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Applying the Technology Choice Model in Consequential Life Cycle Assessment: A Case Study in the Peruvian Agricultural Sector
Author(s) -
LarreaGallegos Gustavo,
VázquezRowe Ian,
Wiener Hugo,
Kahhat Ramzy
Publication year - 2019
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/jiec.12812
Subject(s) - agriculture , dynamism , consumption (sociology) , production (economics) , agricultural productivity , natural resource economics , climate change , greenhouse gas , life cycle assessment , scenario analysis , economics , environmental economics , geography , microeconomics , social science , ecology , physics , archaeology , quantum mechanics , sociology , biology , finance
Summary Demand for grapes to produce pisco in southern‐coastal Peru is expected to double by 2030. However, the appellation of this beverage confines the production and limits the space for agricultural expansion, leading to a situation in which potential competition for resources with established constraints is foreseen. Hence, the objective of this study is to understand the environmental impacts, focused on climate change and water consumption, linked to the agricultural dynamism in the valleys of Ica and Pisco due to an increase in the demand of pisco . For this, the viticulture system was analyzed regarding predicted changes in terms of expansion, displacement or intensification using a consequential life cycle assessment (CLCA) approach, identifying the environmental consequences of these shifts. A two‐step CLCA model was used based on the results of a previous attributional study, in which marginal effects were estimated following the stochastic technology‐of‐choice model (STCM) operational framework. Results identified a potential for the increase of pisco production based on crop substitution in the valleys of Ica and Pisco and suggest that greenhouse gas emissions and water consumption will be reduced locally, but the displaced agricultural production would reverse this tendency. Regardless of the policy implications of the results in the analyzed system, the proposed methodology constitutes a robust methodology that can be applied to other highly constrained agricultural systems, namely, those regulated by geographic indications.