Data quality and flux calculation of low-cost soil gas flux systems: insights from laboratory experiments and novel raw data processing schema

Monitoring soil gas fluxes, particularly greenhouse gases like CO2 and CH4, often relies on a portable chamber-based approach that integrates data from multiple sensors and an accumulation chamber. While increasing the spatiotemporal resolution of soil gas flux measurements for a given study site is critical to disentangling coupled hydro-bio-geochemical processes, budget constraints and complex data processing can pose significant challenges. Automated, low-cost soil gas flux systems offer promising alternatives, enabling scalability and site-specific customization. However, these continuous low-cost systems generate large volumes of data that require automated quality-check routines and adapted flux calculation schema.

Here, we present the developments of an open-source, low-cost CO2 soil gas flux system complemented by a laboratory advection-based soil gas flux experiment that allowed us to assess the performance of the sensor and chamber design. Furthermore, we propose a novel flux calculation schema that avoids arbitrary assumptions, such as a fixed measuring time for calculating the flux. Instead, our approach employs an expanding time window to estimate the soil gas flux and some metrics, such as the Akaike information criterion, to identify the optimal interval considered to calculate the soil gas flux and estimate uncertainties.

Considering that data quality can only be assured given an adequately designed chamber, our laboratory methodology addressed the low-cost sensor’s accuracy and the low-cost system’s capacity to accumulate and determine the rate of change of CO₂. Additionally, the proposed approach for calculating the soil gas flux provides users with a flexible and objective framework that adapts the total measurement time used for the calculations, enhancing the reliability of the soil gas flux estimates independently of the field conditions. This works highlights the potential of low-cost soil gas flux systems for enabling high spatiotemporal greenhouse gas monitoring capabilities while maintaining data quality standards.