EventsThe 3rd International Online Conference on Agriculture
Published
This submission belongs to the session S1. Climate-Smart Agriculture: Practices, Determinants, Productivity, and Efficiency of the event The 3rd International Online Conference on Agriculture
Published date
20 Oct, 2025
Academic Editor
author-avatarSanzidur Rahman
Citation
Diana S.N.M. Nasir, Siti Khadijah Ali, Siti Nur Hannah Ismail, Nor Suzylah Sohaimi, Ben Richard Hughes, Computational Fluid Dynamics (CFD) Analysis for Indoor Paddy Farming: Evaluating Carbon Dioxide (CO2) Enrichment Effects on Growth Conditions via Controlled Air Capture, in Proceedings of The 3rd International Online Conference on Agriculture, 22 October–24 October 2025, MDPI: Basel, Switzerland
Share
Email
Facebook
Twitter
LinkedIn

Computational Fluid Dynamics (CFD) Analysis for Indoor Paddy Farming: Evaluating Carbon Dioxide (CO2) Enrichment Effects on Growth Conditions via Controlled Air Capture

Siti Khadijah Ali 2
Siti Nur Hannah Ismail 3
Nor Suzylah Sohaimi 4
1. School of Mechanical, Aerospace and Civil Engineering, Sir Frederick Mappin Building, The University of Sheffield, Mappin Street, Sheffield S1 4DT, UK
2. Department of Multimedia, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia, Malaysia
3. Department of Landscape Architecture, Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, 81310, Johor, Malaysia, Malaysia
4. Department of Planning and Property Development, Universiti Utara Malaysia, 06010, Sintok, Kedah, Malaysia, Malaysia
Abstract

Indoor paddy farming presents a promising solution to food security challenges, offering controlled environments for optimised crop growth. However, maximising yield efficiency requires a thorough understanding of microclimatic factors including carbon dioxide (CO₂). This study employs Computational Fluid Dynamics (CFD) to evaluate the effects of additional CO₂ supply on airflow dynamics, CO₂ distribution, and plant growth conditions in an indoor paddy farming setup. Two settings are examined, one with ambient CO₂ levels and the second with targeted CO₂ enrichment. The CFD model incorporates realistic paddy plant structures and simulates transpiration, energy exchange, and CO₂ absorption processes. By defining precise boundary conditions for temperature, humidity, and gas exchange on the leaf surfaces, the model enables detailed analysis of CO₂ transport inside the cultivation space (paddy beds) with the help of a small-scale controlled air capture device, inspired by direct air capture (DAC) technology. It is indeed promising that the CO₂ enrichment through controlled air capture enhances uniformity in gas distribution as well as optimising concentrations around the rice canopy, which can boost photosynthesis and biomass accumulation. Contrariwise, the second setting (without CO₂ enrichment) displays areas of restricte plant growth which reduces the overall yield. With the exploration of the effects of controlling ventilation on CO₂ retention and distribution, the findings suggest that an integrated CO₂ delivery system with optimised airflow patterns potentially mitigates stratified flow issues, and therefore it further maintains stable concentrations across the paddy beds as well as enhancing evapotranspiration processes, which creates a balanced microclimate for the plants. This research demonstrates the potential for exploring innovative indoor farming design strategies, particularly for maximising yield efficiency of staple agri-foods like rice using CFD analysis. Through CO₂ enrichment and airflow optimisation, the indoor farming technique potentially maximises its profitability through high yield production and simultaneously reduces resource consumption and uncertainties due to external climatic fluctuations.

Keywords
Indoor Farming
Computational Fluid Dynamics (CFD)
Indoor Carbon Concentration
Crop Simulation
Controlled Air Capture
Indoor Farming Ventilation
From traditions to transitions: empowering women in Lithuanian agriculture through living lab methodology
Time-Series Forecasting of Maize Production in Bangladesh: Integrating ARIMA Models with Diagnostic Validation