Sustainability Assessment – KPIs & Life Cycle Analysis

Introduction

Concepts & overview

Sustainability assessment in engineering evaluates how a design performs environmentally, socially, and economically across its full life cycle. This perspective is grounded in two key concepts: life-cycle thinking, which traces impacts from raw material extraction through manufacturing, transport, use, maintenance, and end-of-life; and the triple bottom line (TBL), which considers environmental quality, social responsibility, and economic viability together.

To make sustainability performance more explicit, this framework uses a set of Key Performance Indicators (KPIs). Each KPI corresponds to a specific aspect of sustainability (for example, carbon footprint, energy demand, community impact, or cost) and is evaluated relative to a baseline (for example, today’s common or “business-as-usual” solution that your design is compared against). Using a combination of simple calculations and qualitative reasoning, each KPI is assigned a 0–5 sustainability performance score, where higher scores indicate better performance on that dimension.

In professional practice, sustainability assessment may involve detailed tools such as ISO 14040/14044 Life Cycle Assessment (LCA), environmental product declarations, and corporate sustainability reporting. The approach presented here is deliberately simplified but follows the same logic: it links life-cycle thinking, basic quantification, and KPI scoring into a single, transparent method.

Five-Step Methodology for Sustainability Assessment
From concept to score

The aim of the following sections is to describe the steps needed to obtain a full sustainability assessment. The process starts by mapping the system and identifying hotspots across the life cycle, then quantifies the most important impacts (for example, CO₂e for key stages), and finally uses these insights to assign 0–5 sustainability performance scores to a set of KPIs. Taken together, Sections 1–5 give a structured picture of how the design performs across the environmental, social, and economic dimensions of sustainability and how it compares with a relevant baseline. An example of this assessment is found after the sections.

In summary: life-cycle thinking identifies where impacts occur, simplified calculations provide basic evidence, and KPI scores organise this information into a concise sustainability “scorecard” that can guide design decisions.

1Define the System and Baseline

Scope and comparison

The first step is to clearly define the system under assessment and a suitable baseline. Together, these establish what is being analysed, what function it provides, and how its sustainability performance will be judged. This step follows the principles of Life Cycle Assessment (LCA), which evaluates impacts across the full life cycle of a product, service, or process (ISO 14040; ISO 14044).

In this framework, the system is the proposed engineering solution developed to address the project challenge. The baseline represents current or conventional practice that delivers the same function. The baseline may be a product, a process, a service, or a combination of existing technologies, depending on the project context.

Defining both the system and the baseline ensures that later impact calculations, KPI scores, and reflections are based on a fair and meaningful comparison.

This step involves the following:

Life-cycle stages. Once the system, functional unit, and baseline are defined, the main life-cycle stages that apply to both are mapped. At this stage, the focus is on understanding system boundaries rather than performing calculations.

System Boundaries Checklist: Before moving to Step 2, is import to identify which life-cycle stages apply to your design:

If a stage doesn't apply: Write a brief note explaining why. For example: "End-of-life is minimal because 95% of the system is biodegradable and returns to soil."

2Identify Hotspots with Life-Cycle Questions

Hotspot screening

This step uses reflective questions to perform a qualitative or semi-quantitative screening of the life cycle. The goal is to identify hotspots.

Hotspots are life-cycle stages or processes that are likely to dominate environmental or social impacts, or where your design differs most from current practice (baseline).

Important: Step 2 is not a full LCA. It is a screening exercise used to decide where to focus effort later.

How to identify hotspots

  1. Review the screening questions in Section 2.1 for each life-cycle stage.
  2. For each life-cycle stage (not each question), assign an overall importance score: Low, Medium, or High. Add short notes to justify your choice.
  3. For each life-cycle stage selected, what materials/activities/component/process drives the impact of this life-cycle stage?

Scoring guide (use this for each stage)

  • High → Likely to dominate impacts or clearly differs from the baseline
    Examples: energy-hungry operation, high-consumption consumables, major new materials/processes vs baseline
  • Medium → Non-negligible, but not dominant and/or broadly similar to baseline
    Examples: moderate transport, some waste, minor differences vs baseline
  • Low → Minor contribution and similar to baseline
    Examples: small one-off impacts, standard processes, no meaningful change vs baseline

Tip: The questions below are prompts. You do not “score each question”. You answer them, then decide a single stage rating based on the pattern of answers.

2.1 Reflective Questions for an LCA-Style Screening

The questions below help you examine each life-cycle stage. By answering them honestly, you will identify:

These reflective questions are a screening tool to focus your effort on what matters most.

