Where does a product spend its energy and its carbon: in its materials, its making, its journey, its use or its disposal? Five numbers, a bill of materials and a calculator you can run in the page.
A full life-cycle assessment needs hundreds of inputs, takes weeks and returns a precision that design decisions rarely need. Early in a design, the useful question is coarser: which phase of life dominates? If it is the material, choose a lighter or less energy-hungry one. If it is the use phase, cut mass or losses, and stop worrying about the packaging. The Eco Audit tool of CES (now Granta) EduPack answers that question from a short bill of materials and a few lines on transport and use.
This chapter rebuilds that tool in its simplest form. Every number below is computed in your browser by about forty lines of code, using a small table of typical material, process and transport data. The same model, data and examples are in a Jupyter notebook for those who prefer Python.
The audit splits life into five phases. Each is estimated from one or two inputs multiplied by an energy or carbon intensity from the database.
Two formulas need a word. A product that sits still and uses power (a kettle, a fridge, a heater) is in static mode. Its delivered energy is converted to primary energy by an efficiency factor η that accounts for the power station or burner:
A part that is carried (a bumper, a seat, the heater in the back of a van) is in mobile mode. It is charged the fuel needed to move its own mass, per tonne-kilometre:
Recycled content lowers the material phase linearly: with a recycled fraction
The database holds 31 materials, 8 processes, 8 transport modes, 5 static conversions, 4 vehicles and 3 end-of-life routes. Values are rounded, typical figures in the spirit of Ashby's Materials and the Environment; where the white paper prints a value (PET, polypropylene, polymer molding, the 14 t truck, the electric-to-mechanical factor) it is used as is. They are teaching data, close enough to reproduce the white paper's case studies within about 10%.
| Material | Family | MJ/kg | kg CO₂/kg | Recycled MJ/kg | Typical recycled | Energy, virgin vs recycled |
|---|
Pick a product or build your own. Edit any cell: the chart and the verdict update as you type. The presets are the white paper's case studies plus a reusable bottle.
| Component | Material | Recycled % | Primary process | Mass (kg) | End of life |
|---|
| Stage | Mode | Distance (km) |
|---|
This is the EduPack tutorial case (Exercises 20–22).
Exercise 21 asks what 35% recycled PET would do. EduPack reports an 11% reduction in first-life energy; this model gives 13% with its rounded recycled-PET value. Slide the recycled fraction to see the trade: recycled content lowers the first life, and recycling at end of life credits the next one.
The bigger lever is reuse. A 300 g stainless-steel bottle shipped from Asia, refilled from the tap and washed a hundred times costs far more to make than one PET bottle, but it is made only once.
A 2 kW kettle, made in South-East Asia and air-freighted 11 000 km to Europe, boils one litre twice a day, five minutes in all, for three years. Its nine components weigh 1.3 kg. Choose “Electric jug kettle” in Figure 6.3: the use phase is 94% of the energy. Even air freight, the most energy-intensive mode, costs 3%. Switch it to sea freight and the transport bar vanishes, but the total moves by less than 3%. A kettle that wastes 20% less heat (better insulation, boiling only the water you need) saves more energy than all its materials embody. That is the white paper's lesson: the eco audit tells you where not to bother.
The white paper audits a 1 800 kg family car driven 25 000 km a year for ten years. Material and use are the only phases that count: 151 GJ for the materials here (162 GJ in the paper) against 927 GJ of fuel (884 GJ). The audit makes a familiar point quantitative: in a vehicle, mass is energy.
The white paper then asks whether a 10 kg aluminium bumper should replace a 14 kg steel one. Aluminium costs about four times more energy to produce, but saves fuel every kilometre. The break-even distance answers the question:
With virgin aluminium the break-even is about 200 000 km, close to the car's whole life: the substitution barely pays. With recycled aluminium, whose production needs a tenth of the energy, it falls below 100 000 km and the aluminium bumper wins clearly. The same audit gives the opposite answer depending on the supply chain.
The last white-paper case uses both use modes at once. A 9.3 kW portable LPG heater warms a workplace two hours a day, 20 days a year, and rides around in a light goods vehicle 60 km a day all year. Static use (burning gas) is 87% of the use energy; carrying the heater's 7 kg in the van is the other 13%. In Figure 6.3, choose the heater and set the van distance to zero: the use bar barely shrinks. Halve the heater's operating hours and it halves.
The calculator's numbers, recomputed live, against the values printed in the white paper and the EduPack exercise.
| Product | Phase | White paper | This model | Difference |
|---|
The largest gap is in manufacture for the bottle, where the white paper's own table (6.8 MJ/kg for polymer molding) and its summary chart (36 MJ) disagree; this model follows the table. Everything else agrees within about 10%, well inside the accuracy an eco audit claims.
The audit's output is a direction, not a score. The dominant phase points to one of five strategies:
| Dominant phase | What to do | Examples above |
|---|
Three limits are worth remembering. Energy and CO₂ are two indicators among many: water, toxicity and land use, which Chapters 1 and 3 weigh with eco-costs and ReCiPe points, are absent. The database holds averages: a material's real footprint depends on its plant, its grid and its recycled share. And the end-of-life potential is a potential: it is realised only if the material is actually collected and recycled.
The Jupyter notebook notebooks/eco_audit.ipynb contains the same model in Python (audit(product, data)), the same data (data/ecoaudit.json) and the seven products, with plots and the exercises: the 35% recycled bottle, sea versus air freight for the kettle, the bumper break-even, and a template to audit your own product. It runs locally or on Google Colab, and the data are fetched from this site's repository when the file is not found.
Open in Colab Download the notebook
The method follows the CES EduPack Eco Audit Tool white paper (Ashby, Coulter, Ball and Bream, 2012) and the bottle exercise of the Granta EduPack 2024 tutorials. The database in data/ecoaudit.js is a rounded teaching set built for this chapter, not the Granta database: use Granta EduPack or a full LCA database for real decisions. The reusable bottle is a new example. Data and model are generated by tools/ecoaudit_data.py and notebooks/ecoaudit.py.