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A Moonshot for Sustainability Assessment Stefano Cucurachi* and Sangwon Suh Bren School of Environmental Science and Management, University of California, Santa Barbara, California 93106, United States greenhouse gases (GHGs). Therefore, QSAs would need to take into account multiple criteria and their synergies and tradeoffs. Such criteria should include not only a multitude of environmental impacts but also social and economic aspects. Recent advances in life cycle assessment (LCA) to embrace socio-economic impacts are encouraging.1 LCA allows quantifying the life cycle impacts of a product system using a wide range of indicators (e.g., depletion of natural resources, contribution to climate change). However, LCA has yet to further evolve into a tool for a comprehensive sustainability assessment. Second, QSAs need to embrace causal relationships in their analysis. The implementation of the SDGs will create a complex network of policy actions and their outcomes, overlaid by ongoing changes in the society and the environment. Understanding the actions and their consequences under this condition is not easy. SDG number 14, for example, states “Conserve and sustainably use the oceans, seas and marine resources for sustainable development”, which includes, for example, the specific target of “reducing the loss of marine species” (i.e., target 14.2 in the SDGs). A statistically sound causal analysis can help determine the strength of the causal link between an action “We choose to go to the Moon [...]; because that goal will (e.g., reducing and enforcing fishing quota) and its outcome serve to organize and measure the best of our energies and (e.g., increasing diversity of marine species). In the field of skills; because that challenge is one that we are willing to economics and ecology, innovative approaches have been accept, one we are unwilling to postpone, and one we intend developed to analyze causal relationships in complex systems.2 to win. . .” For the irreversible, large-scale changes that SDGs and corresponding policy actions may induce, however, existing U.S. President John F. Kennedy, Rice University, 1962. approaches focusing on historical data exhibit significant Early in April this year, the United Nations deliberated on how limitations. to implement the 17 Sustainable Development Goals (SDGs) Third, a policy-maker faces the problem of decision-making and their related 169 targets that will be launched in this under uncertainty. Decisions are seldom supported by perfect September. The International Council for Science recognized information, and no QSA provides uncertainty-free results. A that SDGs offer major improvements on the Millennium rigorous uncertainty analysis with the output of QSA provides Development Goals that they substituted. The implementation policy-makers the opportunity to evaluate the value of the list well covers the social, economic and environmental information that QSAs generate.3 Although the application of components of sustainability. Clearly the SGDs and their techniques of uncertainty analysis has yet to become standard implementation processes pose an unprecedented challenge to practice in the sustainability sciences, recent advances allow policy makers; so do they to sustainability scientists, including identifying the key drivers of uncertainty and to conduct an those who are engaged in quantitative sustainability assessment uncertainty analysis for models of great complexity at a limited (QSA). Science-based QSAs are the key to monitor the computational cost.4 Further efforts are needed to support the progress of and support the decisions on the 17 SDGs. development of protocols to adequately characterize uncerHowever, as they currently stand, they are far from ready to tainty and to communicate it in the results of QSAs. undertake the challenge. We highlighted what we believe to be three fundamental First, QSAs need to account for potential conflicts, synergies needs for QSAs to monitor the progresses of SDGs and to and trade-offs between SDGs. SDG number 7, for example, support decision-makers. These are (1) the use of QSAs in a reads “Ensure access to affordable, reliable, sustainable and modern multicriteria setting, (2) the embracing of causal relationships energy for all.” The achievement of this goal would likely require in the assessment, and (3) the adequate characterization of expanding the energy supply infrastructure especially in the uncertainty of QSAs’ results. The biggest challenge to QSA developing and least developed world. However, this policy decision could clash with SDG number 13 that reads “Take urgent action to combat climate change and its impact”, since Received: June 19, 2015 building a new infrastructure contributes to the emission of Published: July 31, 2015 © 2015 American Chemical Society
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DOI: 10.1021/acs.est.5b02960 Environ. Sci. Technol. 2015, 49, 9497−9498
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Environmental Science & Technology toward the achievement of SDGs might be, however, the lack of cohesion among QSAs and associated disciplines. Albeit a clear scientific progress in individual disciplines, a lack of cohesion between them still limits the contribution that QSAs could give to global challenges. In order for QSAs to support the achievement of SDGs, the piecemeal, incremental improvements should give way to an unprecedented level of integration and collaboration. The three target areas that we identify can serve as the starting points from which fruitful collaborations can sprout. The stakes are unprecedented in the sustainability sciences, and so is the scale and the urgency of the involvement needed across disciplines. Sending humans to the Moon in the early 60s presented a huge systems integration challenge involving multiple domains of science and engineering that only few believed solvable.5 That goal, powerfully declared during the Rice University speech in 1962, created the epicenter that ruptured the walls between the surrounding disciplines and enabled an unprecedented level of integration among them, which eventually led the world to witness two men walking on the Moon seven years later. What could a well-defined goal do to a scientific community? SDGs are calling for another Moonshot for sustainability assessment, only orders of magnitude greater in scale.
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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REFERENCES
(1) Hellweg, S.; Mila i Canals, L. Emerging approaches, challenges and opportunities in life cycle assessment. Science (Washington, DC, U. S.) 2014, 344 (6188), 1109−1113. (2) Sugihara, G.; May, R.; Ye, H.; Hsieh, C. -h.; Deyle, E.; Fogarty, M.; Munch, S. Detecting Causality in Complex Ecosystems. Science (Washington, DC, U. S.) 2012, 338 (6106), 496−500. (3) Morgan, M. G.; Henrion, M.; Small, M. Uncertainty: a Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis; Cambridge University Press, 1992. (4) Anderson, B.; Borgonovo, E.; Galeotti, M.; Roson, R. Uncertainty in climate change modeling: can global sensitivity analysis be of help? Risk Anal. 2014, 34 (2), 271−293. (5) Johnson, S. B. the Secret of Apollo: Systems Management in American and European Space Programs; JHU Press, 2002.
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DOI: 10.1021/acs.est.5b02960 Environ. Sci. Technol. 2015, 49, 9497−9498
