Environmental Hotspots in Semiconductor-Based Diabetes Care: Green ICs and Circular Economy Approaches ^†

Abstract

Diabetes, projected to affect over 1.3 billion people by 2050, presents significant healthcare burdens and environmental challenges, necessitating innovative and sustainable solutions to manage complications effectively. This study applies life cycle assessment to evaluate the environmental impacts of two semiconductor-enabled diabetes care devices: (1) a single-use urine-based C-peptide measurement strip aligned with the reduce strategy and (2) a reusable smart wound dressing for chronic wound monitoring under the reuse strategy. Integrating green electricity reduced the total lifecycle global warming potential by 16.2% for the urine strip and 0.4% for the smart wound dressing. The results emphasize the importance of tailored design strategies, showing that the impact of green integrated circuits is substantial for single-use reduce systems, while long-term treatments benefit more from reuse strategies paired with durable, complex designs that extend component lifespan and limit new manufacturing burdens.

1. Introduction

Diabetes is a growing global health challenge, with 589 million people affected by this disease in 2024. This number is expected to rise to over 1.3 billion by 2050 due to aging populations, rising obesity, and sedentary lifestyles [1]. Without proper management, the disease leads to life-threatening complications such as cardiovascular issues, kidney failure, and amputations due to infected chronic wounds. Global diabetes care expenditures exceeded $1.015 trillion in 2024, accounting for nearly 12% of healthcare spending [1], underscoring the urgent need for innovative and sustainable treatment technologies. Advances in electronics-enabled healthcare tools, including continuous glucose monitors (CGMs), insulin pumps, and smart wound dressings, have revolutionized diabetes management, offering personalized glucose monitoring and long-term complication management [2,3]. Despite these benefits, these tools contribute to environmental challenges, including greenhouse gas (GHG) emissions from energy-intensive semiconductor manufacturing [4] and the waste generated by single-use electronic tools [5]. The global healthcare sector is already responsible for nearly 5% of global GHG emissions [1,6]. Addressing these challenges requires sustainable systems designed to balance functionality, hygiene standards, and reduced environmental impact [5]. The circular economy framework, incorporating strategies like reduce and reuse, guides sustainable design [7]. Reduce strategies prioritize lightweight, single-use components, while reuse strategies emphasize durable designs that extend the lifespan of critical components. Among the electronic components added to healthcare devices, integrated circuits (ICs) are significant environmental hotspots, with energy-intensive manufacturing processes in which electricity accounts for 80% of their total energy demand [4]. Transitioning to renewable electricity in semiconductor manufacturing represents a promising opportunity to mitigate GHG emissions. This study employs life cycle assessment (LCA) to evaluate the environmental performance of two semiconductor-enabled diabetes care devices under the 9-R circular economy framework [7]: (1) a single-use urine-based C-peptide measurement strip aligned with the reduce strategy and (2) a reusable smart wound dressing for diabetic foot ulcers designed with the reuse strategy. The analysis focuses on identifying environmental hotspots in IC manufacturing and explores the potential for green electricity utilization to mitigate impacts at both the system and total lifecycle levels.

2. Materials and Methods

2.1. Use Cases and Functional Requirements

This study evaluates two devices tailored to specific functional needs, representing the circular economy strategies of reduce and reuse.

2.1.1. Urine-Based C-Peptide Measurement Stripe

The urine C-peptide strip (henceforth “urine strip”) is a single-use diagnostic device to assess the metabolism of the patient [8]. It is particularly useful in diabetes classification, therapy assessment, gestational diabetes management, and postpartum diabetes monitoring. The device offers an accessible alternative to current practices, where urine tests are conducted and subsequently analyzed in laboratories. Designed for material efficiency and simplified disposal, the strip uses a flexible substrate printed with a three-electrode system. Powered wirelessly via a near field communication (NFC)-enabled IC without onboard batteries, it integrates a printed supercapacitor for stable energy delivery, ensuring reliable measurements. A schematic is shown in Figure 1a.

2.1.2. Smart Wound Dressing for Chronic Wound Care

Designed for continuous monitoring of chronic wounds to prevent severe infections, the smart wound dressing separates reusable electronics from disposable wound contact layers. This aligns with the reuse strategy while maintaining strict hygiene standards. Unlike current practices in wound care, which rely on manual checks of wound status by healthcare providers, this system aims for real-time, non-invasive monitoring of the wound. The disposable sensing layer combines a pH sensor and a temperature sensor on a flexible printed circuit board (PCB), plugged into a reusable readout unit. The reusable electronics include a sensing IC, a Bluetooth Low-Energy (BLE) IC for wireless communication, a rechargeable battery, and an analog front-end (AFE) for signal processing integrated on a standard PCB. Figure 1b depicts the architecture of the system.

2.2. Life Cycle Assessment

This study applies LCA according to ISO 14040 [9] and 14044 [10] standards, encompassing goal and scope definition, life cycle inventory (LCI), life cycle impact assessment (LCIA), and interpretation. The goal of this analysis is to evaluate the environmental impact of two semiconductor-enabled diabetes care devices, each designed to align with different circular economy strategies, and to identify key environmental hotspots within their system architectures. The aim is to support the development of sustainable design strategies to minimize lifecycle impacts, with a particular focus on the potential of integrating renewable electricity into semiconductor manufacturing.

