Claiming Sustainability: Requirements and Challenges - ACS

Feb 20, 2018 - Despite the strong desire to find solutions that enable sustainable development, understanding of the requirements that methods must sa...
4 downloads 5 Views 1MB Size
Research Article pubs.acs.org/journal/ascecg

Cite This: ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

Claiming Sustainability: Requirements and Challenges Bhavik R. Bakshi,*,† Timothy G. Gutowski,‡ and Dusan P. Sekulic§ †

William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio 43210, United States ‡ Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States § Department of Mechanical Engineering, University of Kentucky, Lexington, Kentucky 40506, United States ABSTRACT: Despite the strong desire to find solutions that enable sustainable development, understanding of the requirements that methods must satisfy to guide technological development toward sustainability is still quite limited. We address this challenge based on a meta-principle for sustainability: human activities should not exceed critical ecosystem capacity, and by translating this principle into six specific requirements that sustainability assessment methods should satisfy. These necessary but not sufficient requirements are to ensure that decisions made by these methods do not demand more from ecosystems than can be supplied, and actions meant to reduce environmental impact do not shift the problem outside the system boundary. By applying these requirements to existing methods, we identify their benefits and shortcomings, and use this insight to suggest a multidisciplinary path forward. This path requires integration of methods for engineering design, with methods for considering spatial effects, socio-economic interactions, and human-natural system interactions. Such integration poses challenges and opportunities for multidisciplinary research toward solutions for sustainable development. KEYWORDS: Life cycle assessment, Eco-efficiency, Triple bottomline, Cradle to cradle, Ecosystem services, Rebound effect



INTRODUCTION The term “sustainability” is often used casually as synonymous with some kind of improvement, such as a reduction in toxic releases associated with a product, or reduced energy use, or carbon emissions. Such ambiguity is understandable given the uncertain nature of a definition of sustainability. Most definitions provided by governmental and professional agencies1 tend to be more inspirational, often with lists of things to do and consider, rather than providing real goals. This leaves the impression that trying harder will be good enough, especially by means of methods such as eco-efficiency, footprint analysis, and life cycle assessment (LCA).2 Unfortunately, such tools only look at part of the problem, and may further obscure it because individual claims of environmental improvement for a product, process or any other corporate or engineering action are often not considered in the larger context of society, the economy, and ecosystem services, but rather in an abbreviated representation of the problem. This is perhaps the natural consequence of a large-scale problem that crosses multiple boundaries. Proprietors will claim that their limited control constrains their actions. But this claim may hide the true complexity of the problem, and actions outside one’s direct boundaries may merit shared responsibility to prevent perverse outcomes. A common problem is to marry a quantitative analysis such as LCA of an engineering intervention with a highly romantic notion of how this intervention will be used by © XXXX American Chemical Society

society. This is particularly true in the evaluation of new proposed technology solutions. First, corn ethanol was going to put us on a sustainable path,3 now it is autonomous vehicles.4 Similarly, sustainability claims are being made from many products of chemistry such as starch-based materials,5,6 higher alcohols from biobased ethanol,7 and polylactic acid polymer from biomass.8 Usually, these analyses get refined as they are subjected to wider scrutiny and interdisciplinary attention. In this article, we examine selected sustainability assessment methods that are popular in industry and academic work on sustainable engineering. With guidance from a meta-principle that we propose for claiming sustainability, we develop six necessary but not sufficient conditions that sustainability assessment methods need to satisfy. We apply these conditions to popular sustainable engineering methods and find that each method suffers from many shortcomings. We use this insight to suggest a framework for a more balanced and interdisciplinary way forward. Due to its wicked nature, developing a formal definintion of sustainability is unlikely,9,10 but various frameworks have been suggested for understanding and supporting decisions toward sustainability. These include a sustainability hierarchy,11 Received: October 29, 2017 Revised: January 16, 2018

A

DOI: 10.1021/acssuschemeng.7b03953 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

Research Article

ACS Sustainable Chemistry & Engineering

acknowledge diverse flows and consider the nexus between them. 5. Account for Inputs Demanded f rom Ecosystems. Ecosystems provide goods such as water, fertile soil, and biomass; and services such as primary production, pollination, and recreational opportunities. Their demand should be quantified. 6. Account for Capacity of Ecosystems to Supply Demanded Inputs. Accounting for the supply of ecosystem goods and services demanded by specific activities is essential to determine whether these activities are within nature’s capacity. Though we acknowledge that these are highly coupled features of sustainability, it is useful to address them individually in order to assess the capabilities of individual methods. We demonstrate the application and benefits of evaluating selected methods by applying these six requirements in the next two sections.

identification of differences and requirements for developing a sustainable engineering science,10 a framework for sustainable decisions,12 and others. Many of these have been discussed in recent review articles.13,14 However, none of the existing frameworks identify requirements that sustainability assessment methods need to satisfy, assess existing methods in terms of these requirements, and provide guidelines for future directions. In the rest of this paper, after stating the meta-principle, we describe the requirements that sustainable engineering methods need to satisfy to claim sustainability. This is followed by a brief overview of some selected methods that are popular for sustainability assessment in industry and academia. We then evaluate these methods in terms of the extent to which they satisfy the six requirements. This evaluation points toward directions for further work.



