Utility of silicone filtering for diffusive model CO2 sensors in field experiments
Utility of silicone filtering for diffusive model CO2 sensors in field experiments
复制标题
有机硅过滤在扩散模型 CO2 传感器现场实验中的实用性
DOI：
10.3402/tellusb.v65i0.20143
复制
发表时间：
2013
期刊：
影响因子：
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通讯作者：
S. Ohkubo
中科院分区：
文献类型：
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作者：
S. Ohkubo
在土壤中安装扩散型CO2传感器是观测土壤中气体CO2浓度随时间变化的一种直接而有效的方法。此外，它不需要庞大的测量系统。疏水硅胶过滤器可防止水渗透。因此，即使在经历洪水（例如，积雪融化的农田，水位变化的湿地）时，其检测元件覆盖有硅树脂过滤器的传感器也可以在现场耐用。在实验室和现场实验中，研究了覆盖有硅胶过滤器的CO2传感器扩散模型的实用性。应用硅树脂过滤器延迟了对环境CO2浓度变化的响应，这是由于气体渗透性低于由诸如聚四氟乙烯的材料制成的其他常规使用的过滤器。从理论上讲，除了传感器本身的精度，土壤气体CO2浓度的日变化是可以计算的一系列数据与硅树脂覆盖的传感器，误差可以忽略不计。在10分钟测井间隔的大多数情况下，误差估计约为昼夜振幅的1%。发生的剧烈变化（如降雨事件）会导致计算值和真实的值之间出现较大的差距。然而，这一差距的比例急剧增加的程度是非常小的（0.43%，为10分钟的记录间隔）。为了准确估计，必须准备一个平滑变化的数据系列作为输入数据。当使用低分辨率的传感器或数据记录仪时，使用移动平均值或应用拟合曲线可能非常有用。气体渗透系数的估算是计算的关键。气体渗透系数可以通过室内实验来估算。本研究揭示了通过在淹水农田中安装硅橡胶覆盖的传感器的扩散模型来评估土壤气体CO2浓度的时间变化的可能性。
Installing a diffusive model CO2 sensor in the soil is a direct and useful method to observe the time variation of gas CO2 concentration in soil. Furthermore, it requires no bulky measurement system. A hydrophobic silicone filter prevents water infiltration. Therefore, a sensor whose detection element is covered with a silicone filter can be durable in the field even when experiencing inundation (e.g. farmland with snow melting, wetland with varying water level). The utility of a diffusive model of CO2 sensor covered with silicone filter was examined in laboratory and field experiments. Applying the silicone filter delays the response to change in ambient CO2 concentration, which results from lower gas permeability than those of other conventionally used filters made of materials, such as polytetrafluoroethylene. Theoretically, apart from the precision of the sensor itself, diurnal variation of soil gas CO2 concentration is calculable from obtained series of data with a silicone-covered sensor with negligible error. The error is estimated at approximately 1% of the diurnal amplitude in most cases of a 10-min logging interval. Drastic changes that occur, such as those of a rainfall event, cause a larger gap separating calculated and real values. However, the proportion of this gap to the extent of the drastic increase was extremely small (0.43% for a 10-min logging interval). For accurate estimation, a smoothly varied data series must be prepared as input data. Using a moving average or applying a fitting curve can be useful when using a sensor or data logger with low resolution. Estimating the gas permeability coefficient is crucial for calculation. The gas permeability coefficient can be estimated through laboratory experiments. This study revealed the possibility of evaluating the time variation of soil gas CO2 concentration by installing a diffusive model of silicone-covered sensor in an inundated field.
氨氧化古菌在酸性条件下的硝化作用
DOI：
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发表时间：
2012
期刊：
影响因子：
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作者：
田原和典;ら
通讯作者：
ら