---
title: "Real-Time Visibility in 2026: The Emissions Your Route Plan Cannot See"
id: "27042"
type: "post"
slug: "real-time-visibility-stationary-emissions-engine-hours-2026"
published_at: "2026-09-24T16:00:00+00:00"
modified_at: "2026-09-24T15:14:43+00:00"
url: "https://locus.sh/blogs/real-time-visibility-stationary-emissions-engine-hours-2026/"
markdown_url: "https://locus.sh/blogs/real-time-visibility-stationary-emissions-engine-hours-2026.md"
excerpt: "Refrigeration burns fuel by the hour, but every published emission factor charges it by the kilometre. Modelling two chilled operations found the same uplift understating one by 70% and overstating the other by 28%."
taxonomy_category:
  - "General"
---

#### [General](https://locus.sh/blogs/category/general/)

# Real-Time Visibility in 2026: The Emissions Your Route Plan Cannot See

[Anas T](/author/anas_locus/)

Sep 24, 2026

15 mins read

## Key Takeaways

- The UK Government applies a flat refrigeration uplift of 19.3% for rigids and 15.9% for articulated vehicles to the per-kilometre factor, based on a 2009 study, although a refrigeration unit consumes fuel by the hour.
- Zemo Partnership chamber testing puts a diesel transport refrigeration unit at 1.8 litres an hour, which is roughly 4.52 kg CO2e for every hour the unit runs.
- Modelled against that, a dense urban chilled round generated 1.70 times the refrigeration emissions the distance-based uplift attributes to it, while a sparse regional run generated only 0.72 times.
- The direction of the error is stable across the published range of unit burn rates, so it is structural rather than a product of the assumptions.
- Locus reasons across more than 250 real-world constraints and retains executed time alongside planned distance, which is the only basis on which a stationary emission can be measured.

## Why Time-Based Emissions Break Distance-Based Factors

Conversion factors for road freight are built from distance. The UK Government’s methodology takes miles per gallon figures from Department for Transport statistics and [converts them to grams of CO2 per kilometre using the standard fuel conversion factor for diesel](https://assets.publishing.service.gov.uk/media/66a9fe4ca3c2a28abb50da4a/2024-greenhouse-gas-conversion-factors-methodology.pdf)
. Because those MPG figures come from real fleet operation, ordinary idling is already averaged into the base factor. The problem is not that stationary burn is missing. It is that it has been converted into a per-kilometre quantity at one fleet-average relationship between time and distance, and applied to operations that do not share it.

Refrigeration makes the mismatch explicit, because it is handled as a separate adjustment. The same methodology applies a [19.3% and 15.9% uplift to rigid and articulated refrigerated vehicles respectively, with 17.3% on the average factors, based on average data for different sizes of refrigerated HGV](https://assets.publishing.service.gov.uk/media/66a9fe4ca3c2a28abb50da4a/2024-greenhouse-gas-conversion-factors-methodology.pdf)
 from a 2009 study. The uplift is a percentage of a distance-based figure. The equipment it represents runs on a clock.

The physical quantity is well established. Zemo Partnership testing, conducted in controlled chambers at chilled and frozen set points with simulated door openings, puts a diesel transport refrigeration unit at [an average of 1.8 litres of diesel per hour, 1.9 in summer and 1.7 in winter](https://www.zemo.org.uk/assets/reports/Zemo_TRU_emissions_report2021.pdf)
. At the published diesel factor that is about 4.52 kg CO2e for each hour the unit is running, whether the vehicle is on a motorway or parked outside a shop.

This has a commercial edge as well as a technical one. Two chilled carriers tendering for the same contract, both reporting honestly against the same official factor set, will submit figures distorted in opposite directions purely because of the shape of their existing work. The urban operator looks cleaner than it is and the trunk operator looks worse, and neither difference reflects anything either of them controls. A shipper comparing those numbers is comparing operating patterns without knowing it.

The gap between those two ways of counting grows with every trend in urban delivery. The World Economic Forum projects that without intervention [the number of delivery vehicles in the top 100 cities globally will increase by 36% until 2030, with congestion rising by over 21%](https://www3.weforum.org/docs/WEF_Future_of_the_last_mile_ecosystem.pdf)
. Congestion adds hours without adding kilometres, which is precisely the direction that makes a distance-based factor wrong.

| Also Read: Beyond the Highway: Real-Time Visibility and Yard Management |
| --- |

## How the Measurement Goes Wrong

### 1. The plan produces a distance

Route optimisation outputs kilometres per route and per stop. This is the number that reaches the emissions calculation, because it exists before the vehicle moves and is available for every shipment.