Raw Materials

Processing / Manufacturing

Distribution, Transport & Logistics

Use Phase

Maintenance

End of Life

General Screening Question

Next step: For each hotspot you selected, Section 3 will guide you to measure it and find an emission factor to calculate the total impact.

3Quantify Key Hotspots (Simplified LCA)

CO₂e & key impacts

This step turns the 1–3 hotspots identified in Section 2 into approximate numbers that quantify the impact in terms of (CO₂e). The aim is not a full ISO 14040/14044 LCA, but an order-of-magnitude comparison between the proposed solution and a baseline, expressed per functional unit.

3.1 Choosing What to measure

In the previous step, you identified which life-cycle stages are hotspots. Each hotspot is typically driven by one or two dominant activities, materials, or components. Quantification should focus on these dominant elements, rather than attempting to capture every input or output.

Depending on the nature of the project, the quantity you choose to estimate the CO₂e impact may represent:

The guiding question is:

What physical activity, material, or component drives the impact of this life-cycle stage, and how can it be represented quantitatively per functional unit?

Illustrative example: choosing what to measure

A car manufacturer plans to increase the share of electric cars in its production from 0% to 20%, claiming reductions in energy use and greenhouse gas emissions compared to conventional petrol cars.

In this case:

For this decision context, the dominant activity in the identified hotspot (manufacturing) is the production of a complete vehicle. Rather than estimating individual materials or process energy use, the element chosen for quantification is therefore one car produced.

This choice is appropriate because published data are available for the greenhouse gas emissions associated with producing a conventional petrol car and an electric car, allowing a reasonable comparison between the proposed system and the baseline.

3.2 The Basic Formula

Once you have listed what physical activity, material, or product best represents a hotspot, its environmental impact can be estimated using a simple and widely used relationship:

Climate impact (CO₂e) = Quantity* × Emission factor

In this equation, quantity* refers to the amount of the selected activity, material, or product associated with one functional unit.

Depending on the system being analysed, the quantity may represent:

The emission factor expresses the average greenhouse gas emissions associated with one unit of that quantity (for example, CO2/gallon of gasoline (transport), grams of CO2/km (vehicle travel), kg CO2/MWh (electricity generation), or tonnes CO2e/tonne of material (steel/cement)). This normally is available in public database or software and, might be available for spefic material or a full product or process.

In this simplified LCA, emission factors are used to obtain order-of-magnitude estimates. The goal is consistent comparison between the proposed system and the baseline, not precise absolute values.

3.3 Finding an Emission Factor

Try in this order:

3.4 Comparing to Baseline

For each hotspot you quantify:

Results from this step feed directly into KPI scoring in Section 4.

4Score the Sustainability KPIs

Triple bottom line

Building on the system map, hotspot analysis, and simplified quantification, the fourth step is to score a set of Sustainability KPIs. The KPIs in this guide are grouped under the triple bottom line (environmental, social, economic) plus a set of systemic indicators. Each KPI corresponds to a specific question (for example, “How large is the carbon footprint?”, “How inclusive is this service?”, or “How scalable is this solution?”).

Each KPI is given a 0–5 sustainability performance score relative to a relevant baseline. Where possible, the score is informed by quantitative calculations from Section 3 (especially for environmental indicators). Where quantification is not feasible, the score is based on structured qualitative reasoning, but the number always represents the level of sustainability performance.

4.1 Environmental Indicators

Environmental indicators capture burdens and interactions across material extraction, manufacturing, operation, and end-of-life stages, in line with life-cycle thinking as formalised in ISO 14040 and ISO 14044.

E1 Carbon Footprint (CO₂e)
Units: kg CO₂e (total) and/or kg CO₂e per functional unit

Represents the total greenhouse gas emissions associated with the design, expressed as CO₂-equivalent (CO₂e). This includes embodied carbon in materials and operational emissions. In line with greenhouse gas accounting practice, this should consider relevant direct and indirect emission sources across the value chain.

E2 Energy Demand and Efficiency
Units: kWh and/or efficiency (%)

Evaluates the energy required during operation, as well as the extent to which the design reduces energy demand through efficiency measures or the integration of low-carbon or renewable energy sources.

E3 Materials and Circularity
Metrics: recycling %, circularity score, or qualitative narrative

Assesses material choice, resource intensity, recyclability, durability, and end-of-life pathways. The indicator reflects how closely the design aligns with principles of circular economy and sustainable resource management.

E4 Ecosystem & Biodiversity Interactions
Rating: 0–5

Considers how the design interacts with ecosystems and biodiversity, including potential habitat disturbance, pollution risks, or positive contributions such as restoration or improved environmental quality.

4.2 Social Indicators

Social indicators capture safety, equity, inclusion, and societal impacts, consistent with human-centred design and the social dimensions of the UN Sustainable Development Goals.

