Richard C Lupton
Biographic Data
| ID | 8952533 |
|---|---|
| NAME | Richard C Lupton |
| GIVEN NAMES | Richard C |
| FAMILY NAME | Lupton |
| SIGNATURE | LUPTON R C |
| AFFILIATIONS | Department of Mechanical Engineering, Centre for Sustainable and Circular Technologies (CSCT) University of Bath Bath UK |
| ORCID | 0000-0001-8622-3085 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Robust modeling of material flows to end‐uses under uncertainty
In this study we quantify wood flows from raw materials to end‐uses for the United Kingdom in a robust way using a new material flow analysis (MFA) model with uncertainty. This is important to identify opportunities for efficiency given constraints on wood supply. We have developed a new “ProbPACTOT” MFA model which introduces a systematic method to handle mixed units during reconciliation and uncertainty in data observations, conversion factors,…
Calculating the chemical exergy of materials
Modern society requires large amounts of materials which lead to emissions of greenhouse gases. Effective climate policy should focus on not just energy efficiency but material efficiency as well. Exergy analysis is a powerful metric used to identify opportunities for efficiency improvement in industrial resource flow systems. Exergy offers a single unified measure of energy and material resources and indicates the real thermodynamic value of the…
Incremental Material Flow Analysis with Bayesian Inference
Material flow analysis (MFA) is widely used to study the life cycles of materials from production, through use, to reuse, recycling, or disposal, in order to identify environmental impacts and opportunities to address them. However, development of this type of analysis is often constrained by limited data, which may be uncertain, contradictory, missing, or over‐aggregated. This article proposes a Bayesian approach, in which uncertain knowledge ab…
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Incremental Material Flow Analysis with Bayesian Inference
Material flow analysis (MFA) is widely used to study the life cycles of materials from production, through use, to reuse, recycling, or disposal, in order to identify environmental impacts and opportunities to address them. However, development of this type of analysis is often constrained by limited data, which may be uncertain, contradictory, missing, or over‐aggregated. This article proposes a Bayesian approach, in which uncertain knowledge ab…
Calculating the chemical exergy of materials
Modern society requires large amounts of materials which lead to emissions of greenhouse gases. Effective climate policy should focus on not just energy efficiency but material efficiency as well. Exergy analysis is a powerful metric used to identify opportunities for efficiency improvement in industrial resource flow systems. Exergy offers a single unified measure of energy and material resources and indicates the real thermodynamic value of the…
Robust modeling of material flows to end‐uses under uncertainty
In this study we quantify wood flows from raw materials to end‐uses for the United Kingdom in a robust way using a new material flow analysis (MFA) model with uncertainty. This is important to identify opportunities for efficiency given constraints on wood supply. We have developed a new “ProbPACTOT” MFA model which introduces a systematic method to handle mixed units during reconciliation and uncertainty in data observations, conversion factors,…
Computer Science (3 works) · Economics (3 works) · Engineering (3 works) · Industrial ecology (3 works) · Sustainability (3 works) · Business (2 works) · Ecology (2 works) · Environmental economics (2 works) · Environmental Impact and Sustainability (2 works) · Environmental Science (2 works)