REQUIREMENTS FOR SUSTAINABILITY



For technological and other interventions to contribute to sustainable development, the following meta-principle must be satisfied: Human activities should not exceed critical ecosystem capacity. A situation where this principle is violated cannot be sustained for long as it causes resource depletion, ecological degradation, and transgression of local, regional, and planetary boundaries.15,16 This is a necessary but not sufficient condition for sustainability: violating this principle means that the system is unsustainable, but satisfying it need not ensure sustainability. The lack of sufficiency is due to the wicked nature of the sustainability problem, and because in addition to this metaprinciple, sustainability also requires that the activity improve human well-being (indicated by economic feasibility) and be societally acceptable. In this work, we focus on the proposed meta-principle and its emphasis on environmental sustainability because the environment is needed for both societal and economic sustainability. Implementing this meta-principle requires quantification of the ecosystem services demanded by human activities and the capacity of relevant ecosystems to supply them. It also requires consideration of the large-scale implications of small-scale interventions to ensure that the problem does not shift outside the analysis boundaries. On the basis of these broad conditions, we propose the following specific areas that should be addressed by methods used for claiming sustainability. 1. Consider Propagation of Impacts Across Multiple Spatial Scales. The interaction of decisions meant to enhance sustainability should be considered across spatial scales, and at large scales. These scales range from that of the technological intervention to its direct and indirect impacts on the environment. 2. Consider Temporal Changes Caused by Interactions. Temporal effects of sustainability interventions depend on growth, emergent properties, type of coupling between human and natural systems, and their resilience properties. Decisions toward sustainability should also consider issues of intergenerational equity. 3. Consider Cross-Disciplinary Ef fects. Claims about sustainability need to acknowledge environmental, economic and societal domains, and interactions between them. 4. Consider Interactions Between Multiple Stocks and Flows. Sustainability is not just about improving one type of impact or efficiency. Therefore, methods need to

COMPARING SUSTAINABILITY ASSESSMENT METHODS

In this section, we provide an overview of five methods that are used to assess engineering activities, processes and products. We have selected these methods based on our impression about their popularity in industry and academic research, and based on some of their unique properties. We expect that these methods cover a wide enough spectrum and will help in applying the six requirements to gain similar insight into other existing methods and future new methods as well. Eco-Efficiency Analysis. Eco-Efficiency Analysis17,18 assesses a product or process based on its environmental impact normalized by a quantity such as revenue or production unit. It may be thought of as a business strategy that uses this metric to demonstrate progress toward improvement. In general, the eco-efficiency metric, or its inverse, an impact intensity metric (e.g., eco-efficiency would be cars produced per tonne of CO2 emitted, and impact intensity would be CO2 per car produced) is an informative and widely used metric. As a business strategy, the approach is suitable for showing improvement or change especially when coupled with information about the absolute level of impact. Its strongest features are consideration of environmental and monetary flows, some interaction across spatial scales if the life cycle is analyzed, and inclusion of the demand for some ecosystem goods such as water and fossil fuel use, but not for services. As compared to other methods discussed in this section, these criteria are considered only in a minimal to moderate manner. As a method to demonstrate sustainability, it is quite limited and can be misleading if not supplemented with additional information. Triple Bottom Line (TBL). Triple Bottom Line19,20 is an expansion of the corporate “bottom line” (i.e., profit) to include a larger group of stakeholders, hence social and environmental bottom lines are also added to the company’s accounting scheme. It is intended to be customized for the needs of the company to help track progress in these spheres, and is sometimes described as People, Planet and Profit. This method is widely used in industry, and improves on eco-efficiency by expanding into multiple domains, however it suffers from its ad hoc nature and lack of standardization. Improvement targets are generally optional and voluntary. There is no guidance on how to make trade-offs between the alternative domains and hence the method leads to a portfolio management type of approach. There are no macro-level effects considered. However, the flexibility of the method suggests that it could be altered and improved in future developments. This approach does slightly better than Eco-Efficiency in considering cross-disciplinary aspects since it clearly acknowledges the broader spheres of influence. However, the three areas are usually reported separately and managed as a portfolio without considering interactions. B

DOI: 10.1021/acssuschemeng.7b03953 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

