Development of a Low-Cost Real-Time Monitoring System for CO₂ and CH₄ Emissions from Agricultural Soil

Abstract

Agricultural soils are a major source of greenhouse gas (GHG) emissions, particularly carbon dioxide (CO₂) and methane (CH₄), highlighting the need for cost-effective and field-applicable monitoring solutions. This study developed and evaluated a low-cost real-time monitoring system for soil CO₂ and CH₄ emissions by integrating surface emission chambers, low-cost gas sensors, a solar-powered energy supply, and IoT-based wireless communication. Three acrylic chambers with different heights (40, 60, and 80 cm) were fabricated to investigate the influence of chamber geometry on measurement performance. System performance was assessed through simultaneous measurements against a Biogas 5000 analyzer under simulated conditions and during field deployment in a sugarcane cultivation area in Khon Kaen Province, Thailand. Relative agreement was used to compare the developed system with the reference instrument. The results showed that relative agreement varied with chamber height for both gases. Under simulated conditions, the 80 cm chamber achieved the highest overall relative agreement for CO₂ and CH₄, underscoring the importance of sufficient headspace volume in chamber-based measurements. Field experiments confirmed the system’s capability for continuous CO₂ monitoring in an agricultural environment. However, CH₄ emissions were not detected during the study period, likely due to drought-induced, well-aerated soil conditions. The developed system demonstrated stable autonomous operation, low energy consumption, and ease of installation, making it suitable for long-term field applications. Overall, the proposed platform provides a practical and scalable approach for real-time soil GHG monitoring and offers strong potential for integration into precision agriculture and climate-smart farming systems to support GHG mitigation strategies.

1. Introduction

Thailand is among the countries most vulnerable to the impacts of climate change, including floods, droughts, heightened rainfall, and landslides. Mitigating greenhouse gas (GHG) emissions is therefore a critical strategy for addressing the impacts of global warming-related disasters. In response to the escalating impacts, Thailand has committed to reducing its GHG emissions by 20–25% by 2030.

Reports from the Intergovernmental Panel on Climate Change (IPCC) indicate that greenhouse gases (GHGs) significantly increase the risks associated with global climate change [1]. The agricultural sector plays a critical role in this context, functioning both as a significant source of GHGs and as a potential mitigation pathway [1,2]. Consequently, the sector is uniquely positioned as both a contributor to and a solution for global environmental challenges. In addition, the Food and Agriculture Organization (FAO) highlights the potential of agricultural lands for carbon storage as a GHG mitigation strategy, although these systems remain a significant source of emissions [3]. In Thailand, the agricultural sector is one of the major contributors to national greenhouse gas emissions. According to Thailand’s First Biennial Transparency Report, agriculture accounts for approximately 18–20% of total greenhouse gas emissions, making it the second largest emitting sector after energy [2]. The principal greenhouse gases emitted from agricultural activities are carbon dioxide (CO₂) and methane (CH₄) [2,3]. CO₂ and CH₄ were selected in this study because they are key greenhouse gases associated with soil respiration and anaerobic biological processes, respectively. In addition, both gases can be monitored continuously using low-cost sensor technologies, supporting the objective of developing a practical real-time monitoring platform [4]. Globally, agriculture accounts for approximately 10–12% of total anthropogenic GHGs [4,5].

According to the IPCC Fifth Assessment Report (AR5), agricultural activities are a major source of non-CO₂ GHGs [3], particularly methane (CH₄) and nitrous oxide (N₂O). Agricultural emissions are largely associated with soil processes, biomass burning, rice cultivation, and manure management. Consequently, soil and vegetation carbon sequestration, together with improved agricultural management practices, are widely recognized as practical and effective options for mitigating GHGs from agricultural systems [4]. Numerous studies, both in Thailand and internationally, have investigated GHG emissions from agricultural systems. For example, Collier et al. [6] assessed spatial patterns of GHGs and sustainability indicators in sloping agricultural areas in Mae Chaem District, Chiang Mai Province. Similarly, Parkin et al. [7] measured greenhouse gas fluxes (CO₂ and N₂O) using stationary chamber techniques combined with gas chromatography, an approach suitable for field applications and large-scale greenhouse gas emission assessments [8].

