Decision Support Systems Based on Gaseous Emissions and Their Impact on the Sustainability Assessment at the Livestock Farm Level: An Evaluation from the User’s Side

Evangelos Alexandropoulos (), Vasileios Anestis (), Federico Dragoni, Anja Hansen, Saoirse Cummins, Donal O’Brien, Barbara Amon and Thomas Bartzanas
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Evangelos Alexandropoulos: Department of Natural Resources Development and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
Vasileios Anestis: Department of Natural Resources Development and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
Federico Dragoni: Leibniz-Institute for Agricultural Engineering and Bioeconomy (ATB), 14469 Potsdam, Germany
Anja Hansen: Leibniz-Institute for Agricultural Engineering and Bioeconomy (ATB), 14469 Potsdam, Germany
Saoirse Cummins: Soils and Environment Research Centre, Irish Food and Agriculture Development Authority (TEAGASC), Johnstown Castle, Y35 TC97 Wexford, Ireland
Donal O’Brien: Soils and Environment Research Centre, Irish Food and Agriculture Development Authority (TEAGASC), Johnstown Castle, Y35 TC97 Wexford, Ireland
Barbara Amon: Leibniz-Institute for Agricultural Engineering and Bioeconomy (ATB), 14469 Potsdam, Germany
Thomas Bartzanas: Department of Natural Resources Development and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece

Sustainability, 2023, vol. 15, issue 17, 1-29

Abstract: To achieve national and global air quality and climate change objectives, the agricultural sector increasingly requires dependable decision support tools for gaseous emissions at the farm level. We evaluated thirteen greenhouse gas (GHG)-based decision support systems (DSS), considering criteria such as not only the accessibility, user-friendliness, stakeholder involvement, sustainability methodology, and modeling aspects, but also the input parameters and outputs provided, all crucial for decision making. While most DSSs provide information for facilitating their use, only four are suitable for inexperienced users, and stakeholder participation in DSS development is infrequent. The dominant methodology for farm-level GHG estimation is IPCC 2006, with quantitative models primarily used for indicators’ assessment. Scenario and contribution analyses are the prevailing decision support approaches. Soil, crop, and fertilizer types are the most implemented non-livestock-related inputs, while climate- and feed-related costs are the least required. All DSSs assess farm-level mitigation measures, but less than half offer sustainability consultation. These tools promote environmental sustainability by evaluating mitigation strategies, disseminating farm sustainability information, and guiding sustainable farm management. Yet, challenges such as disparate estimation methods, result variations, comparison difficulties, usability concerns, steep learning curves, the lack of automation, the necessity for multiple tools, the limited integration of the results, and changing regulations hinder their wider adoption.

Keywords: GHG-emissions-based decision support; software tools; multi-pillar sustainability assessment; livestock systems; farm-level assessment; users’ perspective (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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