Research Article

ACS Sustainable Chemistry & Engineering Cradle to Cradle (C2C). Cradle to Cradle21,22 attempts to overcome the shortcomings of eco-efficiency by encouraging “ecoeffectiveness.” It encourages reliance on renewable resources and closing of material loops by pursuing three goals: relying on current solar income, emulating nature and encouraging diversity. As Braungart et al.22 put it, “In contrast to this [eco-efficiency] approach of minimization and dematerialization, the concept of eco-ef fectiveness proposes the transformation of products and their associated material flows such that they form a supportive relationship with ecological systems and future economic growth. The goal is not to minimize the cradle-to-grave flow of materials, but to generate cyclical, cradle-tocradle “metabolisms” that enable materials to maintain their status as resources and accumulate intelligence over time (upcycling). This inherently generates a synergistic relationship between ecological and economic systemsa positive recoupling of the relationship between economy and ecology.” In practice, this method is more design guidance then assessment method. Nevertheless, the idea is that if the proposed principles are implemented then sustainability should follow; therefore, it makes claims that should be assessed along with the other methods assessed here. The basic ideas behind this method are constructive but are generally confined to small scale applications like individual products; furthermore the method lacks quantification and can be in significant disagreement with other methods.23 Spatial scales considered in this approach include the system being designed and some other systems needed to close material loops to the extent possible: an expanded or even partial life cycle boundary is not considered. Through encouraging industrial symbiosis, this approach can reduce some types of impacts. Even though this method talks about “synergistic relationship between ecological and economic systems” it neither includes ecosystems in its boundary, nor accounts for their capacity. Environmental Footprint. Environmental Footprints are defined for important environmental flows such as those of greenhouse gases, water, nitrogen, and materials.24 This also includes the ecological footprint method,25,26 which represents multiple flows in units of land area, and specifically addresses the demand for, and capacity of, some global scale ecosystem stocks, a feature that is not commonly found in the other methods. The method typically focuses on a single ecosystem resource, and because of its global focus, highly aggregates the contributing sectors. But finer grained analysis is clearly possible and in fact can be used in the initial construction of the model. The ecological footprint model accounts for global land use including, providing for food (crops, grazing land, coastal fishing), wood and fiber (forests and fiber crops), infrastructure and energy use, particularly carbon sequestration in forests. It includes elements of fine grained accounting. By comparing land use demand (including the land needed for carbon sequestration) with the actual available land, it draws conclusions about anthropogenic use and biocapacity, for example it can indicate conditions of potential overshoot. Some newer variations on this approach have been developed, including dual land use, and trading between countries, to address shortcomings in the original. Among other footprint methods, carbon and water footprint are most popular and developed. Carbon footprint accounts for greenhouse gas emissions over the life cycle. Recent efforts are also accounting for the supply of the carbon sequestration ecosystem service along with land use change.27 Water footprint considers three categories of water, blue, green and gray, over the life cycle. Some recent water footprint efforts are also accounting for the availability of water.28 These methods represent selected flows in terms of a common unit and compare the footprint with global capacity to provide the selected flow. These characteristics explain their greater ability to account for the demand and supply of ecosystem goods and services, despite their univariate nature. Footprint calculations often consider multiple spatial scales by including important processes from the life cycle. These methods do not address cross-disciplinary effects, but their emphasis on land use and ecosystem health make them slightly more capable of considering intergenerational effects.

Life Cycle Assessment (LCA). Life Cycle Assessment29−31 has been developed to consider an expanded spatial boundary. It is a widely used approach for considering the broader environmental implications of a product or process, and aims to account for resource use and emissions over the entire life cycle from “cradle to grave” to determine the overall impact. LCA consists of four steps: Goal and Scope Definition, Inventory Analysis, Impact Assessment, and Improvement Analysis. Extensive life cycle inventory databases have been developed and various software packages are available for constructing and analyzing life cycles. Life cycle impact assessment considers diverse flows including various emissions and resources, and has developed ways of aggregating them into several “mid-point” or single “end-point” impact indicators. The method has been standardized under ISO 14000 and seems to be the most popular assessment method used today, sometimes used for making claims about sustainability. The method can be expanded using the Input−Output approach, to include direct as well as indirect resource requirements and emissions at the scale of economic sectors.32 Regional, national and multiregional (MRIO) extended input−output models have been developed. Hybrid LCA models combine data of typical processes with aggregated data of economic sectors in a region. The LCA method commonly used to compare alternatives is referred to as attributional LCA. This approach aims to directly compare the life cycle impact of alternatives. It is based on a static snapshot of the alternatives, and does not consider aspects such as the effect of decisions based on LCA. There are significant efforts to extend the LCA framework into other domains. In particular, guidelines for Social LCA are available from the UNEP,33 and efforts to address the challenging problem of how society appropriates and changes to a new technology intervention are being developed.34−36 LCA does consider a diversity of flows, but stocks are usually ignored. LCA continues to be an active area of research and many efforts aim to address its shortcomings. Recent advances are attempting to consider temporal37 and cross-disciplinary effects,38 supply of ecosystem services,39 and applications to engineering decisions.40,41 Overall, LCA comes closest to satisfying the six requirements. Its strength is in spanning spatial scales and considering many kinds of resources and emissions. In general, these and most other sustainability assessment methods have two major weaknesses: (1) they do not account for human behavior; both the social as well as economic consequences of technology, and (2) they do not account for the available supply of the demanded ecosystem services.