Recent studies have increasingly focused on advanced measurement techniques and monitoring platforms for GHG emissions. For instance, Li Jun et al. [9] investigated spatial and temporal distributions of atmospheric CO₂, CH₄, and N₂O over rice fields in Hefei, China, using high-resolution heterodyne laser radiometers and optimal estimation algorithms. Similarly, Nusrat Jahan Mumu et al. [10] reviewed various GHG measurement methods and concluded that micrometeorological techniques are suitable for large-area monitoring, while chamber-based methods offer higher spatial and temporal resolution. In addition, Sakulrat Sutthiprapa et al. [11] evaluated the performance of a UAV-based biogas sensor against a Biogas 5000 analyzer and found comparable effectiveness at ground level. Furthermore, recent studies have demonstrated the feasibility of low-cost IoT-based systems, wireless sensor networks, and mobile monitoring platforms for real-time environmental and agricultural applications [12,13,14]. These approaches enable continuous data acquisition, autonomous field operation, and high-resolution spatial and temporal analysis.

Previous studies have shown that the design and dimensions of static emission chambers significantly influence the accuracy of GHG flux measurements, particularly chamber height, basal area, and volume, which affect gas accumulation dynamics and measurement bias [15]. However, despite extensive research on greenhouse gas measurement techniques and monitoring platforms, few studies have systematically evaluated the combined effects of chamber height and real-time sensor-based monitoring under field conditions. In particular, integrated approaches combining chamber-based soil greenhouse gas measurements with low-cost, real-time monitoring systems remain scarce, especially in sugarcane cultivation. Therefore, this study aims to develop and evaluate a surface emission chamber integrated with a real-time measurement system for monitoring CO₂ and CH₄ emissions from agricultural soils in a sugarcane plantation in Nong Ruea District, Khon Kaen Province, Thailand. The findings are expected to support greenhouse gas management and emission reduction strategies at both local and national levels.

2. Materials and Methods

2.1. System Design and Architecture

The system was designed as a low-cost, real-time monitoring platform for measuring soil CO₂ and CH₄ emissions using a surface emission chamber integrated with gas sensors, a data acquisition unit, and a solar-powered control system. The static chamber approach is widely used for quantifying soil greenhouse gas fluxes and is recognized as a reliable method for field-based measurements of CO₂ and CH₄ emissions [7]. Building on this principle, the proposed system integrates a surface emission chamber with embedded gas sensors and a real-time monitoring unit to enable continuous field measurements. The system architecture consists of four main subsystems: (i) the surface emission chamber unit, (ii) the gas sensing unit, (iii) the data acquisition and communication unit, and (iv) the power supply and control unit.

The surface emission chamber serves as the primary interface between the soil surface and the gas measurement system. The chamber is designed to accommodate the installation of CO₂ and CH₄ sensors, as well as exhaust fans to ensure controlled air circulation within the chamber. Sensor and exhaust fan placement was configured to allow uniform gas mixing and to minimize gas accumulation during measurement, consistent with established airflow and gas mixing principles in enclosed systems [7,16,17]. This configuration enables continuous, real-time monitoring of gas concentration changes within the chamber.

The gas sensing unit comprises dedicated CO₂ and CH₄ sensors installed inside the surface emission chamber. These sensors continuously detect gas concentration levels and transmit the measured signals to the data acquisition unit. The integration of both sensors within the same chamber allows simultaneous measurement of CO₂ and CH₄ emissions from the soil surface under identical environmental conditions.

The data acquisition and real-time monitoring subsystem is responsible for collecting sensor signals, processing the data, and transmitting the information wirelessly. An embedded microcontroller-based control board serves as the core of the system, managing sensor data collection and communication. The measured data are transmitted via a wireless communication module to enable real-time monitoring and remote access to emission data [18,19].

The power supply and control subsystem was designed to support autonomous field operation. A solar-powered energy system supplies electricity to all components, including sensors, control units, and communication devices. The system includes protective modules such as circuit breakers and battery protection units to ensure stable and reliable operation and prevent damage caused by overvoltage or low-battery conditions. All subsystems are integrated within a control cabinet to provide environmental protection and facilitate field deployment. The overall system configuration and component layout are illustrated in Figure 1.

