Abstract

The objective of this study is to analyze the potential for Unmanned Aerial Vehicles (UAVs) to displace current technology and look at how they impact the environment through a delivery transportation model. It is meant to encompass an ecological perspective of producing and using UAVs as well as understand the environmental consequences that accompany it. This paper presents a new way of looking at the uses of UAVs and attempts to apply typical life cycle assessment (LCA) methods to this technology. This research is intended to be used as an initial environmental baseline of drone technology and as a comparative tool for commercial UAV operations in the United States. This study may also provide some insight into government policy rulings and system environmental reporting for this new industry.

Datasets used in this study are available in the ecoinvent library and address small freight lorries compared to simplified UAV technology. Other data sources are used to support model assumptions and fill in information gaps to assure data transparency. This compares energy consumption, material intensity, and emissions generated across three delivery scenarios.

It was found that the energy used to power drones, not the batteries themselves, has the most impact on the environment. Comparatively, trucks have a far reduced impact with the exception of urban land occupation and natural land transformation due to their operation on the road, as opposed to sky. The energy grid mix contributes heavily to what environmental impacts are significant. Depending on the priorities of a company they may consider location as a large factor for drone use and testing.

Although this study is able to complete some knowledge gaps on the life cycle of Unmanned Aerial Vehicles there are points where typical LCA structure is not optimal for this model. The capabilities of a drone are not directly comparable to other technology. This presents challenges when trying to assess the consequences of displacing additional technology.

Publication Date

7-27-2017

Document Type

Thesis

Student Type

Graduate

Degree Name

Systems Engineering (ME)

Department, Program, or Center

Industrial and Systems Engineering (KGCOE)

Advisor

Brian Thorn

Advisor/Committee Member

Scott Grasman

Advisor/Committee Member

Callie Babbitt

Campus

RIT – Main Campus

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