COMPARING METHODS ACROSS THE REQUIREMENTS FOR SUSTAINABILITY

The most common problem that faces any engineering analysis method for sustainability is related to the system boundary. Engineering analysis boundaries are initially chosen to reflect the domain of interest and control for the engineering actor. Nevertheless, it is often the case that a small-scale intervention may stimulate events outside the engineering analysis boundaries that may cause unintended consequences that may significantly alter the expected outcome. These may be physical, such as the effects of chlorofluorocarbon refrigerants on stratospheric ozone, or behavioral, such as the energy efficiency rebound effect. Inevitably, the expansion of the system boundary has multiple dimensions. Here, we rate the five analysis methods by their ability to address six aspects of analysis expansion. We consider the most common ways that the methods are applied with some consideration for new promising developments. The first four aspects of system expansion, namely spatial boundaries, temporal boundaries, cross-disciplinary effects, and stocks and flows interactions, are usually coupled. In other words, expanding a boundary spatially may also involve crossing disciplinary boundaries, etc., but we postulate that artificially separating out these four aspects helps to articulate the complex nature of the problem we are addressing. The last two aspects may also be considered to be system expansion to include ecological systems. Due to the importance of ecosystems in sustaining human C

DOI: 10.1021/acssuschemeng.7b03953 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

Research Article

ACS Sustainable Chemistry & Engineering Table 1. Comparison of Sustainability Assessment Methods

activities, as conveyed by the meta-principle in the Requirments for Sustainability section, we consider accounting for the demand and supply of goods and services from nature as two separate criteria. Table 1 compares the extent to which five popular methods address the proposed requirements. Here, red indicates that the requirement is ignored or considered minimally, yellow stands for moderate or partial consideration, and green stands for significant or complete consideration. Intermediate situations are represented by red-yellow and yellow-green colors. This comparison is based on the most common current applications of each method with consideration for new promising developments. Spatial Scales. This requirement involves considering the possibility of impacts shifting across the supply and demand chains, and considering large scale global impacts. None of the methods discussed here can make the entire journey from small-scale intervention to global scale effect on Earth’s ecosystems, but the reasons differ. Four of the methods, eco-efficiency, TBL, C2C and LCA, start out at relatively small scales and cannot fully make the transition to the global scale. Among these, LCA is the best. It explicitly incorporates a lifecycle view, the software versions of the model include extensive databases, and it is relatively easy to incorporate indirect effects using the input-output method to develop hybrid models. Among Environmental Footprints, the method of ecological footprinting is mostly a large-scale accounting scheme. It represents snapshots of how the world was at the selected time of the analysis. But at the same time, while they give us large-scale information, this method is less usable in a predictive mode with a new small-scale intervention. As a result, it cannot fully make the transition from small-scale to large. Carbon and water footprints are closer to LCA but with a narrower univariate focus. We give relatively high spatial scale scores to LCA, slightly lower score to Environmental Footprint methods, and relatively lower scores for the other methods. Efforts toward overcoming the shortcomings of existing methods include methods for combining aggregate models at larger scales with detailed models at smaller scales, and addressing uncertainties in data from such diverse sources and scales. Temporal Effects. There are two important aspects of time addressed in the current literature on sustainability analysis that we used to evaluate the methods discussed here. The first is the idea that our actions today should not interfere with the ability of future generations to meet their own needs. This idea was clearly enunciated in the so-called Brundtland Commission report. The second time feature we have looked for in an evaluation method is its ability to accommodate change and upheaval in those stocks. That is, in short, is there any evidence that the method has been used to model the possible system dynamics? Real systems deviate from steady-state and get disrupted. Panarchy42 presents a stylized representation of this dynamic in ecological systems. The

business literature describes business cycles, and the economics literature describes bubbles and recessions. Sustainability analysis needs to address these kinds of features. In our evaluation of the five analysis methods, we feel that most missed the first point by focusing on current goods and services that in themselves have little or no bearing on future generations. The exceptions are Environmental Footprints that address stocks of some ecological goods and services. On the second point, all methods received low scores. None include dynamic features that could be used to integrate multiple flows or cross-disciplinary interactions, or both. As mentioned in the Life Cycle Assessment subsection, dynamic LCA is a topic of research, but is far from being used in practical assessments. It should also be noted that the current literature on resilience and adaptation does attempt to acknowledge some of these aspects of system dynamics, and methods such as inclusive wealth43,44 attempt to account for intergenerational equity. Cross-Disciplinary Interactions. Of the five methods considered, one stands out for explicitly including social and economic features of sustainability. This is the Triple Bottom Line (TBL). It encourages attention to social, environmental and economic aspects, but the method is without any uniform framework and the economic analysis remains at the level of the firm. Inclusive wealth, on the other hand, addresses manufactured, human and natural capital as well as institutions in a far more rigorous manner, albeit in economic units. Hence we rate TBL as minimal/moderate and three of the remaining four as minimal. The exception is LCA due to current promising developments like Social LCA, Life Cycle Sustainability Assessment, and Consequential LCA. However, in its current version, it can not anticipate how society will adapt and change in response to a small scale intervention. Certain aspects of change can be anticipated using economics concepts such as price elasticity of demand, and income elasticity of demand. But other interventions may be too radical to use these ideas. To illustrate, think of a LCA for a self-driving car. If one could clearly define the car, then one could estimate the CO2 emitted to make and to drive the car, but not the number of cars made nor the passenger-kilometers driven per car. Furthermore, one would not know to what extent driverless cars would substitute for, or complement conventional cars. Such a problem could be approached using LCA and scenario analysis, however, to good effect. Note that the so-called consequential LCA approach aims to address this problem, but it is only now being developed. It should be stated that it is not clear at this point how analysis methods should incorporate cross-disciplinary effects. In some cases, standalone separate models with compatible interfaces may be preferable to large integrated models. Nevertheless, in order to span D