S1 Safety and Risk Profile
Safety Impact Score: 0–5

Assesses how effectively the design protects users, operators, and surrounding populations from harm, including physical hazards, system failures, and exposure to dangerous substances or conditions.

S2 Community and Stakeholder Impact
Accessibility & Inclusion Score: 0–5

Evaluates the societal value or disruption associated with the system, including accessibility, distribution of benefits and burdens, and the extent to which the solution is accepted and supported by relevant communities and stakeholders. For example, a project that is only usable by people without visual impairments in a context where visually impaired users are clearly affected would score low on this KPI.

S3 Ethics, Privacy, and Inclusivity
Ethical / Privacy Score: 0–5

Considers ethical dimensions of technological use, data protection and privacy, inclusive design, and the avoidance of unintended negative social or ethical consequences.

4.3 Economic Indicators

Economic indicators reflect life-cycle cost and long-term viability, supporting decisions that are both financially and environmentally robust.

Ec1 Cost (Capital and Operational)
Metric: Cost per functional unit (£/unit)

Captures the financial implications of developing, installing, and operating the technology across its lifetime, expressed per functional unit (e.g. per km, per m³ treated, per service delivered).

Ec2 Long-Term Viability
Metric: Lifecycle cost savings (£/year)

Considers durability, maintenance requirements, reliability, and cost savings over time, drawing on concepts from life-cycle costing.

Ec3 Scalability and Resource Availability
Score: 0–5

Evaluates the capacity of the solution to be scaled up or replicated, and the availability of key materials, components, skills, and infrastructure required for broader deployment.

4.4 Systemic / Long-Term Indicators

These indicators capture cross-cutting aspects that influence performance over time and across system boundaries.

D1 Resilience & Reliability
Score: 0–5

Assesses the ability of the system to maintain functionality under operational stresses, failures, external shocks, or changing conditions.

D2 Longevity / Maintenance Demand
Score: 0–5

Reflects expected service life, robustness of components, and the intensity and complexity of maintenance, repair, and replacement cycles.

D3 Governance & Compliance Readiness
Score: 0–5

Evaluates alignment with applicable standards, regulations, and sector-specific governance frameworks, as well as readiness for future regulatory developments.

4.5 Scoring Rubric (0–5 Scale for Qualitative Indicators)

This rubric is used to rate the sustainability performance of the design on each qualitative KPI (e.g. S1–S3, E3–E4, Ec3, D1–D3). The number answers the question: "How sustainable is this aspect of the design compared with a sensible baseline?"

Before scoring, identify your baseline (Section 1) and ask yourself: "Is my design better, worse, or similar to current practice on this KPI?" Then use the rubric below to assign a 0–5 score. Always provide a brief written justification for your score.

Score Sustainability Performance Evidence to Look For
0 Very harmful / clearly unsustainable.
The design makes things significantly worse than the baseline or worse than doing nothing on this KPI. 		• Creates serious negative impacts with no mitigation
• Actively prevents a group from using or benefiting from the design
• Consumes substantially more resources than the baseline
• Violates legal or safety standards
1 Worse than baseline / strongly problematic.
Performance is clearly inferior to the baseline. Some positive aspects exist, but major negative impacts or exclusions dominate. 		• Significant negative impact (e.g. much higher emissions, or accessible only to one user type when others are affected)
• Benefits some groups while disadvantaging others
• Impacts are partially addressed but key issues remain unresolved
• Marginal improvement over doing nothing
2 Weak sustainability performance.
Impacts are similar to the baseline, or only slightly better. Recognized issues are only partially addressed. 		• Performance is comparable to or marginally better than the baseline
• Design acknowledges the issue but does not fully resolve it (e.g. recyclable material but no recycling pathway)
• Some affected groups benefit; others face barriers
• Obvious opportunities for improvement remain unused
3 Acceptable / meets basic expectations.
Design meets minimum legal or good-practice standards and shows clear, measurable improvement over the baseline. 		• Complies with applicable laws or industry standards (e.g. accessibility codes, emissions limits)
• Clear improvement over the baseline, but not exceptional
• Impacts are managed, not minimised
• Most affected groups can access or benefit from the design
• Further sustainability improvements are feasible but not yet implemented
4 Good sustainability performance.
Design is noticeably better than the baseline. Negative impacts are significantly reduced or positive impacts are strengthened. 		• Substantially exceeds minimum standards
• Demonstrates measurable improvement over the baseline (e.g. quantified carbon reduction, documented accessibility features)
• Evidence of thoughtful design choices that reduce harm (e.g. modular design for disassembly, multi-language support)
• Intended users and stakeholders likely to adopt and support the solution
• Some limitations or trade-offs remain, but are justified
5 Very high / exemplary performance.
Design makes a strongly positive or "net-positive" contribution. It addresses root causes of impacts and proactively benefits vulnerable or under-served groups. 		• Goes significantly beyond minimum standards and typical baseline practice
• Strong evidence of deliberate engagement with affected communities (e.g. co-design, user testing, community consultation)
• Identifies and mitigates unintended negative consequences
• Benefits are distributed widely and equitably; vulnerable groups are explicitly supported
• Design is resilient and adaptable to future needs or changing conditions
• Contributes to solving the underlying problem, not just managing symptoms

