The Internet of Things (IoT) brings new opportunities for creating intelligent and streamlined supply chains that have better environmental and cost performance as compared to conventional ones. In... Show moreThe Internet of Things (IoT) brings new opportunities for creating intelligent and streamlined supply chains that have better environmental and cost performance as compared to conventional ones. In this paper, we quantify such improvements for a specific logistics chain case. To support the inventory of cost and emission data, we utilize system dynamics (SD) and agent-based modeling (AB) to define the structure of the two logistical systems, simulating and estimating differences in e.g., required storage levels, efficiency of transport, etc. In particular, we assess the difference in carbon emissions, cost, and market performance of a battery delivery chain in the delivery process between a two-tier IoT-supported supply chain (users are served by an IoT retailer directly connected to the producer) and a conventional three-tier supply chain (include an additional wholesaler to connect retailer and producer). The results demonstrate that IoT supply chains have significant advantages in minimizing average product storage and shipment fluctuations. IoT suppliers can estimate market demand to adjust production and transportation strategies for new orders. Consequently, the overall profitability of the IoT supply chain increases by more than 30%. Heating and lighting emissions in the storage process and direct emissions in transportation per functional unit (one unit of a Li-ion cell module) are reduced by 60%–70% under middle- and low-demand scenarios, and by at least 50% under high-demand scenario. However, the increasing use and higher loading rates of heavy trucks will weaken the advantages of IoT. Moreover, IoT products occupies a 10% lower market share compared to conventional ones under the same pricing strategy but achieves similar market share under the same value-added strategy. Show less
Van der Giesen, C.; Cucurachi, S.; Guinee, J.; Kramer, G.J.; Tukker, A. 2020
LCA is a well-known assessment tool that identifies and provides insights on the environmental impacts of products and services over their lifecycle. The guidance provided by the existing manuals... Show moreLCA is a well-known assessment tool that identifies and provides insights on the environmental impacts of products and services over their lifecycle. The guidance provided by the existing manuals typically applies to modelling and assessing environmental impacts ex-post, meaning that information is available from empirical experience after products have been commercially in use for extended periods of time. This information is not available if LCA is applied in an ex-ante manner before a technology is commercially deployed at scale. We identify the major challenges of applying LCA in an ex-ante manner and propose a route forward in dealing with these challenges that combines intuitions from other disciplinary fields. The first challenge is how to model consistent future foreground systems for the incumbent and new technology systems. Learning curves and scenario approaches are the way forward. The second challenge is how to model future background systems. Here a solution is to transform existing LCI databases towards future contexts, informed by the Integrated Assessment Models (IAMs) that provide scenarios in line with the Shared Socioeconomic Pathways (SSPs). Finally, uncertainty in exante LCA is of a different nature as in ex-post LCAs. The main difference with conventional LCA studies is the highly uncertain information for the future. To acknowledge this. considerate attention should be attributed to the discussion on these uncertainties, both in the design of the assessment and the data used. Responsive evaluation can play a supportive role here. This will increase the transparency and efficacy of the results because the relevant stakeholders and experts are involved. In this way technology designers and other stakeholders derive insights on the influence of design choices or contextual factors (that are important, but hard to influence) on the potential environmental impacts of their foreseen technology. (C) 2020 The Authors. Published by Elsevier Ltd. Show less
In the last three decades, the Life Cycle Assessment (LCA) framework has grown to establish itself as the leading tool for the assessment of the environmental impacts of product systems.LCA studies... Show moreIn the last three decades, the Life Cycle Assessment (LCA) framework has grown to establish itself as the leading tool for the assessment of the environmental impacts of product systems.LCA studies are now conducted globally both in and outside the academia and also used as a basis for policy making.Now that the science behind existing and established impact assessment models is more solid, LCA modellers may work on deepening and broadening LCA, and on tackling the issues that make the framework incomplete or uncertain.This work of thesis deals with the complete modelling of stressors that are not related to the standard extraction/emission pattern, thus that do not relate to the extraction of a certain quantity of matter or to the emission of matter to the environment.These stressors may be defined in this acceptation as matter-less.The thesis analyses the development of impact assessment models for the case of sound emissions determining noise impacts, radio-frequency electromagnetic emissions leading to electromagnetic pollution, and light emissions determining ecological light pollution.Through the study of these matter-less stressors the computational structure and other methodological topics of the LCA framework are put to the test. Show less
