An Innovative IoT-Based Automated Flux Chamber for Continuous Monitoring of CO2 and VOC Emissions from the Subsurface

Natural attenuation process occurring at hydrocarbon-impacted sites are driven by biogeochemical interactions between the subsurface, microbial communities, and environmental conditions. Beyond direct volatile organic compounds (VOCs) volatilization from the contamination source, aerobic biodegradation pathways lead to the consumption of hydrocarbons and the production of gaseous emission from the subsurface, including CO₂. Current monitoring campaigns for evaluating gas fluxes are generally conducted periodically, relying on either soil-gas sampling and subsequent laboratory analysis or the use of high-cost instrumentation for rapid and expedited concentration measurements. These methods, while providing representative results of average values over specific and narrow time intervals, do not allow for an accurate description of the temporal dynamics of VOC biodegradation and the consequent CO₂ emissions, which are known to exhibit significant fluctuations on both daily and seasonal scales. To overcome this limitation, there has been growing interest in recent years in developing low-cost systems that allow for continuous monitoring of gas emissions.

This work, conducted as part of a research project funded by INAIL (BRiC ID21-2022),  presents the development and application of a self-designed automated static flux chamber for real-time and continuous monitoring of biodegradation-related gas emissions from the subsurface. The system integrates low-cost Non-Dispersive Infrared (NDIR) sensors for CO₂ measurement, together with a Photoionization Detector sensor (PID) for VOC concentration measurements, and is additionally equipped with sensors for environmental parameters (i.e. temperature, relative humidity and atmospheric pressure). The chamber is equipped with two air pumps dedicated to periodic automatic air exchange, ensuring operational continuity and allowing the acquisition of one flux measurement every 20 minutes. The electronic hardware is managed by an ESP32 microcontroller and is completed with an SD card for raw data storage and with a LoRaWAN transmission module for real-time data visualization and management in remote IoT clouds. Furthermore, the system is externally powered by an AGM lead-acid battery, connected to a photovoltaic panel, enabling energy self-sufficiency during field deployments.

The system was calibrated with a commercial multi-gas analyzer through a series of laboratory tests, with results comparable to those of commercially available instruments. Furthermore, experimental tests were conducted using the developed flux chamber prototype to investigate the biodegradation dynamics of soils artificially contaminated with two different fuel types. Continuous monitoring over a two-month period enabled the observation of biodegradation-related processes and the associated emissions of VOCs and CO₂. Subsequently, the automated chamber was employed in a two-week monitoring campaign at a contaminated site, to evaluate its efficiency in real contamination scenarios.

The system developed in this work represents a promising step toward an economical and scalable solution for a deeper understanding of soil biodegradation processes and the resulting gas emissions at contaminated sites, accounting for correlations with environmental parameters as temperature, humidity and atmospheric pressure. Furthermore, the integration with IoT environments, together with full system automation and energy self-sufficiency, provides a significant contribution to the digitalization and automation of subsurface monitoring techniques.