2.2. Surface Emission Chamber Fabrication

Three sets of surface emission chambers were fabricated using transparent acrylic sheets with a square base area of 50 cm × 50 cm. Acrylic was selected for its mechanical rigidity, durability, and transparency, which facilitate field deployment and allow internal inspection during operation. The chambers were designed with three different heights (40, 60 and 80 cm) to evaluate the influence of chamber volume on gas accumulation and flux measurement performance. Chamber headspace volume is a critical factor in static closed-chamber measurements [14,18].

Previous studies have demonstrated that chamber geometry, headspace volume, and collar configuration can introduce measurement bias by altering gas diffusion gradients and microenvironmental conditions at the soil–atmosphere interface [15]. In particular, increasing chamber height and volume has been shown to reduce flux underestimation by decreasing the rate of gas accumulation within the chamber headspace [15]. Therefore, the use of multiple chamber heights in this study allows systematic evaluation of volume-related effects on soil CO₂ and CH₄ flux measurements.

Each surface emission chamber was equipped with dedicated CO₂ and CH₄ sensors installed within the chamber headspace to directly monitor temporal changes in gas concentrations above the soil surface. Exhaust fans were incorporated into the chamber structure to promote controlled air circulation and uniform gas mixing during the measurement period, thereby minimizing gas stratification and accumulation effects that may affect flux estimation accuracy [5,20].

The surface emission chambers were integrated with a real-time soil CO₂ and CH₄ monitoring system designed for autonomous field operation. The control unit was powered by a solar energy system to enable continuous operation in remote field conditions without reliance on grid electricity, as illustrated in Figure 2.

Energy storage was provided by a 12 V, 85 Ah battery, while power conditioning and distribution were managed using a solar charge controller (30 A), a 500 W inverter, and a switching power supply converting 240 V AC to 24 V DC. A microcontroller-based control board (Arduino ESP8266, NodeMCU) served as the central unit for sensor data acquisition, system control, and wireless communication. Wireless data transmission was enabled via a 4G portable hotspot and an LTE USB modem, allowing real-time data communication and remote access to soil gas emission data [21,22].

All electronic components were housed within a weather-resistant control cabinet to provide environmental protection and facilitate stable and reliable field deployment. Together, the fabricated surface emission chambers and the associated control system formed an integrated real-time platform for monitoring soil CO₂ and CH₄ emissions under field conditions.

2.3. Gas Sensors and Calibration

The gas sensing unit consisted of dedicated CO₂ and CH₄ sensors installed within the chamber headspace to continuously monitor changes in gas concentrations emitted from the soil surface. Sensor placement within the chamber was designed to allow direct detection of gas concentration variations under controlled internal conditions while minimizing external environmental interference. This configuration follows the fundamental principles of static closed-chamber measurements, in which gas fluxes are quantified based on temporal changes in gas concentrations within a confined headspace above the soil surface [23,24].

The CO₂ and CH₄ sensors were integrated with a microcontroller-based data acquisition system to enable real-time signal processing and data transmission. Sensor outputs were recorded continuously during the measurement period and transmitted to the monitoring system for data logging and subsequent analysis. The use of both gas sensors within the same chamber allowed simultaneous measurement of CO₂ and CH₄ emissions under identical environmental and operational conditions, thereby reducing variability associated with separate measurement systems.

Sensor calibration and performance verification were conducted by comparing real-time measurements from the developed monitoring system with those from a reference gas measurement instrument, Biogas 5000 analyzer (Geotech, Coventry, UK). Measurements were performed simultaneously using the surface emission chambers and the reference instrument to ensure consistent environmental conditions during calibration. This comparative approach is consistent with established validation practices for chamber-based GHG measurements, where sensor performance is evaluated against reference analyzers under field conditions [23,25,26].

The calibration procedure focused on evaluating the agreement between sensor readings and reference measurements across all chamber heights to assess sensor performance under varying chamber volume conditions. This approach enabled validation of the developed real-time soil CO₂ and CH₄ monitoring system under different gas accumulation environments and supported subsequent accuracy analysis.