DOI: 10.1021/acssuschemeng.7b03953 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

Research Article

ACS Sustainable Chemistry & Engineering

Figure 1. Assessment and design of sustainable systems needs to consider small-scale technological interventions and their large-scale impacts by following the steps as shown. the full range from engineering intervention to large-scale ecosystem response, methods to address cross-disciplinary effects are mandatory. Interactions between Multiple Stocks and Flows (the nexus problem). The five methods reviewed here can address multiple flows of materials in a parallel fashion; that is, the methods can be used independently for different materials without explicitly identifying interactions. But this capability alone makes them usable for these problems. LCA databases are particularly extensive in the materials they cover, both as inputs as well as emissions and wastes. And LCA can then aggregate impacts from multiple flows according to broad categories such as global warming, acidification, eutrophication, etc. Footprint methods are narrower due to their focus on representing all flows in a common unit. We evaluate LCA as currently the best in this category, but with significant room for improvement. The current interest in the nexus of food, energy, and water is helping advance this category. Demand for Ecosystem Goods and Services. It is common for engineering methods of sustainability analysis to account for the demand for ecosystem goods such as energy resources, water and natural materials, and to account, in some fashion, for some ecosystems services. For example, it is common to report CO2 or CO2 eq that will affect climate regulation services. So, all methods considered here receive at least a minimal/moderate rating. The inclusion of ecosystem services such as carbon sequestration, acid buffering, air and water quality regulation, and pollination, however, is very rare. Environmental Footprint and LCA receive the highest but intermediate scores because of their extensive database of ecosystem goods, LCA evaluation methods that can also aggregate emissions in terms of ecosystem impacts, such as global warming, acidification potential, etc. Recent efforts are developing characterization factors to quantify impact on ecosystem services and biodiversity.45 Thermodynamic methods such as cumulative exergy and emergy analysis are able to account for many ecosystem services by quantifying them as the work done in nature.46 However, their use for sustainability assessment of engineering activities has been limited. Supply of Ecosystem Goods and Services. The capacity of ecosystems to supply goods and services has almost never been considered in engineering methods of sustainability analysis. Hence three out of five methods considered here received minimal scores. The environmental footprint method is the exception, as it is common in this method to compare demand to supply. In fact these methods can identify overshoot, or potential overshoot. So, it receives the

relatively higher score of moderate because there are still many ecosystem goods and services that it does not consider. LCA received a score higher than minimum due to recent developments.39 This is also an area of active research. Methods are being developed based on normalizing characterization factors by ecosystem capacity,47 and by expanding the Techno-Ecological Synergy framework to the life cycle.39



DIRECTIONS FOR THE FUTURE The six requirements of methods for claiming sustainability and the analysis in Table 1 suggest a path forward by developing approaches to overcome the shortcomings. Such efforts are already under way: extensions of LCA aim to consider effects across disciplines and time,48,49 life cycle sustainability assessment connects triple bottom line accounting with LCA,50 Inclusive Wealth creates a framework for combining natural, social and manufactured capital stocks to enable intergenerational well-being,44 and Techno-Ecological Synergy connects LCA with ecosystem service assessment to account for the demand and supply of ecosystem services at multiple spatial scales.16 Despite such efforts, it is likely that no one tool could ensure satisfaction of the proposed meta-principle and address all the requirements at once. Instead, an approach based on coupling existing methods and tools may be most appropriate. To outline the steps forward, we use a simple linear diagram meant to represent the systematic expansion of the spatial scale of analysis from small-scale technical intervention, to large-scale effect on ecosystems. Along this journey, all six of our identified sustainability requirements will become evident. Furthermore, we will also point out some of the most important subsystem interactions and feedbacks that must be included in future modeling and analysis methods. The steps, shown in Figure 1, are as follows. 1. Technology development − The new or improved technology (white) is considered for use in society (blue) and ecosystems (green). This first step uses methods from traditional engineering analysis and design E

DOI: 10.1021/acssuschemeng.7b03953 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

Research Article

ACS Sustainable Chemistry & Engineering

ecosystem service is already beyond its planetary boundary (step 4).15 Such insight will encourage consideration of interventions and policies that encourage protection and restoration of ecosystems to prevent further transgression of local, regional and global ecological boundaries. Insight from these steps will then be used to guide the development of future technologies (steps 5a and 5b). Recent claims on such emerging technologies such as additive manufacturing, autonomous vehicles, process intensification, and biobased polymers need to be assessed by these same steps in a balanced way to ensure that they truly may contribute to sustainability, and to ensure resilience to any unintended consequences. Meeting the challenges of this framework requires transdisciplinary research to integrate technological development, human behavior, and ecosystem response while ensuring satisfaction of the six requirements for assessing sustainability. This may be achieved by loose coupling of many existing methods and models along some new ones to fill the gaps and permit iterative use as shown in Figure 1. These methods will need to combine analysis methods like those discussed in this work with methods for obtaining new designs and solutions. Alternatively, entirely new methods and models may be required that enable integrated assessment for satisfying the six requirements of environmental sustainability.