### 2. A factor converts that distance into emissions

The factor is selected by vehicle class and load, and where the vehicle is temperature-controlled a refrigeration uplift is added as a percentage on top.

### 3. The uplift assumes a fixed relationship between time and distance

Expressing an hourly load as a percentage of a per-kilometre figure embeds an assumption about how many hours a vehicle spends per kilometre. That assumption is the fleet average behind the underlying statistics.

### 4. Real operations sit either side of that average

A stop-heavy urban round covers few kilometres in many hours. A trunk run covers many kilometres in few hours. Both receive the same percentage uplift.

### 5. The error compounds over a reporting period

Because the direction of the error is a property of the operating pattern rather than of any single day, it does not average out across a year. A chilled urban network understates every month.

### 6. Only the executed record can correct it

Engine hours, unit run time and stationary duration exist in telemetry and in the execution record, not in the plan. Without them the correction cannot be calculated, which is why this is a visibility capability rather than a modelling one.

| Also Read: What Is Last Mile Visibility |
| --- |

## What the Model Shows

The model applies published conversion factors to stated route profiles rather than to observed customer data. Two archetypes are built with balanced angular clustering, nearest-neighbour sequencing and local search: a dense urban round served by a rigid vehicle of 7.5 to 17 tonnes, and a sparse regional run served by an articulated vehicle. Refrigeration emissions are then calculated two ways, once by the published distance-based uplift and once by run time at the tested unit burn rate.

**The two archetypes have very different time-per-kilometre profiles.** The urban round averaged 68.3 km over 2.92 hours, or 2.57 minutes per kilometre. The regional run averaged 230.2 km over 5.23 hours, or 1.36 minutes per kilometre. The urban operation spends nearly twice as long per kilometre, which is exactly the variable the uplift holds constant.

**The published uplift understates the urban round by 70%.** Expressed per vehicle-kilometre, the refrigerated factor for a rigid of 7.5 to 17 tonnes exceeds the standard factor by 0.11355 kg CO2e, so the uplift attributes 7.76 kg to the modelled round. Run time at 1.8 litres an hour produces 13.22 kg. The ratio is 1.70.

**It overstates the regional run by 28%.** For articulated vehicles the uplift is 0.14236 kg CO2e per kilometre, attributing 32.77 kg across 230.2 km. Run time produces 23.64 kg. The ratio is 0.72, in the opposite direction, from the same published method.

**The swing between the two is 2.36 times.** Two chilled operations, both reporting honestly against the same official factor set, will misstate their refrigeration emissions by amounts that differ by more than a factor of two and point opposite ways. Neither has done anything wrong.

**The direction survives the assumptions.** Across the published range of unit burn rates, from 1.57 litres an hour for chilled loads to 2.06 for frozen, the urban ratio runs 1.49 to 1.95 and the regional ratio 0.63 to 0.83. The sign never changes, which is what makes this structural rather than a product of the inputs chosen.

**At depot scale the misstatement is material.** The urban round understates by 5.45 kg of CO2e per route. Across eleven routes a day over 250 operating days that is 15.0 tonnes a year from one depot, from refrigeration alone. The regional operation overstates by 9.12 kg per route, or 20.5 tonnes a year across nine routes. Neither figure is enormous against a whole network, and both are large enough to matter in a customer’s Scope 3 return, where the carrier’s number is reported as given.

**What the model does not cover.** It isolates refrigeration because that is the component the factor set handles explicitly and the one with published burn rates. Tail lift operation, cab climate during statutory breaks and engine idling at stops all add stationary burn on the same time basis, and all of them sit inside the averaged base factor rather than being separately identified. Their effect runs in the same direction and is not quantified here.

| Also Read: Route Optimisation Saves Emissions You Cannot Report: The Scope 3 Counterfactual Problem |
| --- |

## Planned Distance and Executed Time: Key Differences

| Dimension | Plan-derived emissions | Execution-derived emissions |
| --- | --- | --- |
| Input available | Kilometres, before the vehicle moves | Engine hours, unit run time, stationary duration |
| Handles refrigeration by | A percentage uplift on distance | Run time at a measured burn rate |
| Accuracy on stop-heavy urban work | Understates, 1.70 times in this model | Reflects actual hours |
| Accuracy on trunk runs | Overstates, 0.72 times in this model | Reflects actual hours |
| Behaviour in congestion | Blind, hours rise and kilometres do not | Captures the increase |
| Error over a reporting year | Compounds in one direction | None from this cause |
| Requires | A routing system | A control tower carrying the executed record |

## What to Look for in Visibility and Tracking Platforms

### Engine hours and unit run time retained per route

The correction is impossible without the time dimension. A platform should hold engine-on time, refrigeration run time and stationary duration against each route and each stop, not just arrival and departure timestamps.