The detailed technical specifications of the CO₂ and CH₄ gas sensors employed in this study are presented in

Table 1. Technical specifications of gas sensors used in the developed monitoring system.

Parameter	CO2 Sensor	CH4 Sensor
Sensor type	NDIR	Semiconductor (metal oxide)
Measurement range	0–5000 ppm	0–10,000 ppm
Resolution	1 ppm	1–10 ppm
Accuracy	±(50 ppm + 3% of reading)	±(2–5% of full scale)
Response time (T90)	<30 s	<30–60 s
Operating temperature	−10 to 50 °C	−10 to 50 °C
Operating humidity	0–95% RH (non-condensing)	0–95% RH
Output signal	UART/Analog/PWM	Analog/UART
Supply voltage	5 V DC	5 V DC
Power consumption	<100 mA	<150 mA
Dimensions	9 × 8.5 cm	9 × 8.5 cm

. These specifications, including measurement range, accuracy, response time, operating conditions, and electrical characteristics, provide essential information for assessing sensor performance and confirming their suitability for continuous real-time monitoring of soil greenhouse gas emissions under field conditions.

2.4. Data Acquisition and Real-Time Monitoring System

The data acquisition and real-time monitoring system was developed to continuously record soil CO₂ and CH₄ concentrations from the surface emission chambers and transmit the data for remote monitoring and analysis. The system was designed to operate autonomously under field conditions using a solar-powered energy supply and a wireless communication network.

The CO₂ and CH₄ sensors within each surface emission chamber were connected to a microcontroller-based data acquisition unit using an Arduino ESP8266 NodeMCU (Espressif Systems, Shanghai, China) board. The microcontroller was responsible for collecting sensor output signals, processing the measured gas concentration data, and controlling system operations. Exhaust fans within the chambers were operated to regulate internal air circulation and ensure stable gas sampling conditions during measurements.

Power for the data acquisition system was supplied by a solar energy unit consisting of a 120 W solar panel, a solar charge controller (30 A), a 12 V battery (85 Ah), and protection components including AC and DC circuit breakers, a low-cut module, and a battery protection module. These components ensured stable power delivery and protected the system from over-discharge and voltage fluctuations during continuous operation.

For data transmission, the system employed a wireless communication setup comprising a 4G portable hotspot, a USB LTE modem with a SIM card slot, and a Wi-Fi signal distributor. Measurements collected by the microcontroller were transmitted in real time via the wireless network, enabling remote monitoring and data logging. This configuration allowed continuous observation of soil CO₂ and CH₄ emissions without the need for on-site data retrieval.

The integrated data acquisition and real-time monitoring system enabled synchronized measurement of CO₂ and CH₄ concentrations across all chamber heights under identical environmental conditions. The recorded data were subsequently used for relative agreement evaluation and comparison with reference measurements obtained from the Biogas 5000 instrument.

2.5. Field Experimental Setup

Field experiments were conducted to evaluate the performance of the developed real-time soil CO₂ and CH₄ monitoring system under actual agricultural conditions. The experiments were carried out in a sugarcane cultivation area located at Khon Kaen 3, Phu Wiang District, Khon Kaen Province, Thailand. The selected site represents typical field conditions for soil gas emission measurements in agricultural systems.

Three sets of surface emission chambers, fabricated from acrylic sheets with a base area of 50 cm × 50 cm and different chamber heights, were deployed in the field. Each chamber was equipped with integrated CO₂ and CH₄ sensors and exhaust fans, and connected to the solar-powered data acquisition and real-time monitoring system. The chambers were installed directly on the soil surface to ensure airtight contact and minimize gas leakage during the measurement.

The real-time monitoring system, including the control cabinet and solar power unit, was installed adjacent to the surface emission chambers to support autonomous operation. All chambers operated simultaneously to enable synchronized measurements of soil CO₂ and CH₄ concentrations under identical environmental conditions. Measurements were continuously recorded and transmitted wirelessly for remote monitoring and subsequent analysis.

