Brown Bag Webinar: Advancing Sustainable Packaging Systems Through Life Cycle Thinking and Environmental Trade-Off Assessment

Overview

How can science-based decision-making guide packaging design toward true sustainability?

In our October Brown Bag session, Dr. Rafael Auras, Professor and Amcor Endowed Chair in Packaging Sustainability at Michigan State University’s School of Packaging, shared research and real-world examples illustrating how Life Cycle Assessment (LCA) and Stochastic Multi-Attribute Analysis (SMAA) help clarify complex trade-offs in packaging systems.

The discussion explored the importance of viewing products and packaging together, rather than isolating materials or end-of-life outcomes, and highlighted how regulatory focus on recyclability sometimes overlooks bigger system impacts such as product protection, consumer behavior, and waste prevention.

Key Themes from Dr. Auras’ Talk

• Beyond materials: Sustainable packaging design must balance performance, protection, and policy—not just recycled content or recyclability targets.

• Product-to-package ratio: In food systems, the product’s footprint typically outweighs the packaging’s. Small packaging changes can have large effects on product loss, shelf life, and emissions.

• Modeling consumer behavior: Using discrete-event simulation, Dr. Auras demonstrated how household size and purchase patterns influence total waste—showing, for instance, that switching from two 1-gallon containers to three half-gallons can reduce emissions despite slightly higher packaging use.

• SMAA for decision-making: When multiple indicators conflict, SMAA helps quantify uncertainty and show the probability that one option truly performs better overall—a powerful way to communicate with suppliers, retailers, and regulators.

• Policy implications: End-of-life focused frameworks (like EPR) must expand to include upstream and use-phase dynamics. Functional equivalence and waste prevention are critical to achieving realistic decarbonization.

About the Speaker

Rafael Auras is a Professor and the Amcor Endowed Chair in Packaging Sustainability at Michigan State University’s School of Packaging. He leads a multidisciplinary research group of undergraduate, graduate, and postdoctoral students dedicated to advancing sustainable packaging through studies on mass transfer in polymers, biodegradable materials, life cycle assessment, and the design of circular packaging systems. With extensive experience collaborating with Fortune 500 companies and government agencies, Dr. Auras is a frequent speaker at national and international conferences. His research has been widely published in leading journals and books, contributing to the global advancement of packaging sustainability science and education.

Continue the Conversation

EarthShift Global’s Brown Bag Webinar Series brings together sustainability leaders from industry and academia to share methods, tools, and insights that advance life cycle thinking. Explore our upcoming sessions and past recordings here.

Edited Webinar Transcript:  (Sectioned with Timestamps)

0:05–1:03 — Opening & Introduction

Tess Konnovitch (EarthShift Global):
Hello everybody. My name is Tess Konnovitch and I'm the Scientific Marketing Manager here at EarthShift Global. It's my absolute pleasure today to introduce Dr. Rafael Auras, who is a Professor and the Amcor Endowed Chair in Packaging Sustainability at Michigan State University’s School of Packaging. He leads a multidisciplinary research group of undergraduate, graduate, and postdoctoral students dedicated to advancing sustainable packaging through studies on mass transfer and polymers, biodegradable materials, life cycle assessment (LCA), and the design of circular packaging systems. Please feel free to use the question-and-answer feature at the bottom, and we'll go through all of your questions at the end of this session. Welcome, Rafael—I’m excited for you to get started.

Dr. Rafael Auras (MSU):
Thank you, Tess. I hope that everybody can hear me okay over there. It's a pleasure to be here and to be in this Brown Bag webinar. We have a very long relationship with EarthShift Global, working in the area of life cycle thinking and environmental trade-off assessment. I would like to talk a little about that today. But before I start, I’d also like to tell you about the School of Packaging for those who don’t know where we are and what we do.

1:03–4:35 — MSU School of Packaging Overview

We are here in East Lansing, in the state of Michigan. This is the MSU campus map, and in the middle of the campus there is a School of Packaging—yes, there is a School of Packaging where we do study packaging—and we have been here since 1952. Next year we will celebrate 75 years, and we went through large transformations across many different periods, working with different stakeholders in industry and government. We started in a very small building; we had a renovation in 1982, a latest renovation during the COVID period, and now we are moving to a second phase where we are expanding our research capabilities.

