Non-dispersive Infrared Research Articles

Alternative Analyzers for the Measurement of Gaseous Compounds During Type-Approval of Heavy-Duty Vehicles

Emissions standards describe the fuels, the procedures, and, among others, the analyzers to be used for the measurement of the different compounds during the type-approval of heavy-duty engines and vehicles. Traditionally, NOx, CO, hydrocarbons, and CO2 were the gaseous compounds measured within the Euro standard, with the later addition of CH4 and NH3. Euro 7, introduced in early 2024, expanded those compounds, requiring the measurement of N2O and HCHO. With an increasing number of molecules that need to be measured and introducing carbonless fuels, such as hydrogen, that present different requirements compared to carbon-based fuels, the test procedure needs to be updated. The performances of three laboratory-grade instruments and three portable emissions measurement systems based on Fourier-transformed infrared (FTIR) or quantum cascade laser infrared (QCL-IR) technologies were investigated while measuring from the tailpipe of a Diesel engine and a compressed natural gas (CNG) vehicle. All instruments presented good agreement when emissions of NOx, CO, CH4, NH3, N2O, HCHO, and CO2 were compared using: Z-score, F-test and two tail t-test of student. Water concentration measured by the four FTIRs was also in good agreement. Moreover, the dry emissions of CO2 and CO measured by the laboratory non-dispersive infrared (NDIR) and corrected using water were a few percentages different from those obtained using the regulated carbon-based approach. The results indicate that all the investigated systems are suitable for the measurement of the investigated gaseous compounds, including CO2 and H2O.

Concentration calculation model for calibration of non-dispersive infrared gas detection system

Non-dispersive infrared (NDIR) gas detection systems have been extensively used for gas monitoring because they are considered the simplest approach with moderate sensitivity and fast response. Concentration calculation models for calibration are particularly important in NDIR gas detection systems because of the nonlinear relationship between the output voltage ratio and concentration. We propose a concentration calculation model with two fitting parameters for non-dispersive infrared gas detection systems, accounting for the fact that not all IR radiation that impinges upon the detector is absorbed by the gas and for the saturation effects in absorption peaks leading to the nonlinear relationship. Despite the small number of fitting parameters of the proposed concentration calculation model, it presents high quality curve fitting to experimental data. The performance of the proposed model is compared to that of other concentration calculation models.

Development of a Compact NDIR CO2 Gas Sensor for a Portable Gas Analyzer

A carbon dioxide (CO2) gas sensor based on non-dispersive infrared (NDIR) technology has been developed and is suitable for use in portable devices for high-precision CO2 detection. The NDIR gas sensor comprises a MEMS infrared emitter, a MEMS thermopile detector with an integrated optical filter, and a compact gas cell with high optical coupling efficiency. A dual-ellipsoid mirror optical system was designed, and based on optical simulation analysis, the structure of the dual-ellipsoid reflective gas chamber was designed and optimized, achieving a coupling efficiency of up to 54%. Optical and thermal simulations were conducted to design the sensor structure, considering thermal management and light analysis. By optimizing the gas cell structure and conditioning circuit, we effectively reduced the sensor’s baseline noise, enhancing the overall reliability and stability of the system. The sensor’s dimensions were 20 mm × 10 mm × 4 mm (L × W × H), only 15% of the size of traditional NDIR gas sensors with equivalent detection resolution. The developed sensor offers high sensitivity and low noise, with a sensitivity of 15 μV/ppm, a detection limit of 90 ppm, and a resolution of 30 ppm. The total power consumption of the whole sensor system is 6.5 mW, with a maximum power consumption of only 90 mW.

Accelerating the Diagnosis of Pandemic Infection Based on Rapid Sampling Algorithm for Fast-Response Breath Gas Analyzers.

This paper presents a novel technique for extracting the alveolar part of human breath. Gas exchange occurs between blood and inhaled air in the alveoli, which is helpful in medical diagnostics based on breath analysis. Consequently, the alveolar portion of the exhaled air contains specific concentrations of endogenous EVOC (exogenous volatile organic compound), which, among other factors, depend on the person's health condition. As this part of the breath enables the screening for diseases, accurate sample collection for testing is crucial. Inaccurate sampling can significantly alter the composition of the specimen, alter the concentration of EVOC (biomarkers) and adversely affect the diagnosis. Furthermore, the volume of alveolar air is minimal (usually <350 mL), especially in the case of people affected by respiratory system problems. For these reasons, precise sampling is a key factor in the effectiveness of medical diagnostic systems. A new technique ensuring high accuracy and repeatability is presented in the article. It is based on analyzing the changes in carbon dioxide concentration in human breath using a fast and compensated non-dispersive infrared (NDIR) sensor and the simple moving adjacent average (SMAA) algorithm. Research has shown that this method accurately identifies exhalation phases with an uncertainty as low as 20 ms. This provides around 350 ms of breath duration for carrying out additional stages of the diagnostic process using various types of analyzers.

