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International Journal of Environmental Research and Public Health
Article . 2020 . Peer-reviewed
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A Methodological Integrated Approach to Analyse Climate Change Effects in Agri-Food Sector: The TIMES Water-Energy-Food Module

Authors: C. Cosmi; Mauro Viccaro; Monica Salvia; Senatro Di Leo; Severino Romano; Maria Maddalena Tortorella; Maria Maddalena Tortorella; +3 Authors

A Methodological Integrated Approach to Analyse Climate Change Effects in Agri-Food Sector: The TIMES Water-Energy-Food Module

Abstract

The European Union’s 2030 climate and energy policy and the 2030 Agenda for Sustainable Development underline the commitment to mitigate climate change and reduce its impacts by supporting sustainable use of resources. This commitment has become stricter in light of the ambitious climate neutrality target set by the European Green Deal for 2050. Water, Energy and Food are the key variables of the “Nexus Thinking” which face the sustainability challenge with a multi-sectoral approach. The aim of the paper is to show the methodological path toward the implementation of an integrated modeling platform based on the Nexus approach and consolidated energy system analysis methods to represent the agri-food system in a circular economy perspective (from the use of water, energy, biomass, and land to food production). The final aim is to support decision-making connected to climate change mitigation. The IEA-The Integrated MARKAL-EFOM System (TIMES) model generator was used to build up the Basilicata Water, Energy and Food model (TIMES-WEF model), which allows users a comprehensive evaluation of the impacts of climate change on the Basilicata agri-food system in terms of land use, yields and water availability and a critical comparison of these indicators in different scenarios. The paper focuses on the construction of the model’s Reference Energy and Material System of the TIMES model, which integrates water and agricultural commodities into the energy framework, and on the results obtained through the calibration of the model β version to statistical data on agricultural activities.

Countries
Portugal, Italy
Keywords

690, 330, Health, Toxicology and Mutagenesis, Climate Change, 333, Scenario analysis, Article, climate change mitigation, Climate change mitigation, agri-food system, SDG 3 - Good Health and Well-being, Water Supply, SDG 13 - Climate Action, Food Industry, SDG 7 - Affordable and Clean Energy, Basilicata region, SDG 2 - Zero Hunger, SDG 15 - Life on Land, IEA-TIMES model, Models, Statistical, Public Health, Environmental and Occupational Health, land use, Water, SDG 8 - Decent Work and Economic Growth, Agriculture, scenario analysis, Food, Agri-food system, Land use, SDG 12 - Responsible Consumption and Production, Nexus Thinking

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    41
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
41
Top 1%
Top 10%
Top 1%
Green
gold