Since we started at MSU, we have been a program that has been growing. Right now, we are ranked the number one program in the U.S. Forty percent of packaging professionals in the industry right now are coming from MSU. If you come to MSU, you can have a bachelor’s in Packaging, you can continue to a master’s, and you can also get your Ph.D. You can spend almost 10 years of your life with us and have all your packaging degrees and knowledge at the School of Packaging.

We are a large family—around 600 undergraduate and graduate students plus the faculty. Around 520 undergraduate students, around 30 Ph.D. students, and the remaining are master’s students (online and on campus). We have already conferred more than 10,000 degrees since our beginnings. If you are in the U.S. or around the world, chances are you will meet someone working in packaging who has a degree from us. That makes us a big family around the world and allows us not only to know about packaging, but also to move the scholarship, research, and teaching of packaging forward.

We are also highly involved in research—that’s one of our core missions along with teaching and outreach. As one example of this involvement, we have an NSF IUCRC center to move sustainable innovation in plastics, paper, and materials. If you are interested, please don’t hesitate to contact us. This is a collaboration between the School of Packaging at Michigan State University and Western Michigan University.

This is the team—the faculty plus all the students. I conduct research, as Tess said, in three areas: (1) developing packaging structures with properties and end-of-life scenarios, (2) biodegradation, and today we’ll concentrate on (3) life cycle assessment (LCA) and how we use LCA for decision-making, especially as things are moving globally and in the U.S.

5:02–8:25 — Why Use LCA for Packaging Decisions

Let’s get into LCA in packaging—where we’re going with assessment, our concerns, what we need to solve, and what we’ve been doing. As you know, the packaging industry is often viewed as unsustainable. Consumers love to get the product and to use it; they love the package during the use phase, but they hate the end of life. That creates a relationship where, when we assess, we tend to emphasize some stages of the packaging system more than others.

In general, packaging decision processes are not always based on science-based information. Across the packaging supply chain and product system, different stages have different environmental footprints and contributions. It’s very important to use science-based information to make decisions. LCA can help, but we must use it with a holistic approach, looking at all phases.

This is especially important as, globally, we’re moving toward packaging minimization, reduction of unnecessary packaging, circularity (not only recycling at end-of-life but also post-consumer recycled content introduction), and avoiding leakage into the environment—particularly for single-use packaging. And when we need to report Scope 1 to Scope 3, we must use assessment data to do that reporting for the packaging component related to Scope 3.

With all this regulation moving around the world, the question is: Are we moving in the right direction? Are we using data to make decisions and to implement packaging systems with the lowest environmental footprint? Current regulations often concentrate on packaging and may forget the role of packaging: to protect the product, to distribute it, and to enable consumption. Regulating only the end of life creates an issue when trying to take a holistic approach to reduce environmental footprints across the indicators we evaluate in LCA.

Consumers and companies are often confused about what is important and how to look at it. I’ll provide an example of work we did for a Michigan company providing infant formula to consumers. A retailer required more infant formula in metal cans on their shelves. They distribute in three different formats. The question: which format delivers the lowest environmental footprint? The retailer pushed for a material with large recycled content, focusing on the end-of-life scenario and assuming it would deliver the lowest footprint.

8:25–16:24 — Case Study: Infant Formula Packaging & SMAA

The good thing with this study is that we had primary data. We worked with the company; they provided supply chain configurations and material and data. We ran a study where the functional unit was delivering 1,000 grams of infant formula. As in any classic LCA, we had a contribution analysis across multiple indicators, including assembly and disposal of the primary package, and contributions from secondary and tertiary packaging (which are generally smaller than primary).

When we compare the different containers, we see typical trade-offs between indicators. For example, Package 1 (a plastic can with a barrier layer) had higher values in fossil depletion, lower in global warming and acidification, and lower in respiratory effects, ecotoxicity, carcinogenic, and non-carcinogenic categories. Package 2 had the largest acidification and intermediate values in other indicators. Package 3 had the largest toxicity and respiratory effects, and similar values for other indicators.

