Pérez-Vidal Andrea, Bermeo Varón Leonardo Antonio, Rodríguez-Jiménez Lina Mariana, Bolaños-Muñoz Sonia María, Lemos-Valencia Yordy Mario, Silva-Leal Jorge Antonio, Torres-Lozada Patricia
Faculty of Engineering, School of Natural Resources and Environmental Engineering, Universidad del Valle, 13th Street, 100-00, Cali 760032, Colombia.
Faculty of Engineering, School of Electrical and Electronics Engineering, Universidad del Valle, 13th Street, 100-00, Cali 760032, Colombia.
ACS Omega. 2025 Aug 12;10(33):36974-36984. doi: 10.1021/acsomega.4c11331. eCollection 2025 Aug 26.
The manual manometric (MM) method is widely used in batch anaerobic digestion tests, such as the biochemical methane potential (BMP) and the specific methanogenic activity (SMA), but it can cause inaccuracies due to biogas loss during measurements. This study presents an IoT-based biogas pressure measurement device developed with an Arduino microcontroller to improve accuracy and reliability in batch tests. The device supports four reactors and was tested in 250 mL glass vessels with varying headspace (20 and 50%) and substrate/inoculum ratios (0.5 and 0.2). Two tests were performed: one with glucose (11 days) and another with food waste (60 days). A third 30 h test compared the IoT device to the MM method under identical conditions. All tests used inoculum from a septic tank. The results showed that the MM method underestimates biogas production, with an average biogas loss of 50.7 ± 12.9 mbar per measurement. These losses increased at higher reactor pressures. Implementing IoT-based monitoring in BMP or SMA testing improves measurement accuracy, enables early failure detection, and facilitates efficient data management. In addition, the IoT device allows real-time observation of early biogas production dynamics, including acidogenic and methanogenic activity, as well as the detection of potential methanogenesis inhibition.
手动测压（MM）方法广泛应用于批量厌氧消化试验，如生化甲烷潜力（BMP）和特定产甲烷活性（SMA）试验，但由于测量过程中的沼气损失，该方法可能会导致测量不准确。本研究展示了一种基于物联网的沼气压力测量装置，该装置由Arduino微控制器开发而成，旨在提高批量试验中的测量准确性和可靠性。该装置支持四个反应器，并在250 mL玻璃容器中进行了测试，容器的顶空（20%和50%）和底物/接种物比例（0.5和0.2）各不相同。进行了两项试验：一项使用葡萄糖（11天），另一项使用食物垃圾（60天）。在相同条件下，进行了一项为期30小时的第三次试验，将物联网设备与MM方法进行了比较。所有试验均使用来自化粪池的接种物。结果表明，MM方法低估了沼气产量，每次测量的平均沼气损失为50.7±12.9毫巴。这些损失在较高的反应器压力下会增加。在BMP或SMA测试中实施基于物联网的监测可提高测量准确性，实现早期故障检测，并便于高效的数据管理。此外，物联网设备可实时观察早期沼气生产动态，包括产酸和产甲烷活性，以及检测潜在的甲烷生成抑制。
