In greenhouse cultivation, microclimate control is a highly energy-consuming process, and CO2 enrichment, which is a part of it, requires the direct consumption of fossil fuel energy. To achieve sustainable and economical greenhouse management, we must understand the performance and energy utilisation efficiency of CO2 enrichment in greenhouses. In this study, we conducted computational fluid dynamics (CFD) simulations for two CO2 enrichment methods in a strawberry greenhouse: (1) conventional overall greenhouse enrichment (‘Entire Enrichment’) and (2) crop-localised enrichment (‘Local Enrichment’). The spatial distribution of microclimate parameters was simulated using a CFD model; based on the results, the spatial distribution of the crop photosynthetic rate was also simulated using an environment–plant coupled model group. Furthermore, we quantitatively analysed the efficiency of CO2 enrichment (ECE) by calculating the changes in the photosynthetic carbon assimilation capacity of the crop canopy in relation to CO2 usage, which allowed us to propose a more efficient enrichment strategy. Compared with the Entire Enrichment method, the Local Enrichment method reduced the effects on greenhouse temperature and humidity but increased the average CO2 concentration inside the canopy by 264 μmol mol−1. As a result, Local Enrichment increased the average leaf photosynthetic rate inside the canopy by 1.48 μmol m−2 s−1. According to ECE analysis, Local Enrichment has huge advantages over Entire Enrichment; the mean ECE of Local Enrichment was approximately 4.4 times higher than that of Entire Enrichment (25.7 and 5.9 mmol mol−1, respectively). Moreover, scenario analysis indicated that the Local Enrichment system could be applied to larger greenhouses and improves ECE relative to that in a conventional system. Having compared the two enrichment methods comprehensively, we conclude that the Local Enrichment method could significantly improve the environmental parameters around the crop canopy in relation to photosynthesis and greatly enhance CO2 utilisation efficiency.
All Science Journal Classification (ASJC) codes
- Environmental Science(all)
- Industrial and Manufacturing Engineering
- Renewable Energy, Sustainability and the Environment
- Strategy and Management