Two-wavelength non-dispersive infrared sensing systems using stacked electrically controllable photonic-crystal band-pass filters

We present a scheme of non-dispersive infrared (NDIR) sensing utilizing stacked, two-wavelength electrically controllable bandpass filters that integrate multiple quantum wells (MQWs) and photonic crystals. By appropriately designing the MQWs and photonic crystals, we realize electrically controllable filters that exhibit symmetric, narrow-band transmittance spectra with high transmittance at two target wavenumbers (1035 cm-1 and 1085 cm-1) and demonstrate independent modulation of the transmittance at each target wavenumber when the two filters are stacked. In addition, by using the proposed stacked filters, we construct two-wavelength mechanical-chopper-free NDIR systems with a single detector and demonstrate its ability to robustly measure the gas concentration even when the absolute optical power incident on the detector is varied.

Multi-component Freon gas detection based on infrared tunable Fabry-Perot detector

A multi-component Freon gas sensing system was developed based on the non-dispersive infrared (NDIR) spectroscopy, which had the advantages of simple structure and low cost. This system mainly consisted of a broadband infrared light source, a tunable Fabry-Perot (FP) detector and a small brass absorption cell. In order to improve the utilization rate of infrared light source, the absorption cell was optimized. H1301, R134a and R410A were simultaneously detected through the measurement of gas absorption spectrum. The spectral range of the FP detector was from 8.0 to 10.5 μm, and the entire spectrum was recorded by wavelength scanning. The area of measured absorbance was directly proportional to the concentration of the target gas, which was used to calibrate the sensing system. The temperature and frequency response characteristics of the system were tested. The experimental results showed that the higher the temperature, the lower the responsiveness. In addition, the system had the best signal-to-noise ratio (SNR) at 10 Hz. The minimum detection limits of H1301, R134a and R410A were achieved to be 2.5 ppm, 5.3 ppm and 4.8 ppm, respectively. The cross-interference among the gases was suppressed by using BP neural network.

A cost-effective method for quantifying soil respiration

Soil respiration is a critical indicator of microbial activity, reflecting soil health and its ability to deliver essential ecosystem services and functions. Chamber-based measurements provide direct observations and are relatively simple to implement, making them a popular choice for soil respiration studies. However, current methods to quantify soil respiration are limited in their applicability by high costs, substrate requirements, accuracy concerns and substantial setup time. With an increasing emphasis on routine analysis of soil respiration, existing methods are insufficient to provide the temporal and spatial scale required to proliferate soil respiration data. This study assesses the potential of an affordable and commercially available Non-Dispersive Infrared (NDIR) CO2 detector, used in conjunction with an easy-to assemble closed chamber, to provide reliable and accessible soil respiration measurements. The CO2 detectors utilised in this study are cost-effective yet precise digital detectors, successfully validated against a laboratory reference sensor and the standard alkali trap method. Beyond that, the detector has effectively yielded consistent results across replicates and demonstrated sensitivity similar to standard methods. The proposed detector offers an alternative to traditional laboratory methods by removing the necessity to perform soil respiration analysis in a laboratory setting. The proliferation of soil respiration data would facilitate the increasing interest in accessible information on soil respiration from stakeholders, citizen scientists and decision makers.

A temperature-compensated CO2 detection system based on non-dispersive infrared spectral technology.

The concentration of carbon dioxide (CO2) is an important indicator for coal mine safety. Real-time monitoring of CO2 concentration is of great importance for taking actions in advance to avoid the occurrence of potential accidents. To address the issues of poor portability and high cost associated with existing coal mine CO2 detection equipment, this paper develops a miniaturized CO2 detection system based on non-dispersive infrared (NDIR) technology. This sensor integrates an infrared light source and a dual-channel pyroelectric detector into a reflective gas chamber, thereby achieving an extended optical path and higher system sensitivity within limited space. Meanwhile, the noise interference was greatly mitigated by using hardware and software filtering techniques. Based on principle analysis, the Lambert-Beer law was parametrically corrected, and then, a model relationship between the dual-channel voltage ratio and concentration was established. In addition, temperature compensation for zero and span values was introduced to improve the adaptability of the detection results to temperature changes. Testing results indicate that the developed detection system can realize CO2 measurement in the concentration range of 0 to 50 000 ppm within a temperature range of 0-40 °C, with a maximum detection error of less than 0.12% and a repeatability deviation of less than 1.04%. During a stability test for 12h, the maximum concentration drift is 0.07%, indicating that the developed system meets the requirements for monitoring CO2 safety in coal mines.