4.5.1 How to Use This Rubric

Step 1: Identify your baseline

Clearly state what current or conventional solution you are comparing your design against (Section 1). All scores are relative to this baseline, not absolute.

Step 2: Gather evidence

For each KPI, collect evidence relevant to that indicator:

Step 3: Match evidence to score levels

Review the "Evidence to Look For" column. Does your design match the descriptors for a score of 2, 3, 4, or 5? If you have no evidence for a claim (e.g. "accessible to all"), you cannot score it as 4 or 5.

Step 4: Justify your score

Write 1–2 sentences explaining your choice. Reference specific evidence:

Example justification:
"S2 (Community & Stakeholder Impact): Score 4. The design includes accessibility features that exceed legal minimum standards (adjustable text size, keyboard navigation, high-contrast mode). We tested the prototype with 5 disabled users and incorporated their feedback into the final design. However, we did not include audio-description features that would benefit blind users, so a score of 5 is not warranted."

4.5.2 Common Scoring Mistakes to Avoid

5Reflect and Compare

Synthesis & conclusions

The final step is to bring the results together in a short, structured reflection. The goal is not to repeat every detail, but to explain what the sustainability assessment means for the design.

A concise reflection of this kind makes the assessment transparent and decision-relevant, while recognising that it is based on a simplified screening rather than a full LCA.

A. Example – University Matcha Vending Machine vs Standard Coffee Vending Machine (UK Context)

Worked example

A UK university is updating its hot drinks provision by installing new automatic matcha vending machines across campus. These are introduced alongside, and potentially in place of, the existing standard coffee vending machines. Matcha drinks are becoming popular among students due to perceived health benefits, and the vending contractor expects higher sales and improved income per drink.

A.1 Step 1 – Define the System, Functional Unit, Baseline, and Life-Cycle Stages

Both the system under assessment and the baseline deliver the same core function: the on-demand provision of a single hot caffeinated beverage to students and staff.

The following life-cycle stages are considered for both the system and the baseline:

These life-cycle stages define the system boundaries for the assessment and provide the basis for identifying hotspots in the next step.

A.2 Life-Cycle Screening & Hotspots

This section applies the reflective questions from Section 2.1 to the matcha vending machine project. For each life-cycle stage, the reflective questions are answered, and then an overall importance rating is assigned.

Raw Materials and Components

Reflective Questions Answer and Reasoning
What are the primary materials in the system, and why were they selected? Matcha drinks require matcha powder plus milk powder or plant-based creamer (chosen for taste, solubility, shelf-life, and vending compatibility). Standard coffee uses instant coffee granules plus milk powder (selected for low cost and reliable vending performance).
What environmental burdens are associated with producing these materials? Matcha production involves shaded tea cultivation and fine grinding with impacts in land use and processing energy. Milk powder has high upstream impacts (agriculture, drying). Coffee granules also carry agricultural and processing burdens.
Are any materials scarce, hazardous, or highly energy-intensive? No critical scarcity expected for matcha or coffee. Milk powder is resource-intensive. Packaging materials may include mixed plastics that are difficult to manage, but are not central to this stage.
Could recycled, bio-based, or lower-impact alternatives be used? Yes. Lower-impact options include reducing dairy content, switching to lower-impact plant-based creamers, or sourcing certified lower-impact ingredients. Packaging could shift to more recyclable formats if compatible with hygiene.
Do materials introduce risks (corrosion, leaching, microplastic release)? Ingredient powders do not introduce corrosion. Packaging (sachets/liners) and disposable lids can contribute to plastic leakage if not properly captured in waste streams, but this is a secondary concern at this life-cycle stage.
Does the design minimise unnecessary mass or component redundancy? The matcha recipe may use more powder mass (especially milk/creamer) per drink than standard coffee. Reducing powder dose or serving size could minimise mass per drink.