including cost analysis and performance assessment. These are the most reductionist methods in our framework. If the technology is successful, factors such as improvement by learning and economies of scale couple technical and social domains. 2. Ef fect across spatial scales − This step compares technology alternatives per unit of service at larger spatial scales by considering their life cycles. However, this step tells us nothing about how the technology will be adopted or used, and in many analyses contains an implicit (and often erroneous) social assumption of one for one substitution. 3. Socio-economic interactions − This step focuses on how the intervention will be adopted by society including the scale of the adoption and the mode of use. Here, we have clearly crossed into the domains of human behavior in many forms including at least the behavior of consumers and businesses including attempts to shape this behavior with policy. The expected sustainability benefit can be limited by feedback loops that exploit new advantages that the technology offers, in fact, without a cultural shift away from current exploitive and expansionist behavior the potential benefit of any new technology intervention may be severly limited.51 Methods such as scenario analysis, system dynamics, agent-based modeling, and economic simulation may be used. 4. Natural-human interactions − This step determines the environmental impacts due to large-scale societal adoption in relation to ecological limits and planetary boundaries, and the effect of these impacts on society. Methods for ecosystem service assessment and for considering dynamics of coupled human and natural systems are relevant.52 5. Technology evolution and development − Depending on the findings in the previous steps, existing technologies may be modified or new technologies may be developed to start the cycle over again. Depending on the decision, this step may move the cycle toward or away from sustainability, as depicted in Figure 1. This framework combines reductionist methods from conventional engineering with more holistic methods to consider larger systems in space and time, and with increasing ambiguity. To demonstrate the challenges in this framework, consider existing lighting technology followed by the emerging technology of autonomous vehicles. A simple scenario of light bulb replacement will show a reduction in energy use per bulb and over its life cycle (steps 1 and 2 in Figure 1). But a more comprehensive assessment (step 3) will include multiple effects on safety and productivity, but also the effects of lower cost and greater affluence leading to an offsetting energy increase, as indicated by historical data.53 Such rebound effects have also been observed for other technologies besides lighting.54 A comprehensive analysis should include a balanced discussion that highlights the alternative modes in which the technology may be employed emphasizing past patterns of behavior and possibly suggesting companion incentives or policies that might result in obtaining the hoped for benefit by methods for step 3 in Figure 1. Impacts on ecosystems due to large-scale adoption of technology will then consider multiple effects on ecosystems such as changes in greenhouse gas emissions and the fact that the demanded carbon sequestration



AUTHOR INFORMATION

Corresponding Author

*B. R. Bakshi. E-mail: [email protected]. ORCID

Bhavik R. Bakshi: 0000-0002-6604-8408 Notes

The authors declare no competing financial interest.



REFERENCES

(1) Committee on Scientific Tools and Approaches for Sustainability. Sustainability Concepts in Decision Making − Tools and Approaches for the US Environmental Protection Agency; National Research Council, 2014. (2) Hellweg, S.; Mila i Canals, L. Emerging approaches, challenges and opportunities in life cycle assessment. Science 2014, 344 (6188), 1109−1113. (3) Tilman, D.; Socolow, R.; Foley, J. A.; Hill, J.; Larson, E.; Lynd, L.; Pacala, S.; Reilly, J.; Searchinger, T.; Somerville, C.; Williams, R. Beneficial Biofuels − The Food, Energy, and Environment Trilemma. Science 2009, 325 (5938), 270−271. (4) Greenblatt, J. B.; Saxena, S. Autonomous taxis could greatly reduce greenhouse gas emissions of US light duty vehicles. Nat. Clim. Change 2015, 5, 860. (5) LeCorre, D.; Hohenthal, C.; Dufresne, A.; Bras, J. Comparative Sustainability Assessment of Starch Nanocrystals. J. Polym. Environ. 2013, 21, 71−80. (6) Miculescu, F.; Maidaniuc, A.; Voicu, S. I.; Thakur, V. K.; Stan, G. E.; Ciocan, L. T. Progress in Hydroxyapatite-Starch Based Sustainable Biomaterials for Biomedical Bone Substitution Applications. ACS Sustainable Chem. Eng. 2017, 5, 8491−8512. (7) Patel, A. D.; Telalović, S.; Bitter, J. H.; Worrell, E.; Patel, M. K. Analysis of sustainability metrics and application to the catalytic production of higher alcohols from ethanol. Catal. Today 2015, 239, 56−79. (8) Nagarajan, V.; Mohanty, A. K.; Misra, M. Perspective on Polylactic Acid (PLA) based Sustainable Materials for Durable Applications: Focus on Toughness and Heat Resistance. ACS Sustainable Chem. Eng. 2016, 4, 2899−2916. (9) Norton, B. Sustainability: A Philosophy of Adaptive Ecosystem Management; University of Chicago Press, 2005. F

DOI: 10.1021/acssuschemeng.7b03953 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

