Hot-spring hotel — heavy-oil boilers — Japan
Two heavy-oil boilers at a Japanese hot-spring hotel were compared month against the same month a year earlier. All six measurements fall between 10.7% and 16.0% lower fuel consumption — the most consistent stationary result in our records, and evidence that the treatment is not limited to vehicle engines.
Stationary plant removes several variables that make vehicle trials messy: no route, no driver, no load variation from traffic — just a burner running against a heat demand.
| Operator | Hot-spring hotel, Japan — operator not named pending approval |
|---|---|
| Plant | 2 heavy-oil boilers |
| Baseline | October, November and December 2013 |
| Follow-up | October, November and December 2014 |
| Measured quantity | Heavy oil consumption in litres per month |
| Comparison | Same calendar months, one year apart |
| Result | Between 10.7% and 16.0% lower consumption in all six measurements |
Every measurement, not just the best one
| Boiler | Month | 2013 (L) | 2014 (L) | Change |
|---|---|---|---|---|
| Boiler 1 | October | 21,498 | 18,703 | −13.0% |
| Boiler 1 | November | 28,007 | 24,466 | −12.6% |
| Boiler 1 | December | 36,201 | 31,855 | −12.0% |
| Boiler 2 | October | 22,000 | 18,485 | −16.0% |
| Boiler 2 | November | 27,500 | 23,385 | −15.0% |
| Boiler 2 | December | 37,300 | 33,318 | −10.7% |
Method before result
Monthly heavy-oil consumption was taken from the hotel’s own records for October, November and December in both 2013 and 2014, with the treatment applied in the intervening period.
Comparing the same calendar months a year apart is what makes this dataset readable: a hotel boiler’s consumption is driven mostly by outside temperature and by how much hot water the building needs, both of which follow a strong annual pattern. October against October controls for that far better than any before-and-after comparison within a single season could.
The limits of this trial
We publish these next to the result rather than in a footnote. If a limitation would change how you read the number, you should read it at the same time as the number.
Known limitations
- Occupancy is not controlled. A hotel with fewer guests in 2014 than in 2013 would use less heavy oil regardless of any treatment, and we do not hold occupancy figures.
- Weather is not controlled beyond the month-matching — a milder autumn in 2014 would produce the same direction of result.
- The operator is not named in the records we hold, so this trial cannot currently be independently verified by a third party.
- We hold a derived summary rather than the hotel’s primary records.
- A separate gas-boiler measurement from a different operator in the same records is internally inconsistent and is deliberately excluded from this page until it is clarified.
Reading this evidence in context
This is our clearest indication that the effect is not specific to vehicle engines: the same treatment logic applied to a burner drawing combustion air produced a consistent result across six independent monthly measurements.
For operators of stationary plant — hotels, laundries, food processing, district heating — the practical appeal is that a boiler runs a far more repeatable duty cycle than any vehicle, which makes a properly designed trial easier to interpret.
The missing pieces are occupancy and weather data. With those, this dataset would move from indicative to solid.
Questions operators ask about this trial
Why is the operator not named?
Could the saving just be a warmer winter or fewer guests?
Does NanoEFX work on boilers as well as engines?
Provenance
- Operator
- Hot-spring hotel, Japan — not named pending approval
- Plant
- 2 heavy-oil boilers
- Measurement periods
- October–December 2013 (baseline); October–December 2014
- Source
- Japanese field-study summary — derived record; operator raw data not held
- Last checked
- 15 August 2026
The only baseline that matters is yours
Every trial on this site was run on someone else’s vehicles, duty cycle and baseline. A NanoEFX pilot measures yours — and we will help you design it with a control group so the result stands up.