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4TU.ResearchData
Dataset . 2023
License: CC BY NC SA
Data sources: 4TU.ResearchData
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
4TU.ResearchData
Dataset . 2023
License: CC BY NC SA
Data sources: 4TU.ResearchData
4TU.ResearchData | science.engineering.design
Dataset . 2023
License: CC BY NC SA
Data sources: Datacite
4TU.ResearchData | science.engineering.design
Dataset . 2023
License: CC BY NC SA
Data sources: Datacite
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Data underlying the publication: The embodied carbon emissions of lettuce production in vertical farming, greenhouse horticulture, and open-field farming in the Netherlands

Authors: Blom, Tess; Jenkins, Andrew; Pulselli, Riccardo; Van den Dobbelsteen, A.A.J.F. (Andy);

Data underlying the publication: The embodied carbon emissions of lettuce production in vertical farming, greenhouse horticulture, and open-field farming in the Netherlands

Abstract

This research evaluates the current carbon footprint of vertical farming systems by comparing the impact of one kilogram of butterhead lettuce produced in an operational vertical farm to that of conventional open-field farming (OF), soil-based greenhouse cultivation (GH(s)) and hydroponic greenhouse cultivation (GH(h)) in the Netherlands. A typical farm is defined for OF, GH(s) and GH(h) in the Netherlands, based on existing databases. It is not yet possible to define a typical vertical farm (VF) due to the breadth of approaches. Therefore, an operational vertical farm was used as a case study. Within the dataset the baseline activity data has been collected within the tabs ‘OF’, ‘GH(s)’, GH(h) and ‘VF’. The carbon footprint of each case study was calculated by accounting for all the GHG emissions from activities within the system boundaries, from cradle-to-grave, for the life cycle of both the crop and the farm. These GHG emissions were calculated as follows: CO₂-eq = activity data x EF, where CO2-eq is the carbon footprint of the activity in kg CO2-eq, and EF is the emission factor of the activity in kg CO₂-eq per unit of the activity data, assessed by referring to the IPCC GWP100a characterisation method in SimaPro 9.0.0, which is based on the Ecoinvent 3.6 database. Tab ‘EF’ provides an overview of the emissions factor sources used for activities within the study. Country-specific emission factors for the Netherlands were used for natural gas and electricity consumption to reflect the correct energy mix. By combining the collected activity data with the EFs, the carbon footprints of each farming system were calculated within the tabs ‘FIG04’ and ‘FIG05’. Three scenarios were created to improve the comparability of the baseline data as well as present potential carbon savings as a result of transitioning to renewable energy, which included: the lost carbon sequestration potential as a result of land-use change (FIG06), assuming identical sales packaging for all farming systems (FIG07, FIG08, FIG09), and a transition to renewable energy (FIG10). These scenarios, when considered collectively, greatly reduced the disparity between the carbon footprints of the three farming systems (FIG11 and FIG12). Electricity use represented the largest share in the carbon fooptrint of both baseline and alternative scenario, therefore, the electricity consumption of the VF was compared to that of other VF from literature in the tabs ‘FIG13’ and ‘FIG14’.

Keywords

carbon footprint, LCA, horticulture, Sustainable agriculture, vertical farming, Horticultural Production, open-field farming, renewable energy, Environmentally Sustainable Plant Production, life cycle assessment, FOS: Agriculture, forestry and fisheries, food production

  • BIP!
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    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.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
0
Average
Average
Average