Metrics for the sustainable development goals: renewable energy and transportation

Jonathan J. Buonocore (), Ernani Choma, Aleyda H. Villavicencio, John D. Spengler, Dinah A. Koehler, John S. Evans, Jos Lelieveld, Piet Klop and Ramon Sanchez-Pina
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Jonathan J. Buonocore: Harvard T.H. Chan School of Public Health
Ernani Choma: Harvard University
Aleyda H. Villavicencio: Harvard T.H. Chan School of Public Health
John D. Spengler: Harvard T.H. Chan School of Public Health
Dinah A. Koehler: UBS Asset Management
John S. Evans: Harvard T.H. Chan School of Public Health
Jos Lelieveld: Max Planck Institute for Chemistry
Piet Klop: PGGM
Ramon Sanchez-Pina: Harvard T.H. Chan School of Public Health

Palgrave Communications, 2019, vol. 5, issue 1, 1-14

Abstract: Abstract The private sector is interested in contributing to the United Nations (UN) Sustainable Development Goals (SDGs); however, they lack credible objective metrics to measure progress, which hinders making a case for financial investing toward the SDGs. A set of science-based metrics could allow corporations and interested investors to meaningfully align their actions with the SDGs in locations around the world where they can make the greatest positive impact. Using existing data on country-level electricity generation and land transportation, we develop a set of simple-to-implement and user-friendly metrics to evaluate the benefits that investments in renewable electricity generation and improvements in land transportation can make toward reducing CO2 and air pollutant emissions and the health impacts of air pollution. We then apply these metrics to a set of renewable electricity companies and find meaningful differences in their progress toward the SDGs on health, energy, and climate. We found that under half of the renewable energy companies in our dataset disclose country-level data on where equipment is being sold, and that there is substantial variability in the CO2 reductions and health benefits of renewable energy based on where these companies have installed capacity. There was not a close statistical relationship between country CO2 emissions rates and country health impact rates, indicating that these metrics cannot serve as good proxies for one another. Future improvements to this methodology should be to implement explicit tracking of air pollution from sources to the locations where it has eventual health impacts, updating the underlying dataset, and improving the degree of detail in emissions inventories. Application of this methodology across the renewable energy sector is limited by the availability of country-level data on where a company has renewable energy capacity installed. The methodology developed here can serve as a basis for better measurement of progress toward climate, energy, and health-related SDGs in financial investing and other applications.

Date: 2019
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DOI: 10.1057/s41599-019-0336-4

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