Research Article

ACS Sustainable Chemistry & Engineering (10) Seager, T.; Selinger, E.; Wiek, A. Sustainable Engineering Science for Resolving Wicked Problems. Journal of Agricultural and Environmental Ethics 2012, 25, 467−484. (11) Marshall, J. D.; Toffel, M. W. Framing the Elusive Concept of Sustainability: A Sustainability Hierarchy. Environ. Sci. Technol. 2005, 39, 673−682. (12) Broman, G. I.; Robèrt, K.-H. A framework for strategic sustainable development. J. Cleaner Prod. 2017, 140, 17−31. (13) Little, J. C.; Hester, E. T.; Carey, C. C. Assessing and Enhancing Environmental Sustainability: A Conceptual Review. Environ. Sci. Technol. 2016, 50 (13), 6830−6845. (14) Liu, J.; Mooney, H.; Hull, V.; Davis, S. J.; Gaskell, J.; Hertel, T.; Lubchenco, J.; Seto, K. C.; Gleick, P.; Kremen, C.; Li, S. Systems Integration for Global Sustainability. Science 2015, 347 (6225), 1258832. (15) Steffen, W.; Richardson, K.; Rockstrom, J.; Cornell, S. E.; Fetzer, I.; Bennett, E. M.; Biggs, R.; Carpenter, S. R.; de Vries, W.; de Wit, C. A. Planetary boundaries: Guiding human development on a changing planet. Science 2015, 347 (6223), 1259855. (16) Bakshi, B. R.; Ziv, G.; Lepech, M. D. Techno-ecological synergy: A framework for sustainable engineering. Environ. Sci. Technol. 2015, 49 (3), 1752−1760. (17) Schmidheiny, S.; Stigson, B. Eco-efficiency: creating more value with less impact. World Business Council for Sustainable Development, http://www.wbcsd.org, 2000 (accessed 4/26/2016). (18) DeSimone, L. D.; Popoff, F. Eco-Efficiency − The Business Link to Sustainable Development; MIT Press, 2000. (19) Elkington, J. Cannibals With Forks: The Triple Bottom Line of 21st Century Business; New Society Publishers, 1998. (20) Slaper, T. F.; Hall, T. J. The triple bottom line: What is it and how does it work? Indiana Business Review 86 (1), Spring 2011. (21) McDonough, W.; Braungart, M. Cradle-to-cradle; North Point Press, 2002. (22) Braungart, M.; McDonough, W.; Bollinger, A. Cradle-to-cradle design: creating healthy emissions - a strategy for eco-effective product and system design. J. Cleaner Prod. 2007, 15, 1337−1348. (23) Niero, M.; Negrelli, A. J.; Hoffmeyer, S. B.; Olsen, S. I.; Birkved, M. Closing the loop for aluminum cans: Life Cycle Assessment of progression in Cradle-to-Cradle certification levels. J. Cleaner Prod. 2016, 126, 352−362. (24) Hoekstra, A. Y.; Wiedmann, T. O. Humanity’s unsustainable environmental footprint. Science 2014, 344 (6188), 1114−1117. (25) Wackernagel, M.; Rees, W. E. Our ecological footprint: reducing human impact on the earth; New Society Publishers, 1996. (26) Wackernagel, M.; Schulz, N. B.; Deumling, D.; Linares, A. C.; Jenkins, M.; Kapos, V.; Monfreda, C.; Loh, J.; Myers, N.; Norgaard, R. Tracking the ecological overshoot of the human economy. Proc. Natl. Acad. Sci. U. S. A. 2002, 99 (14), 9266. (27) Hortenhuber, S.; Piringer, G.; Zollitsch, W.; Lindenthal, T.; Winiwarter, W. Land use and land use change in agricultural life cycle assessments and carbon footprints-the case for regionally specific land use change versus other methods. J. Cleaner Prod. 2014, 73, 31−39. (28) Ridoutt, B. G.; Pfister, S. A revised approach to water footprinting to make transparent the impacts of consumption and production on global freshwater scarcity. Global Environmental Change 2010, 20 (1), 113−120. (29) Handbook on Life Cycle Assessment: Operational Guide to the ISO Standards; Guinée, J. B., Ed.; Springer, 2002. (30) Life Cycle Assessment Handbook; Curran, M. A., Ed.; Scrivener, 2012. (31) Rebitzer, G.; Ekvall, T.; Frischknecht, R.; Hunkeler, D.; Norris, G.; Rydberg, T.; Schmidt, W.-P.; Suh, S.; Weidema, B.; Pennington, D. Life cycle assessment: Part 1: Framework, goal and scope definition, inventory analysis, and applications. Environ. Int. 2004, 30, 701−720. (32) Hendrickson, C. T.; Lave, L. B.; Matthews, H. S. Environmental Life Cycle Assessment of Goods and Services − An Input-Output Approach; RFF Press, 2006. (33) Guidelines for the Social Life Cycle Assessment of Products; Benoît, C., Mazijn, B., Eds.; UNEP, 2009.

