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

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 CO_2-eqis the carbon footprint of the activity in kg CO_2-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’.

本研究针对荷兰境内的垂直农场（Vertical Farm, VF）系统当前碳足迹展开评估，将一座运营中垂直农场生产1公斤奶油生菜（Butterhead Lettuce）的环境影响，与荷兰境内传统露地耕作（Open-Field Farming, OF）、土培温室耕作（Soil-based Greenhouse Cultivation, GH(s)）及水培温室耕作（Hydroponic Greenhouse Cultivation, GH(h)）的环境影响进行对比。研究团队基于现有数据库，为荷兰的露地耕作、土培温室耕作与水培温室耕作定义了典型农场范式；但由于垂直农场的生产模式覆盖范围广泛，暂无法统一定义典型垂直农场，因此选取一座实际运营的垂直农场作为案例研究。本数据集的基准活动数据已收录于“OF”“GH(s)”“GH(h)”及“VF”四个标签页中。各案例的碳足迹采用从摇篮到坟墓的系统边界内所有温室气体（Greenhouse Gas, GHG）排放进行核算，覆盖作物与农场的全生命周期。温室气体排放的计算方式为：CO₂当量（CO₂-eq）= 活动数据 × 排放因子（Emission Factor, EF），其中CO₂当量指该活动以千克CO₂-eq计的碳足迹，排放因子指单位活动数据对应的CO₂当量排放强度，计算参考了基于Ecoinvent 3.6数据库的SimaPro 9.0.0软件中IPCC GWP100a特征化方法。“EF”标签页汇总了本研究中各活动所用排放因子的来源。针对荷兰的天然气与电力消费，采用该国专属排放因子以准确反映当地能源结构。将收集的活动数据与排放因子结合后，各耕作系统的碳足迹已在“FIG04”与“FIG05”标签页中完成计算。为提升基准数据的可比性，并展示转向可再生能源可带来的潜在碳减排潜力，本研究设置了三类情景：一是考虑土地利用变化导致的碳固存损失（FIG06），二是假设所有耕作系统采用统一的销售包装（FIG07、FIG08、FIG09），三是向可再生能源转型（FIG10）。综合以上三类情景后，三类耕作系统间的碳足迹差异大幅缩小（FIG11与FIG12）。电力消耗在基准情景与备选情景的碳足迹中均占比最高，因此本研究在“FIG13”与“FIG14”标签页中将该垂直农场的电力消耗与文献报道的其他垂直农场进行了对比。