### Stationary time separated from travel time

Total duration is not enough, because a vehicle waiting at a dock, a vehicle held in traffic and a vehicle moving all burn differently even though the clock runs the same way for each. The split is what allows a time-based figure to be built at all, and it is also what makes the result actionable rather than merely more accurate.

### Executed record reconcilable to the plan version

An operation that re-optimises during the day has several candidate distances and several candidate durations. Emissions calculated on the executed record must be traceable to the plan version it departed from, or period comparisons lose their basis.

### Telemetry integrated rather than exported

Where refrigeration telemetry lives in a separate system from dispatch, the two have to be joined by hand at reporting time, which means it happens quarterly at best and breaks whenever a carrier changes. The value comes from the join being continuous, because a quarterly reconciliation can produce a number but cannot change a decision. The practical test is whether an operator can see, today, which routes ran their refrigeration longest relative to the distance they covered.

### Both figures produced, with the difference visible

A platform should be able to show the distance-derived estimate and the time-derived measurement side by side. The gap between them is the size of the correction, and an operation cannot argue for a better method without being able to quantify what the current one costs it.

| Also Read: Best TMS for Cold Chain and Temperature-Controlled Logistics |
| --- |

## Visibility in Practice

**A leading North American retailer.** Ocean, rail and road ran through six separate legacy systems, so an exception in one mode stayed invisible in the others until it surfaced as a store-level stockout. Consolidation produced more than $1M in savings with exceptions resolved in under two hours and 95%+ route compliance. A single executed record across modes is the precondition for measuring anything on a time basis rather than a planned one.

**A Canadian grocery brand delivering fresh and perishable goods.** Home delivery across more than 30 cities through contracted third-party fleets, where temperature integrity and elapsed time are the same problem. Deliveries ran 33% faster at 15% lower fulfilment cost, with customer support resolution 10 to 20 times quicker. In chilled operations every hour saved is both a quality outcome and a refrigeration emissions outcome, which is unusual and worth exploiting.

**A Fortune 50 parcel and logistics network.** More than a million freight shipments a year across 51 sites, each planning independently with no shared view of state. Centralising raised weekly execution from 75% to 92% and surfaced more than $14M in unused capacity at 99.99% uptime. Capacity invisible to every local view is the same category of problem as hours invisible to a distance-based calculation.

## Common Mistakes in Measuring Stationary Emissions

**Assuming the base factor omits idling.** It does not. Factors derived from fleet miles per gallon already contain average stationary burn, so adding a separate idling estimate on top double counts. The error is misallocation across operating patterns, not omission.

**Applying the refrigeration uplift without checking the time profile.** The uplift is a percentage of distance, so it is only right for an operation running at the average hours per kilometre behind the statistics. Stop-heavy chilled work needs the time-based calculation to avoid understating by a margin that does not wash out.

**Treating a dwell reduction as a service metric only.** Cutting an hour of stationary time on a refrigerated vehicle removes roughly 4.52 kg CO2e regardless of distance travelled. Operations that already track dwell for SLA reasons hold the data for an emissions case nobody is making, and it is one of the few interventions where the service argument and the carbon argument point the same way without a trade-off to negotiate.

**Reporting a single figure without its basis.** A distance-derived estimate and a time-derived measurement are different numbers and both are defensible. Publishing one without saying which it is leaves a customer comparing your figure against a supplier who chose the other, and the comparison will be decided by methodology rather than by performance. Stating the basis costs nothing and is the only thing that makes the number comparable.

| Also Read: TMS: Decarbonising the European Supply Chain |
| --- |

## How Locus Approaches Visibility and Stationary Emissions

Locus, the world’s first Decision-Intelligent, Agentic TMS, retains the executed record alongside the plan that produced it, which is the structural requirement for measuring anything that accumulates with time. The [Control Tower](https://locus.sh/control-tower-software/)
 compares planned against actual for every open order and carries arrival, departure and dwell at each stop, so stationary duration is a recorded quantity rather than a residual inferred from distance. The [route planning and dispatch layer](https://locus.sh/route-planning-system/)
 reasons across more than 250 real-world operating constraints including temperature zone, time windows and driver hours, so the plan and the executed record describe the same shipment in the same terms and can be reconciled rather than compared loosely. Six governance mechanisms covering explainability, traceability, evaluation, autonomy levels, execution sandbox and human-in-the-loop keep each figure traceable to the plan version and the state that produced it, which is what allows a distance-derived estimate and a time-derived measurement to be published side by side with the difference explained.

