By-product Aware Sales Share (ByPASS) Method for Constructing Physical Input-Output Tables from Mechanistic Models : A Case Study on Acetaminophen Manufacturing

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Abstract Input-Output models are generally constructed using Supply and Use tables following standard model assumptions of constant production or fixed product sales structure, which does not always hold at fine-scale sector resolution in the economy. Utilizing these generic transformation rules results in spurious interindustry linkages, as by-products from industries are treated identically to primary products, resulting in erroneous IO tables. Consequently, utilizing a fixed product sales structure (Model D) for bottom up Physical Input-Output Tables (PIOTs) introduces errors in economy-wide material flow analysis (EW-MFA) stemming from structural inaccuracies in the PIOT. To overcome this limitation, we propose a methodology that accounts for economic and engineering-driven decisions at industry scale to capture a realistic by-product sales structure. The proposed By-product Aware Sales Structure (ByPASS) method incorporates product pricing, logistics, and disposal cost, alongside physical parameters of product quality and post-handling losses, to allocate by-products between sales and waste streams, thereby quantifying the physically correct supply tables. We demonstrate ByPASS by constructing a PIOT for the U.S. Acetaminophen industry (2021) and provide a comparative analysis of MFA metrics derived from Model D versus ByPASS. Results show that Model D overestimates domestic extraction by 13 %, generates false commodity exchanges, and deflates waste by 0.35 %. This happens due to misallocation of by-products such as acetic acid and methane using Model D which gets corrected in ByPASS. The future extension of the ByPASS approach can be applied to distinct industrial network case studies, multi-regional frameworks, and optimization-based prescriptive PIOT development.
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By-product Aware Sales Share (ByPASS) Method for Constructing Physical Input-Output Tables from Mechanistic Models : A Case Study on Acetaminophen Manufacturing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article By-product Aware Sales Share (ByPASS) Method for Constructing Physical Input-Output Tables from Mechanistic Models : A Case Study on Acetaminophen Manufacturing Abhimanyu Shekhar, Shweta Singh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9123982/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Input-Output models are generally constructed using Supply and Use tables following standard model assumptions of constant production or fixed product sales structure, which does not always hold at fine-scale sector resolution in the economy. Utilizing these generic transformation rules results in spurious interindustry linkages, as by-products from industries are treated identically to primary products, resulting in erroneous IO tables. Consequently, utilizing a fixed product sales structure (Model D) for bottom up Physical Input-Output Tables (PIOTs) introduces errors in economy-wide material flow analysis (EW-MFA) stemming from structural inaccuracies in the PIOT. To overcome this limitation, we propose a methodology that accounts for economic and engineering-driven decisions at industry scale to capture a realistic by-product sales structure. The proposed By-product Aware Sales Structure (ByPASS) method incorporates product pricing, logistics, and disposal cost, alongside physical parameters of product quality and post-handling losses, to allocate by-products between sales and waste streams, thereby quantifying the physically correct supply tables. We demonstrate ByPASS by constructing a PIOT for the U.S. Acetaminophen industry (2021) and provide a comparative analysis of MFA metrics derived from Model D versus ByPASS. Results show that Model D overestimates domestic extraction by 13 %, generates false commodity exchanges, and deflates waste by 0.35 %. This happens due to misallocation of by-products such as acetic acid and methane using Model D which gets corrected in ByPASS. The future extension of the ByPASS approach can be applied to distinct industrial network case studies, multi-regional frameworks, and optimization-based prescriptive PIOT development. Physical Input-Output Table Economy-Wide Material Flow Analysis Pharmaceutical Manufacturing By-Products Full Text Additional Declarations No competing interests reported. Supplementary Files ESIByPASSforEWMFA.xlsx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 10 May, 2026 Reviews received at journal 05 May, 2026 Reviews received at journal 24 Apr, 2026 Reviewers agreed at journal 15 Apr, 2026 Reviewers agreed at journal 10 Apr, 2026 Reviewers agreed at journal 23 Mar, 2026 Reviewers invited by journal 23 Mar, 2026 Editor assigned by journal 16 Mar, 2026 Submission checks completed at journal 16 Mar, 2026 First submitted to journal 14 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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