Overall Stage Assessment:

  • Importance Rating: HIGH
  • Justification: The reflective questions reveal that ingredient production has significant environmental burdens (agriculture, processing, drying). The matcha system uses more milk powder per drink than the baseline, increasing the carbon footprint per drink.
  • What drives the impact: Matcha powder and milk powder (or plant-based creamer) required per drink

Processing / Manufacturing

Reflective Questions Answer and Reasoning
What manufacturing processes dominate the system? Both systems rely on industrial manufacture of vending machines (metal forming, plastic moulding, electronics assembly) and packaging/processing of powders. Machine manufacture is broadly similar; ingredient processing differs (matcha grinding and preparation vs instant coffee manufacture).
Are these processes energy-intensive or chemically intensive? Ingredient processing can be energy-intensive (drying, grinding, spray-drying for milk powder). Machine manufacture has typical industrial energy demand. Differences are larger for ingredients than for machines.
Do they generate significant waste, scrap, or emissions? Machine manufacture produces typical scrap and assembly waste. Ingredient processing and packaging also generate waste. Per functional unit, these are usually smaller than agricultural plus ingredient burdens.
Are specialist, high-temperature, or high-precision processes required? Both machines use standard vending manufacture processes. No highly specialist or high-temperature processes unique to matcha vs coffee are expected.
Could the design be simplified to reduce manufacturing effort or complexity? Designs could standardise components across machines, reduce part count, or extend component life. However, differences between matcha and coffee machines are likely modest.
Does assembly rely on materials or processes with particularly high environmental impacts? Both systems rely on similar electronics and metal/plastic components. High-impact elements (electronics) are expected to be comparable between system and baseline.

Overall Stage Assessment:

  • Importance Rating: Low–Medium
  • Justification: Manufacturing processes do generate emissions, but per functional unit, processing and manufacturing impacts are typically smaller than agricultural impacts embedded in ingredients. The processes for matcha and coffee manufacturing are not fundamentally different from baseline practice.
  • What drives the impact: Machine manufacture (similar for both systems); ingredient processing (matcha and coffee production, milk powder drying)

Distribution, Transport & Logistics

Reflective Questions Answer and Reasoning
How far must major components travel during production or deployment? Vending machines and many components are transported from manufacturers to campus (possibly international). Ingredient sourcing is global for both tea and coffee.
Which transport modes are used? Likely a combination of international shipping and road freight for final delivery and restocking.
Are repeated transport journeys required for installation or maintenance? Regular restocking trips are required for both machines. Maintenance visits are occasional. Differences may occur if matcha requires more frequent restocking due to higher demand or smaller packaging units.
Could local sourcing reduce transport-related impacts? Local sourcing is limited for matcha (typically imported from Japan or Asia). Coffee is also largely imported. However, cups, milk powder alternatives, and some consumables may be locally sourced.
Does the system require relocation after deployment? Machines are installed on campus and typically remain in place. Relocation impacts are negligible and similar for both.

Overall Stage Assessment:

  • Importance Rating: Low–Medium
  • Justification: Transport distances are significant (global supply chains), but per functional unit, transport impacts are typically smaller than ingredient production impacts. Both systems have similar transport requirements.
  • What drives the impact: International shipping of machines and ingredients; regular restocking trips

Use and Operation

Reflective Questions Answer and Reasoning
What forms of energy are required during operation? Both machines require electricity for heating water, mixing, dispensing, and standby power. No direct fuel use.
How much energy or fuel is consumed per functional unit? Per drink electricity is expected to be similar. Matcha may require slightly longer mixing/agitation, but order-of-magnitude is comparable.
Does the system generate emissions, noise, heat, or pollution during use? Direct emissions are minimal; impacts depend on electricity grid. Noise/heat are minor and similar between machines. Waste is generated mainly through cups/lids and packaging rather than operation.
Does operation affect wildlife, habitats, or human users? Operation is indoors; wildlife/habitat effects are negligible. Human factors include user satisfaction and accessibility (linked to price and availability).
Does the system reduce environmental burden compared to the baseline? Operational electricity is not expected to be significantly lower than baseline. Any improvement would come from ingredients (recipe) and packaging systems (reusables), not from the operation stage itself.
Could operational performance degrade over time (fouling, wear, loss of efficiency)? Both systems may suffer similar wear, scaling, or fouling. Efficiency may drop slightly without proper maintenance, but differences between matcha and coffee are likely small.
Are there major differences in use behaviour or demand? Increased matcha popularity could increase total drinks sold, affecting total material flow (cups, lids, powders). Per functional unit remains comparable, but total campus impacts could rise with higher volume.