Figure 3 illustrates the field deployment of the surface emission chambers and the real-time monitoring system in the sugarcane cultivation area, including the chamber installation, the solar-powered control unit, and the overall experimental setup used for soil CO₂ and CH₄ emission measurements.

2.6. Relative Agreement and Validation Methods

The relative agreement of the developed real-time soil CO₂ and CH₄ monitoring system was evaluated by comparing sensor measurements with reference values obtained from the Biogas 5000. Measurements from both the developed system and the reference instrument were conducted simultaneously under identical field conditions to ensure consistency during validation and minimize the influence of environmental variability.

Relative agreement was defined as the degree of agreement between the measured values obtained from the developed system and the reference values from the Biogas 5000. The relative agreement of the measurements was calculated using Equation (1).

$$\mathrm{Relative}\mathrm{Agreement}(\%)=\left(1-{\displaystyle \frac{\left|X_m-X_t\right|}{X_t}}\right)\times 100$$

(1)

where X_m represents the measured value obtained from the developed system, and X_t represents the reference value measured by the Biogas 5000 analyzer. This formulation expresses the degree of agreement between measured and reference values and has been widely used for the performance evaluation of measurement systems [24]. Relative agreement was calculated for both CO₂ and CH₄ measurements at each chamber height. The resulting values were used to assess the reliability and measurement performance of the developed monitoring system under different chamber configurations.

2.7. Statistical Analysis

Statistical analysis was performed to evaluate the measurement performance of the developed real-time soil CO₂ and CH₄ monitoring system. Descriptive statistics, including the mean and standard deviation (SD), were used to summarize gas concentration measurements obtained from both the developed system and the reference instrument.

Relative agreement was calculated and expressed as a percentage (%) for each chamber height. These values were used to assess the agreement between the developed monitoring system and the reference measurements.

To further evaluate the relationship between the developed sensor system and the reference instrument (Biogas 5000), simple linear regression analysis was applied. The gas concentrations measured by the developed system were treated as the dependent variable (y), while the corresponding values obtained from the reference instrument were considered the independent variable (x). The regression model was expressed as:

y = ax + b

(2)

where a is the slope and b is the intercept.

The coefficient of determination (R²) was used to quantify the strength of the linear relationship between the two measurement methods.

In addition, error metrics including the root mean square error (RMSE) and mean absolute error (MAE) were calculated to quantify the deviation between the developed system and the reference measurements:

$$\mathrm{RMSE}=\sqrt{{\displaystyle \frac{1}{n}}{\displaystyle {\sum }_{i=1}^n}{\left(y_i-x_i\right)}^2}$$

(3)

$$\mathrm{MAE}={\displaystyle \frac{1}{n}}{\displaystyle {\sum }_{i=1}^n}\left|y_i-x_i\right|$$

(4)

where n is the number of paired observations, y_i represents the gas concentration measured by the developed system, and x_i represents the corresponding value measured by the reference instrument.

All statistical analyses were conducted using standard data processing and analysis software. The results were used to support the evaluation of system reliability and performance under both simulated and field conditions.

3. Results

3.1. Performance of the Real-Time Soil CO₂ and CH₄ Monitoring System

The developed real-time soil CO₂ and CH₄ monitoring system was successfully assembled as a fully integrated platform suitable for agricultural field applications. The system consisted of three surface emission chambers with different heights (40, 60, and 80 cm), coupled with a solar-powered data acquisition and wireless communication unit. The integrated design enabled simultaneous gas monitoring under multiple chamber configurations.

The monitoring system enabled continuous, real-time measurement of soil CO₂ and CH₄ concentrations using integrated gas sensors installed within each surface emission chamber. Sensor signals were processed by a microcontroller-based data acquisition unit and transmitted wirelessly, enabling remote monitoring without the need for on-site data retrieval. The solar-powered energy supply supported autonomous operation and ensured stable performance during extended measurement periods.

System stability was evaluated based on continuous operation, the reliability of the solar power supply, successful wireless data transmission, and the absence of hardware or communication failures. Field deployment was conducted over a one-month period (March–April 2023), during which the system operated continuously. Only routine preventive maintenance was required—such as inspecting battery status, electrical connections, and chamber cleanliness—with no corrective maintenance or component replacement necessary.