The study employs the GaBi version 10.9.1.10 database [11] for the urine strip and the ecoinvent cut-off database v3.10 [12] for the smart wound dressing. Due to primary data gaps for BLE IC manufacturing, the study focuses on IPCC AR6 Global Warming Potential (GWP) [13], measured in kg CO₂-equivalent, as the primary impact category. Biogenic CO₂ emissions were excluded from the analysis. The functional unit (FU) defines the healthcare service provided. For the urine strip, the FU corresponds to a single C-peptide test, including activation and data transmission via a smartphone as well as disposal. For the smart wound dressing, the FU is six months of treatment, reflecting the median healing period for diabetic foot ulcers, a prominent chronic wound type [14]. The reusable readout unit was modeled for use throughout the treatment period, with disposable sensing layers replaced per dressing cycle. Related services, such as dressing changes, were also included in the analysis. End-of-life (EoL) treatment involved incineration for disposable components and electronics recycling for the reusable readout unit.

The LCI is based on laboratory-scale system architectures, as shown in Figure 1, with a detailed overview provided in

Table A1. LCI of the urine patch.

Component (FU)	Flow	Amount	Unit	Description of LCIA Data
printed layout (PET, Ag, dielectric)	own model	5.8	g	Sphera and Ecoinven, adapted
supercapacitor	based on primary data and the literature	1	pcs.	own model
capacitor	capacitor, ceramic	1	pcs.	Sphera dataset
resistor	resistor, flat chip	1	pcs.	Sphera dataset
sensing IC, 130 nm	own model: PCF-based	1	pcs.	PCF input from Infineon [16]
lateral flow device system	based on primary data	1	pcs.	own model
use phase–NFC charging	electricity	130	J	measured
EoL
collection and transportation	municipal waste collection service by a 21 metric ton lorry	0.00004	tkm	Ecoinvent dataset
incineration of MSW (incl. ash treatment)	municipal solid waste	0.0107	kg	Ecoinvent dataset

and

Table A2. LCI of the smart wound dressing.

Component (FU)	Flow	Amount	Unit	Description of LCIA Data
printed wiring board	PWB, surface mount	15.9	cm2	Ecoinvent dataset
resistor	resistor surface-mounted	33	pcs.	Ecoinvent dataset
capacitor	capacitor, surface-mounted	18	pcs.	Ecoinvent dataset
solder process incl. paste	mounting, surface mount technology, Pb-free	15.9	cm2	Ecoinvent dataset
LDO, battery management, switch voltage regulator	electronic component, active	3	pcs.	Ecoinvent dataset
ESD, attenuation, coil, push button, resettable fuse, jumper	electronic component passive	11	pcs.	Ecoinvent dataset
LED	light-emitting diode	3	pcs.	Ecoinvent dataset
rech. Li-ion battery 3.7 V, 205 mAh	battery, Li-ion, NMC111, rech.	5.4	g	Ecoinvent dataset
sensing IC, 130 nm	own model: PCF-based	1	pcs.	PCF input from Infineon [16]
sensing IC, VQFN Package 32	own model: PCF-based	25	mm2	PCF input from Infineon [16]
BLE, 55 nm	own model, literature-based	1	pcs.	Jones [17], 65–45 nm av.
BLE, QFN Package, 64 mm2	own model: PCF-based	64	mm2	scaled PCF input from Infineon
ZIF connector	cable ribbon, with plugs	1	g	Ecoinvent dataset
housing	PLA, 3D-printed	12.7	g	own model, the literature [15]
neodymium magnets	permanent magnet	1.6	g	Ecoinvent dataset
flex. sensor layout (PET, Ag ink)	measured, lab scale	30.5	cm2	primary data, Ecoinvent, adapted
dressing material, superabsorber	own model, BOM-based	5.8	g	own model
wound contact	own model, BOM-based	100	cm2	own model
gauze	own model, BOM-based	7	g	own model
use phase-per charging cycle	electricity	0.0005661	kWh	measured
use phase-transportation, V1	transportation, passenger car, EURO 5	2.5	km	Ecoinvent dataset
use phase-transportation, V2	transport, passenger car, electric	2.5	km	Ecoinvent dataset
EoL
used PCB	PCB recycling	15.9	cm2	Ecoinvent dataset
used Li-ion battery	used Li-ion battery	5.4	g	Ecoinvent dataset
used flex PCB	incineration, own model, BOM-based, (incl. ash treatment)	30.5	cm2	Ecoinvent, adapted
used dressing material	based on Ecoinvent ref. treatment textile soiled (incl. ash treatment)	89.3	g	Ecoinvent, adapted
collection and transportation	municipal waste collection service by a 21 metric ton lorry	0.002	tkm	Ecoinvent dataset