If you use only one indicator, you might reach one decision; another indicator could point you somewhere else. End-of-life allocation methods also matter. Under the cut-off method, material sent to recycling isn’t penalized, while landfill or incineration is penalized for emissions. Under a 50/50 method, you pay 50% of the recycling emissions and the second user pays the other 50%. The EU Circular Footprint Formula (CFF) is more complex and can grant energy credits for certain end-of-life scenarios, which can reduce some indicators.

To navigate conflicting indicators and allocation choices, we used Stochastic Multi-Attribute Analysis (SMAA)—a method developed at Arizona State University and applied in packaging by colleagues such as Valentina Prado and Lise Laurin (EarthShift Global). SMAA runs uncertainty on the LCA results and over indicator weightings to estimate the probability of ranking (which package is most likely “best overall” or “worst overall”).

Across scenarios and allocation methods, Package 1 most often ranked first (highest probability of the lowest environmental footprint). Package 3 most often ranked last (highest footprint). Package 2 changed ranking when we modeled a composite option (e.g., a metal bottom replaced with a paper or fiber-based component), illustrating how design adjustments can shift outcomes. With this information, the company could engage the retailer: if you want more metal cans, we can discuss, but based on our supply chains and primary data, Package 1 delivers infant formula with the lowest environmental footprint.

This is a nice journey and nice science-based decision process, helping with decision process, retailer dialogue and Scope 3 understanding.

But then, let’s take it a step further and start looking at the package versus the product.

16:24–21:27 — Product vs. Package

In this case, I’ll use the container with the highest environmental footprint—the infant formula in the metal can. If you look at that, you can see that in this case the green or olive color here is the contribution of the metal container. This is actually the metal cylinder in two indicators—you have the carcinogenic and non-carcinogenic that are larger.

But when you’re looking at the one kilogram of milk powder, you see that in this case the milk powder has a much larger contribution than the container. These are the containers with the high environmental footprint, and this is not surprising. It’s not surprising that you’ll see those containers with the largest environmental footprint.

Many years ago, we were also doing another study with milk and found the same situation. That’s what I want to bring today: when you have this situation and you look at the environmental footprint of the product and the package, sometimes you need to look at the whole supply chain in order to decide where you’ll actually make reductions.

Because in this case, if the milk formula has such a large contribution, any loss that happens in the container due to the formula there may fully change any difference that you do with the package.

Many years ago, we did a study with colleagues in Arkansas looking at in-home containers and on-the-go containers for milk delivery. In this case, if you actually look—this is the one-gallon container, the regular one we put in our refrigerators—and these are the on-the-go. If you look at that and the supply chain and production and distribution, the same thing happens here.

You have climate change, cumulative energy demand, freshwater depletion, all the way to eco-toxicity. What you expect to see is that the milk has the largest environmental footprint across all those indicators. You have a packaging system to protect the product, which has the largest environmental footprint.

The second largest contributor in most indicators is the consumption phase. You see here that consumption phase in climate change, cumulative energy demand, photochemical oxidation, and ecosystem ecotoxicity is the second largest. If you look at the container, in cumulative energy demand and climate change, you can see some contribution; in others, it’s almost negligible because it’s very small.

That’s very important for decision-making because you look at this and say, well, anything I can reduce here may reduce the total emissions. That put us on a journey to look at this information and see if we can make decisions based on the supply chain.

21:27–27:27 — Modeling Supply Chain Loss and Consumer Behavior

So, what we did there: we looked at the supply chains. You can see it’s very common that you have different types of losses that happen before the consumer and after the consumer. We tried to model what happens in that supply chain. Milk accounts for about 13% of total food waste in the U.S., and that’s a very large amount—about 4.76 billion kilograms of milk.

If you multiply that by the amount of CO? required to produce and deliver one kilogram of milk, you get a very large emission total. That’s not a small contribution to the environment. We have around 1,270,000 homes’ worth of emissions—about the same as those households produce in energy-related emissions.

The problem is that LCA as a tool is very linear, and when you need to do consumer-oriented decision processes, you need to integrate LCA and environmental footprint with other processes. This is similar to modeling the on-time departure and landing of airplanes—you have events starting and stopping, and you optimize the runway for how many planes you can land and take off.

The same thing happens when you want to model milk consumption. The consumer buys the milk, takes it home, puts it in the refrigerator, uses it for breakfast or drinking, then puts it back. We modeled that using discrete-event simulation (DES), which lets you base the model on events that happen over time.