The surface emission chambers with varying heights were successfully deployed and operated simultaneously, enabling synchronized measurements under identical environmental conditions. The different configurations ensured consistent evaluation of the influence of chamber height on gas accumulation behavior and measurement performance.

Figure 4 presents the completed surface emission chambers and the real-time soil CO₂ and CH₄ monitoring system, including the control cabinet, power supply components, and integrated sensors. The system operated successfully, demonstrating readiness for accuracy evaluation under simulated conditions and field deployment in agricultural environments.

3.2. Relative Agreement of CO₂ and CH₄ Under Simulated Conditions

Relative agreement of the developed real-time soil CO₂ and CH₄ monitoring system was evaluated under simulated soil conditions using surface emission chambers with heights of 40, 60, and 80 cm. Relative agreement assessment was conducted by comparing the sensor measurements with reference values measured simultaneously using a Biogas 5000 analyzer. Relative agreement was calculated based on the agreement between sensor measurements and reference values, as described in Section 2.6.

The results demonstrated that the relative agreement for both CO₂ and CH₄ varied with chamber height. For CO₂ measurements, the average accuracies obtained at chamber heights of 40, 60, and 80 cm were 78.36%, 50.20%, and 83.15%, respectively. In contrast, the relative agreement of CH₄ increased with chamber height, yielding average relative agreement of 53.97% at 40 cm, 66.56% at 60 cm, and 77.82% at 80 cm, as shown in Figure 5.

Overall, the simulated experiments indicated that the developed system was capable of detecting and quantifying soil CO₂ and CH₄ emissions, with performance dependent on chamber height. The results also revealed distinct patterns between the two gases, with higher CH₄ relative agreement observed at increased chamber heights under simulated conditions.

3.3. Field Relative Agreement of CO₂ and CH₄ in a Sugarcane Cultivation Area

The developed real-time soil CO₂ and CH₄ monitoring system was evaluated under field conditions in a sugarcane cultivation area (Khon Kaen 3) located in Phu Wiang District, Khon Kaen Province. Field measurements were conducted over a one-month period from March to April 2023 using surface emission chambers with heights of 40, 60, and 80 cm. Relative agreement was assessed by comparing the sensor measurements obtained from the developed system with reference values measured simultaneously using a Biogas 5000 gas analyzer.

The field measurement results showed that CO₂ Relative agreement varied with chamber height. Average CO₂ relative agreement were 67.11% at a chamber height of 40 cm, 58.08% at 60 cm, and 73.89% at 80 cm, as illustrated in Figure 6. Among the tested configurations, the 80 cm chamber provided the highest CO₂ relative agreement under field conditions in the sugarcane cultivation area.

In contrast, CH₄ emissions were not detected during the field measurement period at any of the tested chamber heights, as shown in Figure 6. As a result, CH₄ relative agreement could not be evaluated under the field conditions of this study.

Overall, the field evaluation demonstrated that the developed system was capable of monitoring soil CO₂ emissions in an agricultural environment, with performance trends consistent with those observed under simulated conditions.

3.4. Linear Regression Analysis of CO₂ and CH₄ Measurements

To further evaluate the relationship between the developed sensor system and the reference instrument (Biogas 5000), linear regression analysis was conducted under simulated conditions, as commonly applied in environmental sensor validation studies.

Figure 7 shows the scatter plots and corresponding regression lines for CO₂ and CH₄ measurements. For CO₂, a moderate linear relationship was observed (R² = 0.780), indicating an acceptable level of agreement between the developed system and the reference instrument. However, a systematic offset was evident at low concentration levels, which is consistent with previous studies reporting baseline drift and sensitivity limitations in low-cost gas sensors.

For CH₄, a strong linear relationship was obtained (R² = 0.902), suggesting that the developed system is capable of capturing methane concentration trends. Nevertheless, the relatively high RMSE and MAE values indicate increased measurement deviation, particularly at higher concentration levels, which has also been reported in sensor-based methane monitoring systems under varying concentration ranges.