The platform reasons across those constraints over 1.5B+ deliveries for 360+ enterprise customers in 30+ countries at 99.99% uptime, with $320M+ in aggregate logistics cost savings, 800M+ miles reduced and 17M+ kg of CO2 avoided. Locus has been [recognised by Gartner for seven consecutive years](https://locus.sh/analyst-recognition/)
, including the 2026 Gartner Hype Cycle for Supply Chain Execution and Logistics Technologies and the 2026 Gartner Market Guide for Multicarrier Parcel Management Solutions, where ShipFlex is featured as a Representative Vendor. Locus holds Leader designation in the QKS SPARK Matrix for Transportation Management Systems 2025 and the #1 position for Route Planning in G2’s 2026 Best Software Awards. In October 2025, Ingka Investments, the investment arm of Ingka Group, the world’s largest IKEA retailer, acquired Locus. Locus continues to operate independently.

Two deployments show what the executed record makes possible. A [leading North American retailer](https://locus.sh/case-studies/retailer-multimodal-logistics-automation/)
 ran ocean, rail and road across six legacy systems, so no single record described a movement end to end and exceptions in one mode were invisible in the others. Consolidating onto Locus produced more than $1M in savings, 99%+ on-time store delivery, 95%+ route compliance, exceptions resolved in under two hours, an 80%+ reduction in manual dispatch and break-even inside year one. A [Canadian grocery brand](https://locus.sh/case-studies/grocery-carrier-orchestration/)
 delivering fresh and perishable goods to homes across 30+ cities through contracted third-party fleets achieved 33% faster deliveries, 15% lower fulfilment cost, 25% less manual shipping time and customer support resolution 10 to 20 times faster. In a chilled network those hours are not only a service improvement; every one of them is refrigeration fuel that was not burned.

Refrigeration, tail lifts and cab climate consume fuel by the hour, while every published conversion factor charges them by the kilometre, and the resulting error tracks how long an operation spends per kilometre rather than how carefully it reports. Modelling two chilled archetypes against the same official uplift found a dense urban round understated by 70% and a sparse regional run overstated by 28%, a swing of 2.36 times, with the direction stable across the full published range of unit burn rates. Correcting it needs engine hours and stationary duration, which exist in the executed record and not in the plan. Locus carries that record against the plan version that produced it, so time-based emissions can be measured rather than estimated from distance. [Request a Locus visibility and emissions data review](https://locus.sh/schedule-demo/)
 to see how far your reported figures sit from your engine hours.

## Frequently Asked Questions

**What are stationary emissions in road freight?** They are emissions produced while the vehicle is not moving, principally refrigeration units holding temperature, hydraulic tail lifts, cab climate during breaks and engine idling at stops. They accumulate with time rather than distance, which is what makes them difficult to attribute using standard conversion factors.

**Do published emission factors already include idling?** Partly. Road freight factors derived from fleet miles per gallon contain average stationary burn, because real fuel consumption includes it. What they cannot do is reflect an individual operation’s time-per-kilometre profile, so the figure is misallocated rather than missing.

**How much fuel does a transport refrigeration unit use?** Zemo Partnership chamber testing at chilled and frozen set points with simulated door openings puts a diesel unit at an average of 1.8 litres an hour, 1.9 in summer and 1.7 in winter. At the published diesel conversion factor that is roughly 4.52 kg CO2e for every hour of operation.

**Why does the refrigeration uplift understate urban operations?** Because it is a percentage applied to a per-kilometre figure, so it assumes a fixed number of hours per kilometre. A stop-heavy urban round runs many hours across few kilometres. In this model it produced 1.70 times the refrigeration emissions the uplift attributed to it.

**What data is needed to measure stationary emissions properly?** Engine hours, refrigeration unit run time and stationary duration per stop, held against the plan version the route departed from. None of these exist in a route plan, which is why the measurement depends on real-time visibility and the executed record rather than on better modelling.

**Is this only a cold chain problem?** Refrigeration is the largest and most measurable component, and the only one the factor set adjusts for explicitly. Tail lifts, cab climate and idling behave the same way on any vehicle, so ambient operations with long dwell times carry a smaller version of the same error.

MEET THE AUTHOR

Anas T

Senior Content Writer - Product Marketing

Anas is a product marketer at Locus who enjoys turning complex logistics problems into simple, clear stories. Outside of work, he’s usually unwinding with a book or catching a good movie or series.

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## Real-Time Visibility in 2026: The Emissions Your Route Plan Cannot See

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