N Kotsu — Japan
Four LPG taxis of the same model were compared against one shared reference consumption figure of 11.89. Three improved, by +8.4%, +5.9%, +10.1%. The fourth came out at −6.6% — it used more fuel after treatment than the reference. That is the only negative measurement in all 386 records we hold, and that fact says as much about the dataset as it does about this taxi.
One negative result in 386 measurements is not a reassuring statistic. It is a warning that the dataset was filtered before it reached us — and this page is where we say so.
| Operator | Recorded only as N交通 — a taxi operator, name abbreviated in the source itself |
|---|---|
| Vehicles | 4 LPG taxis, all the same model (Zendai Japan Taxi) |
| Method | 基準燃費と比較 — comparison against a reference consumption figure |
| Reference figure | 11.89 — identical for all four vehicles |
| Results | +8.4%, +5.9%, +10.1%, −6.6% |
| Negative results | 1 of 4 here — and 1 of 386 across the whole dataset |
| Measurement period | Not recorded in the dataset |
Every measurement, not just the best one
| Vehicle | Before | After | Change |
|---|---|---|---|
| Zendai Japan Taxi (1) | 11.89 | 12.89 | +8.4% |
| Zendai Japan Taxi (2) | 11.89 | 12.59 | +5.9% |
| Zendai Japan Taxi (3) | 11.89 | 13.09 | +10.1% |
| Zendai Japan Taxi (4) | 11.89 | 11.11 | −6.6% |
| Median across all 4 measurements | +7.2% |
Method before result
All four taxis were compared against the same reference consumption figure of 11.89 rather than against their own individual pre-treatment history. That is worth understanding before reading the percentages: what varies between the four rows is only the after figure. A vehicle whose true baseline was above 11.89 would show an improvement it never made, and one whose true baseline was below it would show the opposite.
The fourth taxi recorded 11.11 against that reference — −6.6%. We have no explanation for it in the data, because the data contains no route, load, driver or seasonal information to explain it with.
The more important observation is about the dataset as a whole. Across all 386 measurements we hold, exactly 1 is negative. Real fuel measurements on real vehicles do not behave that way; a genuine unfiltered dataset contains failures, no-changes and reversals in quantity. A set with one negative result in 386 has been filtered somewhere before it reached us, and we do not know by whom or on what basis.
Every percentage on this page was recalculated by us from the recorded before-and-after figures rather than taken from the summary column of the source; all of them reproduce the recorded value. That is a check on transcription, not on the measurement itself — it confirms the arithmetic is right, not that the reading was.
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
- The single shared reference figure of 11.89 is the central weakness. Four vehicles measured against one common expectation is not four independent measurements.
- The operator is recorded only as an initial in the source dataset. We cannot name it because we do not know it — our approval to publish operator names does not create information the record never held.
- We cannot explain the −6.6% result, and we do not attempt to. Publishing it without an explanation is more honest than constructing one.
- Four vehicles of one model at one operator, with no control group and no recorded period.
- The unit behind the LPG figures is unresolved. The dataset labels these columns km/L, but its own CO₂ calculation uses an emission factor of 3.00 kg per kilogram of LPG, which only makes sense if the figures are kilometres per kilogram. The percentage change is unaffected either way — it is a ratio — but we flag it rather than quietly picking one.
- This is a dataset entry, not a trial report. What we hold is the before-and-after fuel-efficiency figure per vehicle as recorded in the master test dataset — not the operator’s raw fuel logs, not the odometer readings behind them, and not a written test protocol.
- There is no control group. No comparable untreated vehicle was tracked over the same period, so seasonal, route and traffic effects cannot be separated from the treatment.
- The measurement dates and the length of each measurement period are not recorded in these entries. We therefore cannot say how far each vehicle ran between the two readings, or which months the comparison covers.
- The figures were recorded by the operator or by the local distributor, not by an independent party, and we cannot re-derive them from primary records.
Reading this evidence in context
For an operator reading this site, the useful takeaway is not the taxi that got worse. It is that we told you the ratio: 1 negative in 386. Any supplier presenting hundreds of field measurements with essentially no failures is presenting a filtered set, whether or not they did the filtering themselves.
It also sets the standard we hold our own new trials to. The Waste Services and Sanden Kotsu datasets exist because we now insist on protocols that record every vehicle, including the ones that go the wrong way.
A pilot on your own fleet will produce vehicles that improve, vehicles that do not move and occasionally a vehicle that gets worse. That is what a real measurement series looks like, and it is what we will show you.
Questions operators ask about this trial
Why is one bad result worth its own page?
Why can you not name this operator now that names are released?
What caused the negative result?
Does this change how we should read the other pages?
Provenance
- Source
- Eco-Spray / NanoEFX master test dataset, compiled 22 March 2020 — operator-named section
- Recalculation
- All percentages recomputed from the recorded before-and-after figures
- Raw records
- Held by the operator or the local distributor — not in our possession
- Operator entry
- N交通（タクシー） — abbreviated in the source; full name not held
- Method as recorded
- 基準燃費と比較 (against reference consumption)
- Cross-reference
- The full 386-measurement dataset is published at /evidence/field-data/
- 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.