in Appendix A. Appendix A compiles the complete LCI (components, use phase, and end-of-life) and documents the data sources and assumptions, including selected literature-based parameters [15]. Primary data for the 130 nm CMOS sensing IC were obtained using a combination of top-down and bottom-up approaches to capture chemicals, energy demand, emissions, materials, waste, and transportation from frontend and backend manufacturing processes. This data was derived from Infineon’s Product Carbon Footprint (PCF) inventory. While this specific PCF data is proprietary and unavailable to the public, the underlying methodology is documented in [16]. For the 55 nm CMOS BLE IC, GWP was scaled using data from Jones [17]. To ensure comparability with the primary data from the sensing IC, the GWP of the 130 nm CMOS was also calculated using the same model, resulting in a deviation of 10% compared to the data used in this study. This deviation is considered reasonable for subsequent comparisons. To evaluate the potential impact of renewable electricity use, green IC scenarios incorporated Germany’s 2024 renewable electricity mix [18] into 130 nm CMOS IC manufacturing for GWP reduction evaluation. The same relative GWP reduction was applied to the BLE IC under a hypothetical scenario, enabling the estimation of environmental benefits in the absence of primary data for 55 nm CMOS manufacturing. Additionally, the use of electric vehicles for healthcare-related transportation was evaluated as a complementary strategy.

3. Results

The LCIA results identified IC manufacturing as one key contributor to GWP, with its impact significantly influenced by the electricity mix. Using renewable electricity reduced the GWP of IC manufacturing by 43%; see Figure 2a. In the reduce scenario (urine strip), the sensing IC dominates the system’s GWP footprint, resulting in a 16.5% system-level GWP reduction when green electricity is used for IC manufacturing. This reduction also remains through the full lifecycle, which is dominated by the system impact (Figure 2b,c). In contrast, the reuse scenario (smart wound dressing) showed that while ICs were significant contributors to GWP, the system’s extended lifespan necessitated a more complex design with additional electronic components, which further increased GWP. Among these, the AFE emerged as a particularly dominant contributor (Figure 2d). The laboratory-scale system architecture includes AFE components specifically added for testing and development purposes, which do not directly impact the device’s functionality in its final implementation. For a more realistic evaluation, an optimized design with a higher level of integration was used as a reference for analyzing the impact of green IC manufacturing. Under this optimized layout, system-level GWP reductions of 13.6% may be achieved when both ICs are fabricated using renewable electricity (Figure 2d). As shown in Figure 2e, the total lifecycle GWP of smart wound dressing is dominated by the use phase, driven by emissions from healthcare provider travel for dressing changes. Green IC manufacturing may yield only a 0.4% reduction, whereas modeling travel emissions using an electric vehicle achieved a 30.7% reduction.

4. Interpretation, Discussion, and Outlook

This study highlights the significant environmental burden of adding electronics to diabetes care devices, which substantially increases their cradle-to-gate GWP. The findings underscore the importance of tailored sustainability strategies, based on circular economy principles. For single-use devices like the urine strip, the reduce strategy effectively minimizes GWP through passive NFC-enabled energy harvesting and miniaturized component layouts. For reusable devices such as smart wound dressings, the reuse strategy—extending component lifespans—enables lifecycle impact reductions, despite requiring more complex and resource-intensive designs. Incorporating green ICs further mitigates GWP in both scenarios, with reductions of 16.5% for the urine strip and of 13.6% for the reusable wound dressing. However, total lifecycle GWP improvements for reusable devices are limited to 0.4% due to the dominance of the use phase, highlighting the need for further optimizations, such as the adoption of electric vehicles by healthcare providers—a practice already implemented in many home-healthcare services [19].

ICs were identified as critical GWP hotspots, heavily influenced by electricity use during manufacturing. The sensing IC, manufactured in Germany using a 100% renewable electricity mix, demonstrated a 43% GWP reduction compared to the standard electricity mix, as confirmed by primary data for the 130 nm CMOS process. However, due to the lack of primary data for the BLE IC, the green electricity share for its manufacturing remains uncertain. Future research should focus on the geographic origins of IC production, based on node type, and examine the availability of renewable electricity in those regions, which are particularly relevant for the energy-intensive advanced-node ICs [17,20].

While this study provides valuable insights into the GWP implications of ICs integrated into diabetes care devices, several limitations must be considered to contextualize the results and guide future research. For both designs, primary data from laboratory-scale production of flexible PCBs likely overestimates impacts compared to industrial-scale scenarios. Additionally, the lack of detailed primary data for the 55 nm BLE IC manufacturing restricts the analysis to GWP, rather than a more holistic evaluation incorporating material use and water consumption. Benchmarking of the smart wound dressing against state-of-the-art wound care systems has shown that improvements in personalized care can offset the environmental impacts of added electronics and significantly decrease use case-related environmental impacts [21]. However, further comparisons of urine strip testing with current laboratory-based test methods are required.

In conclusion, sustainably manufactured ICs play a key role in reducing GWP, especially for single-use devices. For long-term treatments, reuse strategies offer the greatest benefits by extending component lifespans and reducing new manufacturing needs, despite more complex layouts and higher cradle-to-gate impacts. These findings provide actionable insights for mitigating the environmental footprint of emerging healthcare technologies.