ORCID Profile
0000-0003-4405-2382
Current Organisations
ETH Zurich
,
Universiteit Leiden
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Publisher: American Chemical Society (ACS)
Date: 11-03-2016
Abstract: The recent acceleration of urbanization and industrialization of many parts of the developing world, most notably in Asia, has resulted in a fast-increasing demand for and accumulation of construction materials in society. Despite the importance of physical stocks in society, the empirical assessment of total material stock of buildings and infrastructure and reasons for its growth have been underexplored in the sustainability literature. We propose an innovative approach for explaining material stock dynamics in society and create a country typology for stock accumulation trajectories using the ARIMA (Autoregressive Integrated Moving Average) methodology, a stochastic approach commonly used in business studies and economics to inspect and forecast time series. This enables us to create scenarios for future demand and accumulation of building materials in society, including uncertainty estimates. We find that the so-far overlooked aspect of acceleration trends of material stock accumulation holds the key to explaining material stock growth, and that despite tremendous variability in country characteristics, stock accumulation is limited to only four archetypal growth patterns. The ability of nations to change their pattern will be a determining factor for global sustainability.
Publisher: IOP Publishing
Date: 16-04-2019
Publisher: Wiley
Date: 22-08-2017
DOI: 10.1111/JIEC.12471
Publisher: Wiley
Date: 26-07-2021
DOI: 10.1111/JIEC.13054
Publisher: Elsevier BV
Date: 11-2021
Publisher: Wiley
Date: 30-06-2017
DOI: 10.1111/JIEC.12626
Publisher: Elsevier BV
Date: 05-2015
Publisher: MDPI AG
Date: 25-01-2018
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 11-2022
Publisher: Wiley
Date: 10-04-2014
DOI: 10.1111/JIEC.12114
Publisher: Wiley
Date: 07-02-2019
DOI: 10.1111/JIEC.12730
Abstract: Modern society depends on the use of many erse materials. Effectively managing these materials is becoming increasingly important and complex, from the analysis of supply chains, to quantifying their environmental impacts, to understanding future resource availability. Material stocks and flows data enable such analyses, but currently exist mainly as discrete packages, with highly varied type, scope, and structure. These factors constitute a powerful barrier to holistic integration and thus universal analysis of existing and yet to be published material stocks and flows data. We present the Unified Materials Information System (UMIS) to overcome this barrier by enabling material stocks and flows data to be comprehensively integrated across space, time, materials, and data type independent of their disaggregation, without loss of information, and avoiding double counting. UMIS can therefore be applied to structure erse material stocks and flows data and their metadata across material systems analysis methods such as material flow analysis (MFA), input‐output analysis, and life cycle assessment. UMIS uniquely labels and visualizes processes and flows in UMIS diagrams therefore, material stocks and flows data visualized in UMIS diagrams can be in idually referenced in databases and computational models. Applications of UMIS to restructure existing material stocks and flows data represented by block flow diagrams, system dynamics diagrams, Sankey diagrams, matrices, and derived using the economy‐wide MFA classification system are presented to exemplify use. UMIS advances the capabilities with which complex quantitative material systems analysis, archiving, and computation of material stocks and flows data can be performed.
Publisher: Proceedings of the National Academy of Sciences
Date: 06-02-2017
Abstract: A large part of all primary materials extracted globally accumulates in stocks of manufactured capital, including in buildings, infrastructure, machinery, and equipment. These in-use stocks of materials provide important services for society and the economy and drive long-term demand for materials and energy. Configuration and quantity of stocks determine future waste flows and recycling potential and are key to closing material loops and reducing waste and emissions in a circular economy. A better understanding of in-use material stocks and their dynamics is essential for sustainable development. We present a comprehensive estimate of global in-use material stocks and of related material flows, including a full assessment of uncertainties for the 20th century as we analyze changes in stock-flow relations.
Publisher: Wiley
Date: 20-07-2020
DOI: 10.1002/JBMR.4114
Publisher: Wiley
Date: 10-07-2019
DOI: 10.1111/JIEC.12773
Publisher: Springer Science and Business Media LLC
Date: 29-11-2019
DOI: 10.1007/S00198-019-05214-0
Abstract: Manual correction of automatically generated contours for high-resolution peripheral quantitative computed tomography can be time consuming and introduces precision error. However, bias related to the automated protocol is unknown. This study provides insight into error bias that is present when using uncorrected contours and inter-operator precision error based on operator training. High-resolution peripheral quantitative computed tomography workflow includes manually correcting contours generated by the manufacturer's automated protocol. There is interest in minimizing corrections to save time and reduce precision error however, bias related to the automated protocol is unknown. This study quantifies error bias when contours are uncorrected and identifies the impact of operator training on bias and precision error. Forty-five radii and tibiae scans across a representative range of bone density were analyzed using the automated and manually corrected contours of three operators, with training ranging from beginner to expert, and compared with a "ground truth" to estimate bias. Inter-operator precision was measured across operators. The tibia had greater error bias than the radius when contours were uncorrected, with compartmental bone mineral densities and cortical microarchitecture having greatest biases, which could have significant implications for interpretation of studies using this skeletal site. Bias and precision error were greatest when contours were corrected by the beginner operator however, when this operator was removed, bias was no longer present and inter-operator precision was between 0.01 and 3.74% for all parameters except cortical porosity. These findings establish the need for manual correction and provide guidance on operator training needed to maximize workflow efficiency.
Location: United States of America
No related grants have been discovered for Tomer Fishman.