基于CO2排放量检测的秸秆腐解动态监测系统研究

Development and Application of Monitoring System for CO2 Emission Dynamics during Straw Decomposition

摘要:

针对秸秆腐解产物复杂，导致在线监测困难的问题，提出以秸秆腐解CO2排放量作为反映秸秆腐解动态特性的指标。并针对市面CO2传感器成本高、体积大，在秸秆腐解监测中普及困难的问题，基于小型、低成本非色散红外（Non-dispersive infrared, NDIR）CO2传感器、环境传感器及Arduino板，设计了秸秆腐解动态监测系统，实现秸秆腐解过程环境参数、秸秆温度以及CO2浓度多位点的监测，并结合微生物群落数据，分析了秸秆腐解规律。以市面TR-76Ui CO2记录仪为基准，对每个低成本NDIR CO2传感器进行测试与校准，1829个数据点的线性回归模型决定系数R2为0.97~0.99，RMSE为14.56~56.36 μL/L，表明低成本NDIR CO2传感器具有良好的检测精度和稳定性。秸秆堆体内部CO2浓度具有周期性变化规律，变化趋势与温度的变化趋势一致，且振动幅度随秸秆干燥逐渐减弱，该现象反映了微生物活动的生物节律，揭示了秸秆堆体内部CO2变化能够反映秸秆腐解的行为特征。分析表明，秸秆腐解速率与温度和含水率呈正相关，决定系数R2分别为0.813 7与0.892。调节秸秆含水率大于40%后，秸秆腐解速率迅速下降，至第4天趋于平稳。添加微生物菌剂后秸秆腐解速率在第7天开始明显下降，至第12天开始趋于平稳。监测周期内传感器未发生明显漂移，有较好的稳定性，检测精度可以满足秸秆腐解试验的分析需求，小型、低成本硬件对于秸秆腐解动态监测具有很好的推广应用潜力。

Abstract:

Monitoring decomposition process of crop straw is essential for both soil improvement and carbon sequestration, but it is challenging due to the complexity of straw decomposition products. To address this issue, CO2 emission was used as an indicator to reflect the dynamic characteristics of straw decomposition. In addition, considering the high cost of commercially available CO2 sensors, a monitoring system was designed and developed based on small, low-cost non-dispersive infrared (NDIR) CO2 sensors, environmental sensors, and Arduino. Using the commercial CO2 recorder TR-76Ui as a reference, each low-cost NDIR CO2 sensor was tested and calibrated. The linear regression model of 1 829 data points yielded coefficients of determination (R2) between 0.97 and 0.99, and RMSE between 14.56 μL/L and 56.36 μL/L, indicating good detection accuracy and stability of the low-cost NDIR CO2 sensors. The CO2 concentration inside the straw pile exhibited a periodic variation pattern, which was consistent with temperature variations, and the amplitude of vibration was gradually weakened as the straw dried. This phenomenon reflected the biological rhythm of microbial activity, revealing that the CO2 changes within the straw pile can indicate the decomposition behavior of the straw. The analysis showed that the rate of straw decomposition was positively correlated with temperature and moisture content, with R2 values of 0.8137 and 0.892, respectively. After adjusting the straw moisture content to over 40%, the decomposition rate rapidly declined and stabilized by the fourth day. When microbial inoculants were added, the decomposition rate was significantly decreased on the seventh day and stabilized by the twelfth day. Throughout the monitoring period, the sensors exhibited no significant drift and maintained good stability. The detection accuracy met the analytical needs of straw decomposition experiments, and the small, low-cost hardware showed great potential for widespread application in dynamic straw decomposition monitoring.