One of the most controversial topics in energy analysis consists in the internalization of the effects of human labor in the embodied energy requirements of goods and services. In this paper, the Bioeconomic Input-Output model is proposed to address such issue: it consists in a partially closed Hybrid Input-Output model in which the production of human labor is internalized within the economy as a new productive sector. The human labor sector absorbs a portion of the national final demand, while it produces working hours in order to sustain the national economic activities. The Bioeconomic model causes a reallocation of the total energy embodied in the production of goods and services due to two overlapping effects: a change in the national production technology due to the definition of the human labor sector, and a reduction in the available final demand for the consumptions of the households. The Bioeconomic and the standard Input-Output models are comparatively applied for the analysis of (1) the energy embodied in goods and services produced by the Italian economy in 2010, and (2) the primary energy requirements of alternative dishwashing solutions in Italy. Specific embodied energy in Italian products increases by less than 5% for mining and energy industries, by 5–15% for manufacturing industries and by 15–70% for tertiary sectors. On the other hand, the energy embodied in total production from each sector may be lower or greater (from −20% to +50%) with respect to results of the standard Input-Output model. Moreover, it is found that the energy embodied in dishwashing by hand and by dishwasher in Italy increases respectively by 62% and by 35% if the Bioeconomic model is adopted. Based on these results, Authors argue that human labor should methodically be included alongside the supply chain of goods and services in both embodied energy analysis and life-cycle assessment.

Internalization of human labor in embodied energy analysis: Definition and application of a novel approach based on Environmentally extended Input-Output analysis

ROCCO, MATTEO VINCENZO;COLOMBO, EMANUELA
2016-01-01

Abstract

One of the most controversial topics in energy analysis consists in the internalization of the effects of human labor in the embodied energy requirements of goods and services. In this paper, the Bioeconomic Input-Output model is proposed to address such issue: it consists in a partially closed Hybrid Input-Output model in which the production of human labor is internalized within the economy as a new productive sector. The human labor sector absorbs a portion of the national final demand, while it produces working hours in order to sustain the national economic activities. The Bioeconomic model causes a reallocation of the total energy embodied in the production of goods and services due to two overlapping effects: a change in the national production technology due to the definition of the human labor sector, and a reduction in the available final demand for the consumptions of the households. The Bioeconomic and the standard Input-Output models are comparatively applied for the analysis of (1) the energy embodied in goods and services produced by the Italian economy in 2010, and (2) the primary energy requirements of alternative dishwashing solutions in Italy. Specific embodied energy in Italian products increases by less than 5% for mining and energy industries, by 5–15% for manufacturing industries and by 15–70% for tertiary sectors. On the other hand, the energy embodied in total production from each sector may be lower or greater (from −20% to +50%) with respect to results of the standard Input-Output model. Moreover, it is found that the energy embodied in dishwashing by hand and by dishwasher in Italy increases respectively by 62% and by 35% if the Bioeconomic model is adopted. Based on these results, Authors argue that human labor should methodically be included alongside the supply chain of goods and services in both embodied energy analysis and life-cycle assessment.
2016
Human labor, Embodied energy, Input-Output analysis, Life Cycle Assessment.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/995644
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