Linear regression analysis between the developed sensor system and the reference Biogas 5000 analyzer under simulated conditions: (a) CO₂ and (b) CH₄. The solid lines represent the linear regression fits, and R² indicates the strength of the relationship.

4. Discussion

4.1. Methodological Reliability

The methodological reliability of the developed real-time soil CO₂ and CH₄ monitoring system is strongly supported by its chamber-based measurement design and controlled deployment strategy. Static closed-chamber techniques remain among the most widely accepted methods for quantifying soil greenhouse gas fluxes due to their high spatial resolution and suitability for heterogeneous agricultural fields [26]. However, previous studies have shown that chamber geometry, headspace volume, and air circulation conditions can significantly influence gas accumulation dynamics and introduce measurement bias [18,26,27].

In this study, the use of three chamber heights enabled a systematic evaluation of volume-related effects on measurement performance. The observed variation in relative agreement across chamber heights is consistent with earlier findings that insufficient headspace volume may lead to rapid gas accumulation and nonlinear concentration increases, whereas larger volumes can stabilize concentration gradients and reduce flux underestimation [19,28]. In addition, the integration of exhaust fans to promote internal air mixing aligns with recommended practices for maximizing stratification effects and improving chamber representativeness [17]. Collectively, these design features enhance methodological robustness and ensure that the observed differences in relative agreement are primarily attributable to chamber configuration rather than experimental artifacts.

4.2. Relative Agreement and Calculation Validity

Reliable evaluation of greenhouse gas measurements from chamber-based systems depends critically on the correctness of the comparison procedure [26]. highlighted that common errors in closed-chamber studies arise from improper treatment of temperature, pressure, and headspace volume when converting concentration changes into flux values [26]. In the present study, relative agreement was defined as the agreement between sensor measurements and reference values obtained from a Biogas 5000 analyzer [24].

The calculation framework applied in this study is consistent with best practices for chamber-based gas flux measurements, where synchronized measurements under identical environmental conditions are essential to minimize bias [23,24,29]. By conducting simultaneous measurements with the reference instrument at each chamber height, uncertainties associated with temporal variability in soil respiration and atmospheric conditions were reduced. Therefore, the reported relative agreement values reflect system performance rather than computational artifacts, reinforcing the validity of the comparative evaluation approach.

4.3. Sensor Performance and Reliability

Although low-cost gas sensors are often criticized for limited precision and susceptibility to environmental interference, recent studies have demonstrated that, when carefully calibrated and validated, they can provide reliable measurements for environmental monitoring applications [30,31]. The relative agreement levels achieved in this study, particularly for CO₂, are comparable to those reported for other low-cost sensor-based greenhouse gas monitoring platforms in agricultural and environmental contexts [32].

The observed dependence of CH₄ relative agreement on chamber height further highlights the interaction between sensor performance and chamber design, rather than inherent sensor limitations. Larger chamber volumes likely enhanced CH₄ detectability by allowing greater gas accumulation above sensor detection thresholds, a phenomenon also reported in multi-channel and mobile methane monitoring systems [31,33]. These findings support the conclusion that low-cost sensors, when integrated into a well-designed measurement system and validated against reference instruments, can provide meaningful and operationally useful data for real-time soil greenhouse gas monitoring.

4.4. Biogeochemical Interpretation

The contrasting behavior of CO₂ and CH₄ observed during field measurements can be explained by established soil biogeochemical processes. Soil CO₂ emissions primarily reflect microbial respiration and root activity, which can occur across a wide range of moisture and oxygen conditions [34]. In contrast, CH₄ production is strongly associated with anaerobic conditions and active methanogenic microbial communities, which are highly sensitive to soil moisture and oxygen availability [35].

During the field measurement period, drought conditions prevailed in the sugarcane cultivation area, resulting in well-aerated soils unfavorable for methanogenesis. Similar reductions or absence of detectable CH₄ emissions under dry conditions have been reported in both laboratory and long-term field studies [36,37]. Consequently, the absence of detectable CH₄ emissions in the field reflects site-specific biogeochemical conditions rather than limitations of the monitoring system. This outcome underscores the importance of interpreting sensor-based measurements within the context of soil–water–microbial interactions and highlights the potential of the developed system to capture environmentally driven variations in soil greenhouse gas dynamics.