(34) Finnveden, G.; Hauschild, M. Z.; Ekvall, T.; Guinée, J.; Heijungs, R.; Hellweg, S.; Koehler, A.; Pennington, D.; Suh, S. Recent developments in Life Cycle Assessment. J. Environ. Manage. 2009, 91, 1−21. (35) Sharp, B. E.; Miller, S. A. Potential for Integrating Diffusion of Innovation Principles into Life Cycle Assessment of Emerging Technologies. Environ. Sci. Technol. 2016, 50, 2771−2781. (36) Marvuglia, A.; Benetto, E.; Rege, S.; Jury, C. Modelling approaches for consequential life-cycle assessment (C-LCA) of bioenergy: critical review and proposed framework for biogas production. Renewable Sustainable Energy Rev. 2013, 25, 768−781. (37) Levasseur, A.; Lesage, P.; Margni, M.; Deschenes, L.; Samson, R. Considering time in LCA: dynamic LCA and its application to global warming impact assessments. Environ. Sci. Technol. 2010, 44, 3169− 3174. (38) Zamagni, A.; Guinée, J.; Heijungs, R.; Masoni, P.; Raggi, A. Lights and shadows in consequential LCA. Int. J. Life Cycle Assess. 2012, 17, 904−918. (39) Liu, X.; Bakshi, B. R. Ecosystem Services in Life Cycle Assessment while Encouraging Techno-Ecological Synergies. J. Ind. Ecol. 2018, accepted, DOI: 10.1111/jiec.12755. (40) Subramaniam, B.; Helling, R. K.; Bode, C. J. Quantitative Sustainability Analysis: A Powerful Tool to Develop Resource-Efficient Catalytic Technologies. ACS Sustainable Chem. Eng. 2016, 4, 5859− 5865. (41) Gong, J.; You, F. Consequential Life Cycle Optimization: General Conceptual Framework and Application to Algal Renewable Diesel Production. ACS Sustainable Chem. Eng. 2017, 5, 5887−5911. (42) Panarchy − Understanding Transformations in Human and Natural Systems; Gunderson, L. H., Holling, C. S., Eds.; Island Press, 2002. (43) United Nations Environment Programme and United Nations University. Inclusive wealth report 2014: Measuring progress toward sustainability; Cambridge University Press, 2015. (44) Dasgupta, P. Nature’s Role in Sustaining Economic Development. Philos. Trans. R. Soc., B 2010, 365, 5−11. (45) Koellner, T.; de Baan, L.; Beck, T.; Brandao, M.; Civit, B.; Margni, M.; Mila i Canals, L.; Saad, R.; Maia de Souza, D.; MullerWenk, R. Unep-setac guideline on global land use impact assessment on biodiversity and ecosystem services in LCA. Int. J. Life Cycle Assess. 2013, 18 (6), 1188−1202. (46) Hau, J. L.; Bakshi, B. R. Expanding exergy analysis to account for ecosystem products and services. Environ. Sci. Technol. 2004, 38 (13), 3768−3777. (47) Bjorn, A.; Hauschild, M. Z. Introducing carrying capacity-based normalisation in LCA: framework and development of references at midpoint level. Int. J. Life Cycle Assess. 2015, 20 (7), 1005−1018. (48) Earles, J. M.; Halog, A.; Ince, P.; Skog, K. Integrated economic equilibrium and life cycle assessment modeling for policy-based consequential LCA. J. Ind. Ecol. 2013, 17 (3), 375−384. (49) Gibon, T.; Wood, R.; Arvesen, A.; Bergesen, J. D.; Suh, S.; Hertwich, E. G. A Methodology for Integrated, Multiregional Life Cycle Assessment Scenarios under Large-Scale Technological Change. Environ. Sci. Technol. 2015, 49 (18), 11218−11226. (50) Zamagni, A.; Pesonen, H.-L.; Swarr, T. From LCA to life cycle sustainability assessment: concept, practice and future directions. Int. J. Life Cycle Assess. 2013, 18 (9), 1637−1641. (51) Rees, W. What’s blocking sustainability? Human nature, cognition and denial. Sustainability: Science, Practice and Policy 2010, 6 (2), 13−25. (52) Liu, J. G.; Dietz, T.; Carpenter, S. R.; Alberti, M.; Folke, C.; Moran, E.; Pell, A. N.; Deadman, P.; Kratz, T.; Lubchenco, J.; Ostrom, E.; Ouyang, Z.; Provencher, W.; Redman, C. L.; Schneider, S. H.; Taylor, W. W. Complexity of coupled human and natural systems. Science 2007, 317, 1513−1516. (53) Tsao, J. Y.; Saunders, H. D.; Creighton, J. R.; Coltrin, M. E.; Simmons, J. A. Solid-state lighting: an energy-economics perspective. J. Phys. D: Appl. Phys. 2010, 43 (35), 354001. G

DOI: 10.1021/acssuschemeng.7b03953 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX

Research Article

ACS Sustainable Chemistry & Engineering (54) Dahmus, J. B. Can Efficiency Improvements Reduce Resource Consumption? J. Ind. Ecol. 2014, 18 (6), 883−897.

H

DOI: 10.1021/acssuschemeng.7b03953 ACS Sustainable Chem. Eng. XXXX, XXX, XXX−XXX