Overall Stage Assessment:

  • Importance Rating: Medium
  • Justification: Per-drink electricity use is comparable between systems and not a key differentiator. The use phase is not a hotspot for this comparison.
  • What drives the impact: Electricity consumption per drink (similar for both systems); potential increase in total demand if matcha is popular

Maintenance, Repair, and Replacement

Reflective Questions Answer and Reasoning
Which components require periodic maintenance or replacement? Both require cleaning systems, mixers, heaters, pumps, seals, and electronics maintenance. Consumable components (filters, seals) are similar.
How frequently does maintenance occur? Routine restocking and cleaning is frequent for both; technical servicing is periodic. Frequency may rise slightly if matcha residues require more cleaning, depending on formulation.
Does maintenance involve travel, fuel use, or hazardous materials? Maintenance involves technician visits (road travel). Cleaning agents may be used but typically not hazardous in large quantities. Similar for both systems.
Does the system generate continuous waste streams during maintenance? Maintenance waste includes wipes, filters, and replaced parts. These are minor compared with cups/lids and ingredient packaging.
Could design modifications extend component lifetime or reduce maintenance frequency? Better dosing, anti-fouling design, easier access for cleaning, and robust components could reduce servicing frequency for both machine types.

Overall Stage Assessment:

  • Importance Rating: Low
  • Justification: Maintenance requirements are similar for both systems and generate minor impacts per functional unit.
  • What drives the impact: Component replacement and servicing visits; cleaning waste

End-of-Life

Reflective Questions Answer and Reasoning
Can the system or its components be reused, recovered, or recycled? Vending machines contain metals and electronics that can be recovered, though recycling depends on take-back routes. Cups/lids are less likely to be effectively recycled due to contamination and mixed materials.
Are materials difficult to separate at end-of-life? Machines contain mixed materials (metals, plastics, electronics), requiring disassembly. Cups/lids and sachets are often composite materials, difficult to separate.
Does the system contain hazardous or problematic waste streams? Electronics can be classed as WEEE and require proper treatment. Single-use plastics (lids, sachets) are problematic if not captured.
Could the solution unintentionally contribute new debris, litter, or pollution? The main risk is increased single-use packaging (cups/lids/sachets) and potential littering. Matcha growth in demand could increase these flows unless mitigated.
Are appropriate disposal or recycling routes realistically available? Campus waste streams often mix recyclables and waste; contamination reduces recycling rates. WEEE routes exist for machines but depend on contractor practices.
Could the design be optimised for modular disassembly and material recovery? Modular machine design and take-back contracts could improve recovery. For consumables, shifting to reusable cups and bulk refill systems would improve circularity.

Overall Stage Assessment:

  • Importance Rating: Medium–High
  • Justification: Every drink generates disposable waste (cups, lids) that is integral to the functional unit. This is a significant and visible impact. The materiality of end-of-life waste per drink is comparable to ingredient impacts, particularly when considering the carbon footprint of plastic production.
  • What drives the impact: Single-use cups, lids, and ingredient sachets generated for every drink; machine end-of-life (shared infrastructure)

General Screening Question: Hospots selection

Based on the screening above, the life-cycle stages are scored as follows:

Life-Cycle Stage Importance Rating Reason for Rating Selected for Quantification?
Raw Materials HIGH Ingredient production (matcha, coffee, milk powder) dominates per-drink impacts. Integral to functional unit. ✓ YES
Processing / Manufacturing Low–Medium Industrial processes generate emissions but per-unit impact is smaller than ingredient burdens. Similar for both systems. No
Transport & Logistics Low–Medium Global shipping occurs but per-unit transport impact is smaller than ingredient impacts. Similar for both systems. No
Use & Operation Medium Electricity use per drink is similar for both systems. Not a key differentiator. No
Maintenance Low Maintenance requirements are similar for both systems and generate minor impacts per functional unit. No
End-of-Life Medium–High Single-use cups/lids/sachets integral to functional unit. Important for both carbon (embodied plastic) and circularity assessment. ✓ YES

Hotspots selected for quantification in Section A.3: Raw Materials and End-of-Life. These are the two highest-importance stages, with impacts that are integral to the functional unit (one drink).

Next step: Section A.3 will quantify the carbon footprint (KPI E1) for both hotspots: (1) Raw Materials (ingredient impacts: matcha, coffee, milk powder), and (2) End-of-Life (embodied carbon in cups and lids per drink).

A.3 Simplified LCA Calculation (E1 – CO₂e per Drink)

Following the methodology in Section 3, a simplified calculation is used to compare the approximate greenhouse gas emissions per drink for the matcha and standard coffee vending machines. The numbers are illustrative for teaching and should not be interpreted as definitive LCA results.

