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

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.

Health Benefits from Renewable Electricity Sources: A Review

“…Italia 1 [46] 74 metropolitan areas 1 [47] Table 4. Studies included in the SLR and their methodology (source: own elaboration).…”

“…Specificities Description [36] Simulation of replacement of fossil fuels for wind and solar projects in several US locations from 2009 to 2011 [25] Simulation of replacement of natural gas with wind power in two locations: a 580 MW wind farm in California and a 22 MW wind farm in Idaho [38] Simulation of conversion of California's all-purpose energy infrastructure to one relying exclusively on RESs [39] Simulation of the health co-benefits of four different EE/RES installation types (two of RESs) in six different locations in the US [40] Simulation of the replacement of coal-fired plants with RESs and estimation of the associated health co-benefits [28] Simulation of implementation of two offshore wind power facilities in two different locations and in two years (2012 and 2017) [33] Simulation of use of hydrogen (collected from RESs) in a natural-gas-fueled combined cycle power plant [42] Simulation of a 17% share of solar photovoltaic generation in the electricity generation mix in the Eastern US [46] Simulation of hydrogen (produced using RESs) use in hydrogen mobility and hydrogen injection in the natural gas grid/pipeline in three different locations in Italy [47] Simulation of the transition to 100% RESs in all energy sectors in 74 Metropolitan Areas until 2050 [29] Scenario comparison Simulation of wind power growth in the US from 2013 to 2050, comparing different scenarios (different shares) [32] Simulation of different scenarios for the evolution of Renewable Portfolio Standards in the US, from 2015 to 2050 [30] Simulation of evolution of sub-national RPS or carbon pricing in the US until 2030 [45] Simulation of an expansion of electricity generation and estimation of the health co-benefits of using RESs (promoted by RPS) instead of fossil fuels [34] Simulation of the evolution of energy demand and carbon emissions in China, from 2020 to 2050, in response to different climate policies [48] Simulation of different penetration shares of Electric Vehicles (EVs) powered exclusively with RESs in a large metropolitan area [23] LCA/Scenario comparison Simulation of an increasing share of distributed generation (RESs) and estimation of resulting health co-benefits under different carbon tax levels from 2006 to 2008 [21] Simulation of replacement of centralized generation for distributed generation of two types of grid-connected photovoltaic panels and three types of micro-wind turbines [31] LCA Simulation of RES growth from 2010 to 2030 in Taiwan [43] Simulation of use of small-sized trees to generate electricity instead of disposing them…”

“…obtain direct health co-benefits. Solar, Wind, Hydrogen [33] Solar, Wind, Hydrogen, Geothermal [46] Solar, Wind, Hydropower, Geothermal [47] Wind, Geothermal, Biomass, Waste, Hydropower [31] [32]…”

“…Table 7 summarizes the pollutants included in each study. NO 2 , PM 2.5 [33] PM 2.5 , O 3 [38] CO 2 and non-specified air pollutants [47] As can be seen in Table 7, most studies include both types of benefits since they include CO 2 and other "traditional air pollutants". The most frequent pollutants considered in the studies are Sulfur Dioxide (SO 2 ), Oxides of Nitrogen (NO x ), and Carbon Dioxide (CO 2 ), combined with other pollutants.…”

Improving energy efficiency of rental housing

“…An increase in energy efficiency will take place during the building (31%) or reconstruction process (47%) [9]. Mark Z. also, using the foreign cities example, shows us that there can be a reduction in annual energy costs by 61.1% by 2050 and social-energy costs when implementing the strategy for using renewable energy sources in buildings [10].…”