4.5. Cost Analysis and System Feasibility

The summary of bill of materials and associated costs of the developed monitoring system is presented in

Table 2. Summary of bill of materials.

Components	Specification	Unit	Total Cost	Materials Source Link	Types of Materials
CO2 sensor	NDIR	1	$15.9	https://www.alibaba.com/product-detail/MH-Z19-MH-Z19B-NDIR-Infrared_60664884475.html (accessed on 30 April 2026).	Electronics
CH4 sensor	MQ-4	1	$2.5	https://www.alibaba.com/product-detail/ACEBOTT-5V-300-10000ppm-Electronic-Component_1601766172025.html (accessed on 30 April 2026).	Electronics
4G hotspot	LTE 150 Mbps	1	$69	https://www.alibaba.com/pla/TP-Link-M7200-4G-LTE-Mobile-Wi-Fi_1601573076499.html (accessed on 30 April 2026).	Electronics
Arduino ESP8266	NodeMCU	1	$1.5	https://www.alibaba.com/product-detail/100-Stock-ESP8266-NodeMCU-LUA-CH340_1601516752274.html (accessed on 30 April 2026).	Electronics
Solar panel	120 W	1	$24	https://www.alibaba.com/product-detail/120-Watt-12-Volt-Monocrystalline-Solar_1601666079358.html (accessed on 30 April 2026).	Electronics
	System cost		$112.9

, with a total estimated cost of approximately 112.9 USD. The system is constructed using low-cost and commercially available electronic components, including gas sensors, a microcontroller unit, a wireless communication module, and a solar-powered energy supply. Compared with conventional greenhouse gas monitoring systems that rely on high-cost analytical instruments, the proposed system provides a significantly more affordable alternative while maintaining acceptable measurement performance under both simulated and field conditions. This finding is consistent with previous studies demonstrating the feasibility of low-cost IoT-based environmental monitoring systems for real-time applications [4,12,13,14]. In addition, the integration of a solar-powered system and wireless communication enables autonomous operation in remote agricultural environments, aligning with recent developments in self-powered monitoring systems [21,22]. Therefore, the developed system is not only economically feasible but also scalable and suitable for large-scale deployment in agricultural greenhouse gas monitoring and climate-smart farming applications.

5. Conclusions

This study developed and evaluated a low-cost, real-time monitoring system for soil CO₂ and CH₄ emissions for practical agricultural field applications. The proposed system integrates surface emission chambers, low-cost gas sensors, a solar-powered energy supply, and IoT-based wireless communication into a single autonomous platform capable of continuous field operation. This integrated design addresses key limitations of conventional greenhouse gas measurement approaches, including high cost, operational complexity, and limited temporal resolution, by providing a cost-effective and scalable solution suitable for long-term environmental monitoring.

The experimental results demonstrated that system performance is strongly influenced by chamber configuration and environmental conditions. In particular, the use of surface emission chambers with different heights (40, 60, and 80 cm) provided important insights into the role of chamber geometry in gas accumulation behavior and relative agreement with the reference instrument. Among the tested configurations, the 80 cm chamber achieved the highest relative agreement for both CO₂ and CH₄ under simulated conditions, highlighting the importance of sufficient headspace volume in chamber-based measurements.

Field deployment in a sugarcane cultivation area confirmed the applicability of the developed system for continuous CO₂ monitoring under real agricultural conditions. The system operated stably under field conditions and enabled real-time data acquisition without reliance on grid electricity. Although CH₄ was not detected during the field measurement period, this result is attributed to unfavorable soil conditions for methane production, particularly drought-induced and well-aerated soil environments, rather than limitations of the sensor system itself.

Overall, the developed monitoring platform demonstrates strong potential as a practical and low-cost tool for real-time soil greenhouse gas monitoring. The system is particularly suitable for applications in agricultural engineering, precision agriculture, and climate-smart farming practices. Future research should focus on validating the system in methane-emitting environments, improving data processing and flux estimation methods, and extending the platform to support multi-gas monitoring and decision-support integration.