions are estimated from country energy-related CO 2 emissions [54] scaled by population to give metropolitan area emissions, then adjusted for non-CO 2 climate-relevant emissions, as described in [55]. Emissions are then projected to 2050 as in [33]. The avoided climate cost per unit energy is the annual mean BAU climate cost from

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 (CO 2 e) 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-CO 2 e emissions. The SCC from several recent studies is estimated for 2050 as $500 (282-1060)/metric tonne-CO 2 e in 2013 USD [33]. Multiplying the SCC by estimated 2050 CO 2 e 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.

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 creatẽ 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.   A temporary construction job is a full-time equivalent (FTE) job (one that provides 2080 h per year of work) required for building infrastructure for one year. A long-term construction job is defined as the number of consecutive temporary one-year construction jobs for L years to replace 1/L of the total nameplate capacity of an energy device every year, all divided by L years, where L is the average facility life. By way of example, suppose 40 GW of nameplate capacity of an energy technology must be installed over 40 years, which is also the lifetime of the technology. Also, suppose the installation of 1 MW creates 40 one-year construction jobs (direct, indirect, and induced jobs). In that case, 1 GW of wind is installed each year and 40,000 one-year construction jobs are required each year. Thus, over 40 years, 1.6 million one-year jobs are required. This is equivalent to 40,000 40-year jobs. After the technology life of 40 years, 40,000 more one-year jobs are needed continuously each year in the future. As such, the 40,000 construction jobs are long-term jobs. Long-term operation jobs are full-time jobs that last as long as the energy facility lasts and that are needed to manage, operate, and maintain an energy generation facility. In a 100% WWS system, long-term jobs are effectively indefinite because, once a plant is decommissioned, another one must be built to replace it. The new plant requires additional construction and operation jobs. Monetary values are in 2013 USD. Calculations are based on individual country job and monetary changes from [33] (after removing jobs created due to generators beyond those needed to meet annual average load). The calculated number, for each country that a metropolitan area resides in, is scaled by the 2050 metropolitan area-to-country population ratio and by the LCOE that results from keeping the grid stable ( Table 7, Column (e)) to the LCOE that results from meeting annual average load (Table 7, Column (d)). The job change numbers are across all energy sectors. Construction jobs are for new WWS devices only. Operation jobs are for new and existing devices. The jobs created account for new jobs in the electricity, heat, cold, and hydrogen generation, storage, and transmission (including high-voltage direct current transmission) industries. By accounting for the LCOE ratio of keeping the grid stable to meeting annual average load, the job change numbers also attempt to account for jobs created for building additional electricity and heat generators beyond those needed to meet annual average load; electricity, heat, cold, and hydrogen storage; and additional transmission and distribution lines. They do not account for changes in the numbers of jobs due to the production of electric appliances and machines or due to increasing building energy efficiency. Job losses are due to eliminating jobs for mining, transporting, processing, and using fossil fuels, biofuels, and uranium. Fossil-fuel jobs due to non-energy uses of petroleum (e.g., lubricants, asphalt, petrochemical feedstock, and petroleum coke) are retained. For transportation sectors, the jobs lost are those due to transporting fossil fuels (e.g., through truck, train, barge, ship, or pipeline). The jobs not lost are solely those for transporting other goods. The table does not account for jobs lost in the manufacture of combustion appliances, including the manufacture of automobiles, ships, or industrial machines.
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.
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.