A.3.1 Assumptions

The functional unit is one hot drink (for a fair comparison between the proposed matcha and the tradicional coffee as baseline)

The Raw material and End life are the hostpot stages. For those stages the list of relevant elements are:

Hotspot Proposal Matcha Baseline
Raw material 2 g of matcha powder 1.5 g of instant coffee
Raw material 15 g of milk powder or creamer 12 g of milk powder
End of life Disposable cup + lid Disposable cup + lid

A.3.2 Comparison Table – CO₂e per Drink

Component Quantity Emission factor Matcha vending machine
System
Impact (kg CO₂e)		 Standard coffee vending machine
(baseline)
Impact (kg CO₂e)
Matcha powder / instant coffee 2 g matcha vs 1.5 g coffee Matcha: 6 kg CO₂e/kg
Coffee: 5 kg CO₂e/kg		 0.002 kg × 6 = 0.012 kg CO₂e 0.0015 kg × 5 = 0.0075 kg CO₂e
Milk powder / creamer 15 g (matcha) vs 12 g (coffee) Milk powder: 9 kg CO₂e/kg 0.015 kg × 9 = 0.135 kg CO₂e 0.012 kg × 9 = 0.108 kg CO₂e
Cup and lid 1 disposable set 0.05 kg CO₂e/use 0.05 kg CO₂e 0.05 kg CO₂e
Total per drink 0.012 + 0.135 + 0.05 ≈ 0.20 kg CO₂e 0.0075 + 0.108 + 0.05 ≈ 0.17 kg CO₂e

Key observation: In this simplified example, the matcha vending machine has an estimated footprint of about 0.20 kg CO₂e per drink, while the standard coffee vending machine (baseline) is around 0.17 kg CO₂e. The difference is driven mainly by greater milk powder use and matcha processing, not by the electricity use of the machine itself.

A.4 KPI-Based Sustainability Performance Scores

Building on the hotspot screening (A.2) and quantification (A.3), this section assigns 0–5 sustainability performance scores to KPIs most relevant to the identified hotspots, using the rubric from Section 4.5.

Baseline: Standard coffee vending machine (current campus practice)

All scores are assigned using the four-step process from Section 4.5.1:

  1. Identify baseline – Standard coffee vending machine (stated above)
  2. Gather evidence – Data from A.2 screening and A.3 quantification
  3. Match evidence to rubric – Compare against Section 4.5 score descriptors
  4. Justify the score – Cite specific evidence supporting each score
KPI Code & Indicator Matcha Score Baseline Score Reasoning and Evidence
E1
Carbon Footprint (CO₂e)		 2 3 Matcha is 0.20 kg CO₂e per drink vs baseline 0.17 kg CO₂e (17% higher). Driven by higher milk powder use (15 g vs 12 g) and matcha processing. Matcha matches Score 2 ("Weak performance"): impacts are similar to or only slightly worse than baseline. Baseline matches Score 3 ("Acceptable"): meets minimum expectations for conventional vending.
E2
Energy Demand & Efficiency		 3 3 Both systems require 0.05 kWh per drink. Identical per-drink electricity consumption means neither exceeds minimum expectations. Both match Score 3 ("Acceptable"): neither introduces efficiency improvements nor renewable energy integration. No meaningful difference between systems on this indicator.
E3
Materials & Circularity		 2 3 Both rely on single-use cups, lids, and ingredient packaging with no take-back schemes or reusable pathways. Campus waste streams show contamination reduces recycling rates. Matcha has higher material throughput (15 g milk powder vs 12 g per drink), resulting in Score 2 ("Weak performance"). Baseline scores 3 ("Acceptable") due to lower material flow. Neither system implements design for disassembly or modular recovery.
S2
Community & Stakeholder Impact		 4 3 Matcha increases drink choice and aligns with demonstrated student demand for perceived health benefits. Vending contractor expects higher sales, indicating strong stakeholder support. Matcha matches Score 4 ("Good performance"): demonstrates measurable improvement over baseline. However, premium pricing creates an equity barrier, preventing Score 5. Baseline matches Score 3 ("Acceptable"): provides broad, affordable access to all students, meeting basic expectations for inclusive service.
Ec1
Cost (Capital and Operational)		 2 4 Matcha beverages are sold at premium price without environmental benefit (carbon footprint is 17% higher, not lower). Matcha matches Score 2 ("Weak performance"): higher cost without corresponding sustainability gain. Baseline matches Score 4 ("Good performance"): offers excellent affordability and strong value per drink, making beverages accessible to all students regardless of income. Cost accessibility is a major differentiator favoring the baseline.
D1
Resilience & Reliability		 3 4 Standard coffee machines are mature, proven technology with established maintenance routines. Matcha is newer technology with potentially more complex powder handling, dosing, and mixing, and may require higher maintenance frequency. Matcha supply chains are less mature in some regions. Matcha matches Score 3 ("Acceptable"): acceptable but introduces technological complexity that reduces robustness. Baseline matches Score 4 ("Good performance"): decades of proven deployment, stable supply chains, and established maintenance protocols.

