A large aggregated pile of onions at a produce market
Solar Cool Chain · Concept Multi-crop cold-chain validation

Test the servicebefore choosingcapacity

Measure produce arrivals, waiting times and buyer requirements before deciding whether cooling is needed.

Before capacity

Start with what arrives

Produce arrives unevenly and waits for handling, transport and buyers. Cooling only makes sense where enough of that flow would use it.

Produce being weighed and aggregated in a wholesale market
Produce aggregation · wholesale handling before dispatch
Aug 2025100 farmer units reported launched
Jan 2026Further units entered procurement
Jun–Jul 2026Larger network ambitions announced

Public pipeline activity shows where to look. Operating status, reach and crop fit still determine usable supply.

Crop Intelligence · 2024–25

Crop patterns shape capacity

Potato is concentrated, vegetables are dispersed, and mango clusters differently again. A fixed cold-chain assumption can fit one crop window and miss another.

Bangladesh crop concentration plate A district atlas showing the five highest recorded production districts for potato, vegetables and mango in 2024–25. Potato · Rangpur · rank 1Potato · Dinajpur · rank 2Potato · Bogra · rank 3Potato · Joypurhat · rank 4Potato · Munshiganj · rank 5Vegetables · Chattogram · rank 1Vegetables · Rajshahi · rank 2Vegetables · Mymensingh · rank 3Vegetables · Jashore · rank 4Vegetables · Pabna · rank 5Mango · Chapainawabganj · rank 1Mango · Naogaon · rank 2Mango · Rajshahi · rank 3Mango · Kushtia · rank 4Mango · Natore · rank 5
Top-five recorded districts are marked for each crop. Marker position indicates district, not a proposed Solar Cool Chain site.
Potato Vegetables Mango
Potato2024–25 recorded production · 11.57m t
52.6%Top-5 district share

#1 district: Rangpur · 1.48m t.

Vegetables2024–25 recorded production · 6.28m t
23.4%Top-5 district share

#1 district: Chattogram · 379k t.

Mango2024–25 recorded production · 1.81m t
60.9%Top-5 district share

#1 district: Chapainawabganj · 412k t.

District production shows where to test. Actual loads determine capacity.

Capacity follows use

Size the service from use

Adjust the assumptions to see how much capacity would be used. One tonne-day means one tonne held for one day.

Modelled use

5.0 tof 10 t installed capacity occupied on an average day

At 55% occupancy and 90% uptime, modelled use reaches about half of a 10-tonne design.

Occupied tonne-days / month149
Unfilled tonne-days / month122
Indicative turns / month7.4
10 tonnes
55%
90%

Fixed assumption Average waiting time · 2 days

Capacity calendar

Loads arrive, wait and move out. Each column is a day, each row a tenth of design capacity.

  • Arrives
  • Waits · 2-day dwell
  • Moves out
  • Service down
  • Unfilled

Model illustration, not a forecast. Field measurements of arrivals and waiting time will replace it.

Demand, operator and final cost require field confirmation.

First commission

What the validation delivers

Four decision outputs before permanent equipment is specified.

  • Capacity-days mapArrival, dwell, peak demand and low-season use.
  • Alternatives appraisalHandling, local cooling, shared capacity or no permanent build.
  • Operator economicsTariff, uptime, repair response and service ownership.
  • First-site recommendationA documented Build, Resize, Defer or No build decision.
Field check

Validate the service in the field

  1. VolumeHow much produce actually arrives during the peak?
  2. TimeHow long does it wait, and when does cooling matter?
  3. UseWho would use the service, how often, and in the low season?
  4. OperationWho can run it reliably, and what would users pay?
  5. BuyerWhat condition, timing and route does the buyer require?
Booking → settlement clock One operating record across the service route
  1. BookNamed load + arrival window
  2. ReceiveWeight + condition recorded
  3. CoolTemperature + dwell
  4. ReleaseDispatch time + route
  5. AcceptRecord acceptance or rejection
  6. SettlePayment closes the record

The smallest justified response may be better handling, local cooling, shared capacity or no permanent build.

Build · Resize · Defer · No build

Produce moving through a market and buyer route
Buyer-route handling · market movement and handoff

Allocation

Sequence before spend

No permanent-asset budget is published before validation is complete. Colour identifies workstream, not spending share.

Flow + demand mappingNamed crop weeks, arrival, dwell and buyer windows
Scope first
Alternatives + service testsHandling, cooling and shared-capacity responses
Test
Operator economicsTariff, uptime, repair and service responsibility
Model
First-cluster decisionMandate the smallest viable intervention
Decide

No percentage split is published. Cost shares follow confirmation of the validation scope, sites and fieldwork.

Evidence notes

Public pipeline: 2025–26 launches, tenders and announcements indicate continued national activity. They do not prove operating status, utilisation or commercial sustainability; field mapping must verify each facility.

Sustainable-cooling hierarchy: World Bank guidance prioritises demand reduction, efficiency and system-level business models before expanding supply.

Cold-chain constraints: IFC links weak business models, financing, electricity and fragmented movement. Cooling-as-a-service remains one model to test, with mixed reported scaling outcomes.

Hardware comes last

Validate crops, routes and loads before any permanent asset is sized.