There were a couple of themes on quantifying sustainability metrics from the Annual Meeting that resonated across many sessions. The themes addressed gaps in conducting sustainability evaluations and promoted:
1. Creating comparative scenarios that determine true sustainability. Comparative scenarios are in contrast to deeming a single system "sustainable," but rather, "more sustainable" than an alternative; and
2. Resolving sustainability problems through multidisciplinary approaches.
The first speaker of the Annual Meeting's First World Congress on Sustainability was Subhas Sikdar, Director of the Sustainable Technology Division at the National Risk Management Research Lab of US EPA. Subhas is past chair of AIChE's Institute for Sustainability (IfS) and founder of the Sustainable Engineering Foundation (SEF). He provided perspective on the evolution of the sustainability paradigm from a risk assessment exercise to a decision-making factor in practical applications today.
Four basic types of sustainable systems
Risk reduction, according to Subhas, first took off with a linear approach designed to reduce the presence and concentration of a single chemical in the environment, not as a scalable systems-approach that factors in other components for a sustainability analysis. Subhas identified four types of sustainable systems:
- Global, which include CO2 budgeting, since CO2 emissions have a global impact;
- Regional, including brownfields;
- Business and related networks; and
- Technology, which covers green chemistry solutions.
As a result of acknowledging the scale of these systems, there is an opportunity to take an engineering approach that guarantees the intersection of economic, environmental, and societal concerns. Sustainability is ensured when a reduction in the quality of any of these three pillars can occur without a negative impact on the other two. In other words, the impact can be renewed or restored, thus ensuring continuity and sustainability of the system in consideration.
Determining reliable metrics
How sustainable can a system actually be? The answer to that question depends on determining a reliable set of metrics, based on analyses that can lead to reportable results. Examples of sustainability metrics include BASF's eco-efficiency metrics, or AIChE's Sustainability Index. One consideration for the development of any metric is the number of indicators the metric addresses. According to Dr. Sikdar, too many indicators for a single metric can lead to poor inspection of a system's true sustainability--especially if the metric relies on visual inspection as a reading. Thus, sustainability analyses benefit from metric indicators that are system-dependent and quantifiable in terms of units. The end goal of performing sustainability analyses is to achieve the lowest possible impact, verging on no impact. Subhas expressed the urgency well by stating: "[Zero waste is] obviously a pipedream, but we have to approach the idea of zero waste."
A few "musts" of any sustainability analyses, according to Dr. Sikdar, include:
- Comparing the system under assessment to a reference.
- Basing assessments on the life cycle of materials, energy, and cost through the appropriate supply chain.
A comparative judgment can be made based on the aggregate behavior of the metrics for the improved system: an aggregate is always a more reliable indicator than simply measuring a metric for one aspect of the system. In response to quantifying impacts that take into account aggregate metrics, Subhas shared the development of consolidating metrics in the composite measurement unit labeled D, the geometric mean of the ratios of the individual metrics for pair-wise comparisons. The method of developing D reveals the sensitivity of the aggregate metric to individual metrics and a specifically-assigned weighting factor. This means D eliminates the uncertainty that can accompany visual inspection of plotting certain metrics according to index requirements and allows a true comparison that does not rely on a metric-by-metric comparison that relies on units. Normalizing sustainability metrics with a composite measure makes sustainability analyses easy then, right?
I hate to break it to you, but that's not entirely the case. While engineering new technologies are a major part of the answer to sustainable development, and comparing systems of technologies yield more accurate sustainability assessments, even technologies must be evaluated from a systems point of view in the context of an even larger picture. (Where does the system "end?") As Subhas explained, sustainability is not an absolute measurement but a comparative one. It's important not to lose important data in measurements and metrics alone. In other words, the greater context of social implications must be considered in any analysis or life cycle assessment (LCA).
As one of the two themes on sustainability I uncovered at the Meeting imply, sustainability analyses cannot be conducted on behalf of a single engineering discipline. This process is highly multi- and interdisciplinary, and Subhas emphasized consulting civil engineers, bioengineers, and others in the process. One astute audience member asked about the extent of moving beyond engineering disciplines, and involving social scientists, economists and other professionals in the discussion. As far back as last year, I wrote about this very question, and solicited input on the extent of collaboration it will take for chemical engineers to make significant progress in the realm of sustainability. Dr. Sikdar explained that different disciplines have a tendency to frame the question of sustainability within their own metrics or performance indicators. As such, multidisciplinary approaches to sustainability or LCAs occur by integrating metrics from one discipline into another.
In some cases, it is altogether difficult to perform an LCA or sustainability evaluation when no assessment method currently exists for a process or product or values have not yet been assigned to certain parameters that are reliable for multiple applications or among multiple organizations. Examples of software that exist to perform these analyses are SimaPro, or as presented by the group of E. D. Frank and I. Palou-Rivera, GREET, developed by Argonne National Laboratory for algae. Having sufficient or complete data to enter as inputs to these models will dictate the accuracy of the models' results.
LCAs can apply to many systems, and there are many ways of conducting these analyses. Did you attend the Annual Meeting? If so, what other LCA lessons did you learn?