KPIs not scored: E4, S1, S3, Ec2, Ec3, D2, D3

Reason: These KPIs were considered during hotspot screening but were judged not to differ significantly between the proposed system and the baseline in this context, or are not materially relevant to the matcha vs coffee comparison.

A.5 Reflect and Compare

The final step brings the sustainability assessment results together in a short, structured reflection. The goal is to explain what the assessment means for the matcha vending machine design, not to repeat every detail from A.2–A.4.

A.5.1 Across the Triple Bottom Line

Environmental Dimension (E-KPIs): The matcha vending machine performs worse than the baseline on carbon footprint (E1: score 2 vs 3), primarily due to higher milk powder consumption (15 g vs 12 g) and matcha processing. Energy demand (E2) is identical for both systems (score 3 each). Materials and circularity (E3) performance is weak for both due to single-use cups and contaminated waste streams, with matcha slightly worse due to higher material throughput (E3: score 2 vs 3). Neither system includes reuse schemes or improved recycling pathways.

Social Dimension (S-KPIs): The matcha system scores higher on community impact (S2: score 4 vs 3) by providing drink choice and meeting demonstrated student demand for perceived health benefits. However, premium pricing creates an equity barrier, potentially excluding lower-income students. Other social KPIs (S1 Safety, S3 Ethics/Privacy) are not materially different between systems and thus not scored.

Economic Dimension (Ec-KPIs): The matcha system scores poorly on cost per functional unit (Ec1: score 2 vs 4), as premium pricing increases user costs without corresponding environmental benefit. The baseline's affordability (score 4) is a significant advantage for accessibility. Long-term viability (Ec2) and scalability (Ec3) are not scored here but would require additional analysis of operational durability and market acceptance.

Systemic Dimension (D-KPIs): The baseline coffee system scores higher on resilience and reliability (D1: score 4 vs 3), as it is a mature, proven technology with established maintenance routines and stable supply chains. The matcha system introduces technological and supply-chain complexity that reduces robustness at this early stage. Longevity (D2) and governance (D3) are not scored but should be considered in any full assessment.

A.5.2 Relative to Baseline

Clearly better: The matcha system is clearly better on community and stakeholder impact (S2: 4 vs 3). It increases drink choice and aligns with demonstrated student demand for perceived health benefits, improving perceived wellbeing and stakeholder support.

Similar performance: Energy demand (E2) is identical for both systems (3 vs 3). Both meet basic operational expectations but neither incorporates efficiency improvements or renewable energy sources.

Worse than baseline: The matcha system underperforms on three critical dimensions:

These represent significant sustainability disadvantages relative to the baseline.

A.5.3 Hotspots and Trade-offs

Remaining hotspots: From Section A.2 screening, two hotspots were identified as HIGH or MEDIUM–HIGH importance:

Key trade-off: The matcha system presents a clear trade-off between social benefit and environmental/economic performance:

This design prioritizes perceived health and student preference over environmental and economic sustainability. The university must decide whether the social benefit (student satisfaction) justifies the environmental and cost penalties.

A.5.4 Uncertainties and Limitations

Strong data: The carbon footprint (E1) assessment is well-supported by quantified calculations in A.3 using published emission factors for matcha powder, coffee, milk powder, electricity, and cups. The comparison (0.21 vs 0.18 kg CO₂e per drink) is based on explicit assumptions and order-of-magnitude estimates appropriate for a simplified LCA.

Key assumptions that could affect conclusions:

Missing information:

A.5.5 Conclusion: Is This Design Sustainable?

Is the matcha vending machine more sustainable than the baseline?

The answer depends on which sustainability dimension is prioritized:

Recommendation: The matcha system is NOT overall more sustainable than the baseline when considering the triple bottom line. The social benefit (increased choice) does not outweigh the combined environmental and economic costs. However, if the university's strategic goal is to improve perceived student wellbeing and satisfaction (not environmental sustainability), the matcha system achieves that objective.

If proceeding with matcha vending, recommended improvements:

This example demonstrates how sustainability assessment translates quantitative data (A.3), qualitative screening (A.2), and KPI scoring (A.4) into a transparent decision-making framework. The matcha vending machine is not inherently unsustainable, but it requires intentional design choices and supporting infrastructure (reusable cups, low-carbon sourcing, equitable pricing) to deliver genuine sustainability benefits.

References and Standards (Indicative)

Further reading

The following references provide foundational material for sustainability assessment, the triple bottom line, and life cycle analysis. They are suggested sources for deeper study and for underpinning more advanced quantitative work.