We tried to model the consumers in the U.S. based on different categories using U.S. Census data. We had one-person households (1NFM)—about 32 million people around 2018—two-person households (2NFM), and four-person households with two adults and two children (4FM).

The one-person household buys one half-gallon of milk; the two-person home buys one gallon; the four-person home buys two one-gallon containers every week. In the results, the green represents milk consumed, the pink represents milk spoiled, and the small bars represent containers used or disposed, and even “top-up shops” when people go out to buy more milk.

Then we ran scenarios to see what happens if the one-person household buys two quarts, the two-person home buys two half-gallons instead of one gallon, and the four-person home buys four half-gallons instead of two gallons.

We found that for one-person homes, waste milk decreased, though container use increased a bit. Two-person homes showed little variation. But for four-person homes, if they don’t buy two one-gallon containers but buy three half-gallon containers, they have more milk available during the year, less milk waste, and the total greenhouse gas emissions decrease. The later opening of the second or third container delays spoilage.

That’s important when we start making decisions now for EPR systems and state regulations. When we look at what happens across states, we need to think about which decision processes will reduce the total environmental footprint. In this case, switching from two gallons to three half-gallons increases packaging a little but reduces total emissions.

27:27–33:59 — Regulation, Meta-Analysis, and Ratios

A few years ago, we looked at how regulations are changing globally—with recycling requirements, recycled content, and EPR programs. The U.S. is transitioning: California, Oregon, and Colorado are all implementing EPR systems. You also have reuse and refill requirements.

To make sense of this, I’ll show one more paper we published about two years ago. We looked at studies between 2010 and 2023 comparing systems to deliver products—metal, plastic, carton, paper, glass—in North America and Europe. We gathered all studies published in English and did a meta-analysis.

For each study, we collected greenhouse gas emissions and nonrenewable energy use. Other indicators are rarely reported consistently, but we compiled all we could. After crunching the data, we built a distribution of results.

If you look at delivering one liter of product, you see that multicomponent, carton, rigid cup, flexible pouch, rigid plastic bottle—all deliver that liter with essentially the same greenhouse gas emissions. We can debate other indicators, but there’s no statistically significant difference in GHG for those types.

In North America, bottles are sometimes heavier than in Europe, so metals and glass diverge more, but for most plastic-based systems, emissions are comparable. The same pattern appears for delivering one kilogram of product: flexible pouches, bottles, and cartons are all statistically similar in greenhouse gas emissions, while rigid boxes are slightly lower and metal cans are much higher.

This is important because as we regulate systems, we may need to rethink the ratio between the environmental footprint of the product and the package, and when it might be beneficial to use eco-modulation or eco-design approaches to reduce total environmental footprint.

For example, if you have a large ratio—where the package contributes heavily relative to the product—introducing recycled content or lightweighting can make a noticeable difference. But when the product footprint is dominant, anything you can do to reduce losses of the product itself will have a much larger effect, even if packaging emissions increase slightly, because the environmental footprint of those materials or this product here are much more larger than the other product.

33:59–35:59 — Conclusions

I think we covered a lot. What I want to emphasize is that LCA allows us to have a comprehensive evaluation of environmental footprints of both products and packaging systems. We shouldn’t forget that we put a package there to deliver a product and serve a function.

We need to look at them as one holistic system. It allows us to estimate environmental trade-offs, compare packaging systems, and even do product–package trade-offs. That’s more challenging but much more insightful if we want to decarbonize supply chains. Looking only at end-of-life scenarios won’t give us enough insight to do that job.

We also have projects that use LCA to inform design—looking at material substitution or other design strategies to reduce environmental footprints across primary, secondary, and tertiary packaging.

There’s still a lot of work to do. We need fair and transparent environmental assessment methods that capture full product-and-packaging impacts, including waste, loss rates, and user behavior. We tend to use tools that only assess the package, not the product plus the package. That’s something we need to change to make better decisions and ensure functional equivalence.

We also need more regional data. It’s not the same in North America, Europe, South America, Africa, or Asia. Some indicators or assumptions used in LCA may not fit every region because the systems differ.

And finally, to create win-win strategies for consumers and industry stakeholders, we need to fully include waste and loss in the supply chain if we truly want to decarbonize.

