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Xiaoyu Ren^1,2, Kai Wu^1,2, Dongxu Yang^1,2

¹Carbon Neutrality Research Center (CNRC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.

Sensors (Basel, Switzerland)

|October 16, 2025

概括

一种新的多变量线性回归方法显著提高了低成本非分散红外 (NDIR) CO2传感器的准确性. 这种结合温度,压力和湿度的校准方法大大降低了偏差和根平均平方误差 (RMSE),以实现可靠的碳监测.

科学领域:

环境科学环境科学
大气化学大气化学
传感器技术传感器技术

背景情况:

低成本的非分散性红外 (NDIR) CO2传感器对于广泛的碳监测网络至关重要.
现有的NDIR传感器通常由于环境因素而遭受重大偏差和不准确.
准确的二氧化碳测量对于了解气候变化和大气过程至关重要.

研究的目的:

开发和评估NDIR CO2传感器的多变量线性回归校准方法.
用实验室和现场观测数据评估校准方法的有效性.
为了确定可靠的传感器性能,最优的参考数据和校准周期的数量.

主要方法:

多变量线性回归校准,包括温度,压力和相对湿度.
使用来自受控实验室环境的数据进行测试和验证.
评估与兴隆大气背景观测站的长期观测数据进行了评估,与高精度腔环下光谱仪 (Picarro) 相比较.

主要成果:

在实验室环境中,多变量回归校准将平均绝对偏差从5.218 ppm降至0.003 ppm.
在实验室校准后,根平均平方误差 (RMSE) 在2.1ppm以内.
现场观测显示RMSE从8.315 ppm减少到2.154 ppm,偏差从39.170 ppm减少到0.018 ppm.
校准数据成功捕获了白天CO2变化.
大约10天的共同位置的参考数据证明足以进行可靠的测量.
使用冬季或夏季数据进行校准产生了更好的结果,这表明了优化校准策略.

结论:

多变量线性回归是一种高效的校准方法,用于低成本的NDIR CO2传感器.
校准的传感器提供准确可靠的二氧化碳分子分数数据,适用于大气监测.
优化校准策略,包括数据持续时间和季节性选择,可以提高传感器性能和网络可靠性.

关键词:

测量二氧化碳分子分数的测量校准校准的时间长期现场观测长期现场观测低成本的传感器

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