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Investigating the emissions effect of integrating drones into mixed-mode logistics – a case study of a healthcare setting

Investigating the emissions effect of integrating drones into mixed-mode logistics – a case study of a healthcare setting
Investigating the emissions effect of integrating drones into mixed-mode logistics – a case study of a healthcare setting

Interest is growing in the potential of using Uncrewed Aerial Vehicles (UAVs; known as drones) for logistics applications (i.e. last-mile payload delivery). Based on case studies of pathology specimens taken from patients at community clinics and transported to central laboratories for analysis, the effect on greenhouse gas emissions of using drones alongside more traditional transport modes (i.e. electric vans (e-vans) and bicycle couriers) in mixed-mode logistics systems was investigated for networks in locations with contrasting geographic characteristics. Results suggested that reductions in emissions of up to 83% were possible compared to e-van-only solutions. Notably, bicycle couriers made a considerable contribution to these reductions in some cases. In general, serving clinics that were remote and/or isolated tended to be where drones could offer a beneficial effect. Using drones was also associated with decreases in payload transit times (up to 76%) but increases in costs (up to 134%), raising a question regarding the true value of expedited delivery in a medical context.

Drone, emissions, healthcare, logistics, mixed-mode
1556-8318
1200-1219
Grote, Matt
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Oakey, Andy
dfd6e317-1e6d-429c-a3e0-bc80e92787d1
Pilko, Aliaksei
862c6e08-d848-49f9-ae61-d222751d6422
Krol, Jakub
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Blakesley, Alexander
e0d82136-9157-4e6d-a134-599449767116
Cherrett, Tom
e5929951-e97c-4720-96a8-3e586f2d5f95
Scanlan, James
7ad738f2-d732-423f-a322-31fa4695529d
Anvari, Bani
77a23168-fb8f-471d-89dc-b6ed20d65c78
Martinez-Sykora, Toni
2f9989e1-7860-4163-996c-b1e6f21d5bed
Grote, Matt
f29566f9-42a7-498a-9671-8661a4287754
Oakey, Andy
dfd6e317-1e6d-429c-a3e0-bc80e92787d1
Pilko, Aliaksei
862c6e08-d848-49f9-ae61-d222751d6422
Krol, Jakub
d034772d-681e-4119-8068-ba6250d56ced
Blakesley, Alexander
e0d82136-9157-4e6d-a134-599449767116
Cherrett, Tom
e5929951-e97c-4720-96a8-3e586f2d5f95
Scanlan, James
7ad738f2-d732-423f-a322-31fa4695529d
Anvari, Bani
77a23168-fb8f-471d-89dc-b6ed20d65c78
Martinez-Sykora, Toni
2f9989e1-7860-4163-996c-b1e6f21d5bed

Grote, Matt, Oakey, Andy, Pilko, Aliaksei, Krol, Jakub, Blakesley, Alexander, Cherrett, Tom, Scanlan, James, Anvari, Bani and Martinez-Sykora, Toni (2025) Investigating the emissions effect of integrating drones into mixed-mode logistics – a case study of a healthcare setting. International Journal of Sustainable Transportation, 19 (12), 1200-1219. (doi:10.1080/15568318.2025.2564851).

Record type: Article

Abstract

Interest is growing in the potential of using Uncrewed Aerial Vehicles (UAVs; known as drones) for logistics applications (i.e. last-mile payload delivery). Based on case studies of pathology specimens taken from patients at community clinics and transported to central laboratories for analysis, the effect on greenhouse gas emissions of using drones alongside more traditional transport modes (i.e. electric vans (e-vans) and bicycle couriers) in mixed-mode logistics systems was investigated for networks in locations with contrasting geographic characteristics. Results suggested that reductions in emissions of up to 83% were possible compared to e-van-only solutions. Notably, bicycle couriers made a considerable contribution to these reductions in some cases. In general, serving clinics that were remote and/or isolated tended to be where drones could offer a beneficial effect. Using drones was also associated with decreases in payload transit times (up to 76%) but increases in costs (up to 134%), raising a question regarding the true value of expedited delivery in a medical context.

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Accepted/In Press date: 22 August 2025
e-pub ahead of print date: 29 September 2025
Published date: 29 September 2025
Additional Information: Publisher Copyright: © 2025 The Author(s). Published with license by Taylor & Francis Group, LLC.
Keywords: Drone, emissions, healthcare, logistics, mixed-mode

Identifiers

Local EPrints ID: 506031
URI: http://eprints.soton.ac.uk/id/eprint/506031
ISSN: 1556-8318
PURE UUID: 44ee2966-e2d9-45d9-98a7-472fcaf5c44c
ORCID for Matt Grote: ORCID iD orcid.org/0000-0001-5590-7150
ORCID for Andy Oakey: ORCID iD orcid.org/0000-0003-1796-5485
ORCID for Aliaksei Pilko: ORCID iD orcid.org/0000-0003-0023-0300
ORCID for Tom Cherrett: ORCID iD orcid.org/0000-0003-0394-5459
ORCID for Toni Martinez-Sykora: ORCID iD orcid.org/0000-0002-2435-3113

Catalogue record

Date deposited: 27 Oct 2025 18:11
Last modified: 03 Dec 2025 03:01

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Contributors

Author: Matt Grote ORCID iD
Author: Andy Oakey ORCID iD
Author: Aliaksei Pilko ORCID iD
Author: Jakub Krol
Author: Alexander Blakesley
Author: Tom Cherrett ORCID iD
Author: James Scanlan
Author: Bani Anvari

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