Happy to answer any questions. Go Green, and let’s see if we have time to answer some of your questions.

36:05–48:06 — Q&A

Tess:
Thank you. That was incredible—I learned a lot. We’ve received a few questions, both in my chat and Q&A. Please enter any more questions you have there.

Q: Using science-based information to make decisions to lower emissions doesn’t always translate to consumer understanding. How should brands communicate about their packaging decisions to consumers?

Dr. Auras:
Thank you—that’s a great question. It’s not only about consumers. Consumers are very important, but sometimes we put too much pressure on them to understand and make decisions based on all this information. It’s very hard—even for us in the field—to make sense of all the data.

I think the first ones who need to understand are the policymakers. Policymakers need that information so they can create policies that incentivize production and consumption with the lowest environmental footprint. When those incentives are in place, brand owners have a much easier path to communicate their decisions to consumers.

Right now, we’re going through a mixed process. There are material substitutions happening that we don’t fully understand, and they may create boomerang effects or rebound effects in emissions. It’s important that professionals and associations communicate with policymakers so the policies being created actually incentivize decarbonization of supply chains. Once that’s in place, brands can better communicate with consumers and help them make the best decisions.

Q: When you consider food waste in the model, how should it be quantified and modeled?

Dr. Auras:
That’s a very good question. We strive to model proper losses in the supply chain and consumption phase. That’s why we moved to discrete-event simulation to quantify those losses and their timing. Others, like WRAP in the UK, are also using discrete-event simulation, and more studies are going that way.

The key is that waste doesn’t happen all at one point. To deliver one pound of product, you’ll have excess production across the supply chain, but that waste is not all at the farm gate—it happens throughout. The percentage of waste is different at different stages, and emissions from those stages differ. So, we need to understand where that waste is created geographically and in the supply chain.

We can’t just compare A versus B without understanding those boundaries, or we’ll miss important context.

Q: Do you provide certificates of participation for this webinar?

Tess:
At EarthShift Global, we don’t currently provide certificates for this session, though we’re exploring that for the future.

Dr. Auras:
At the School of Packaging, we offer several opportunities: bachelor’s degrees, short courses for industry, and a full master’s on campus or fully online for professionals. You can learn about streamlined LCA tools or full LCA tools and apply those to decision-making processes.

Tess:
At EarthShift, we also offer training programs, and we’re working to revamp that page to include on-demand courses and possibly certificates in the future.

Q: How critical is high-quality primary data for LCA trade-off assessments, and which data gaps most skew results?

Dr. Auras:
In the example I showed with the three containers, we were able to provide useful results because we had primary data—where the containers were produced, where materials came from, what energy was used. That is very important.

When you want to make comparisons, if you don’t have primary data, the study becomes assumption-based. It can be informative, but not robust enough for decisions. Having real data allows us to rank packages accurately.

When does it matter most? When the stage is a large contributor. If you have poor data on your primary container, assumptions can dramatically change results. The same goes when you expand the model to the whole supply chain—if you have even 10–20% uncertainty in key data, you may not be able to tell which option is truly better.

Q: EPR policies often fixate on end-of-life. What upstream impacts and key trade-offs are we overlooking by doing so?

Dr. Auras:
We often overlook loss rates and functional performance. For example, if I open a whole gallon of milk, all of it is exposed and I have about seven days to use it. If instead I buy two half-gallons, I delay opening the second one and extend its shelf life, so less milk spoils.

It’s very important that EPR considers functional equivalence of packaging systems, not just end-of-life scenarios. Maybe one system uses more packaging but still results in lower total emissions overall.

Q: Where can we access the stochastic multi-attribute analysis (SMAA) methodology you spoke about earlier?

Dr. Auras:
There are several papers, including work by Valentina Prado and Lise Laurin. You can email Lise—EarthShift Global has models in their MatterPD software that use SMAA. You can access those papers; many are open-source. Feel free to send an email—we’ll share links and resources for getting started with stochastic multi-attribute analysis.

Tess (Closing):
Thank you, Rafael, for such a great talk. I really enjoyed it, and thank you everyone for engaging with so many thoughtful questions. Thank you all for attending today—and we’ll see you at next month’s webinar, which we’ll be announcing soon. Have a great afternoon.

Dr. Auras:
Thank you. Bye for now.