Ship Emission Measurements Using Multirotor Unmanned Aerial Vehicles: Review

This review investigates the ship emission measurements using multirotor unmanned aerial vehicles (UAVs). The monitoring of emissions from shipping is a priority globally, because of the necessity to reduce air pollution and greenhouse gas emissions. Moreover, there is widespread global effort to extensively measure vessel fuel sulfur content (FSC). The majority of studies indicate that more commonly used methods for measuring ship emission with UAVs is the sniffing method. Most of the research is concerned with determining the fuel sulfur content. Fuel sulfur content can be determined by the ratio of CO2 and SO2 concentration in the exhaust gas plume. For CO2, the non-dispersive infrared (NDIR) method is used, the most common measuring range reaches 0–2000 ppm, the overall measuring range 0–10,000 ppm, and detection accuracy is ±5–300 ppm. For SO2, the electrochemical (EC) method is used, the measuring range reaches 0–100 ppm, and the detection accuracy is ±5 ppm. Common UAV characteristics, used in measurement with ships, involve the following: 8–10 m/s of wind resistance, 5–6 kg maximum payload, and a flight distance ranging from 5 to 10 km. This can change in the near future, since a variety of emission measuring devices that can be mounted on UAVs are available on the market. The range of available elements differs from device to device, but available ranges are allowed and the accuracy provides good possibilities for wider research into ship emissions.

Development of High-Precision NO2 Gas Sensor Based on Non-Dispersive Infrared Technology.

Increasing concerns about air quality due to fossil fuel combustion, especially nitrogen oxides (NOx) from marine and diesel engines, necessitate advanced monitoring systems due to the significant health and environmental impacts of nitrogen dioxide (NO2). In this study, a gas detection system based on the principle of the non-dispersive infrared (NDIR) technique is proposed. Firstly, the pyroelectric detector was developed by employing an ultra-thin LiTaO3 (LT) layer as the sensitive element, integrated with nanoscale carbon material prepared by wafer-level graphics technology as the infrared absorption layer. Then, the sensor was hermetically sealed using inert gas through energy storage welding technology, exhibiting a high detectivity (D*) value of 4.19 × 108 cm·√Hz/W. Subsequently, a NO2 gas sensor was engineered based on the NDIR principle employing a Micro Electro Mechanical System (MEMS) infrared (IR) emitter, featuring a light path chamber length of 1.5 m, along with integrated signal processing and software calibration algorithms. This gas sensor was capable of detecting NO2 concentrations within the range of 0-500 ppm. Initial tests indicated that the gas sensor exhibited a full-scale relative error of less than 0.46%, a limit of 2.8 ppm, a linearity of -1.09%, a repeatability of 0.47% at a concentration of 500 ppm, and a stability of 2% at a concentration of 500 ppm. The developed gas sensor demonstrated significant potential for application in areas such as industrial monitoring and analytical instrumentation.

Smart mid-infrared metasurface microspectrometer gas sensing system

Smart, low-cost and portable gas sensors are highly desired due to the importance of air quality monitoring for environmental and defense-related applications. Traditionally, electrochemical and nondispersive infrared (IR) gas sensors are designed to detect a single specific analyte. Although IR spectroscopy-based sensors provide superior performance, their deployment is limited due to their large size and high cost. In this study, a smart, low-cost, multigas sensing system is demonstrated consisting of a mid-infrared microspectrometer and a machine learning algorithm. The microspectrometer is a metasurface filter array integrated with a commercial IR camera that is consumable-free, compact ( ~ 1 cm3) and lightweight ( ~ 1 g). The machine learning algorithm is trained to analyze the data from the microspectrometer and predict the gases present. The system detects the greenhouse gases carbon dioxide and methane at concentrations ranging from 10 to 100% with 100% accuracy. It also detects hazardous gases at low concentrations with an accuracy of 98.4%. Ammonia can be detected at a concentration of 100 ppm. Additionally, methyl-ethyl-ketone can be detected at its permissible exposure limit (200 ppm); this concentration is considered low and nonhazardous. This study demonstrates the viability of using machine learning with IR spectroscopy to provide a smart and low-cost multigas sensing platform.

Low-cost UAV coordinated carbon observation network: Carbon dioxide measurement with multiple UAVs

Improving the mitigation of global greenhouse effects requires drastic reductions in carbon emissions. Effective carbon management at different spatial scales is therefore crucial to a more sustainable path of economic development. Regional and local carbon management currently rely on the traditional bottom-up method of emission reports, which are known for their opaque and complex procedures. Novel top-down carbon monitoring methods including space-based, aerial and ground-based observations are tantalising alternatives to more reliable data sources of carbon emissions as well as sinks. Unmanned Aerial Vehicles (UAVs) based carbon monitoring is an upcoming field because of its lower costs, higher spatial-temporal resolution and operability at a wider range of weather conditions compared to satellite observations. UAVs equipped with Non-dispersive Infrared (NDIR) carbon dioxide (CO2) sensors can measure in the air with faster response and can intelligently navigate themselves within areas of greater interest. With the help of lighter NDIR payloads and multiple UAVs flying in synchrony, larger cross sections or areas for maximising information acquisition of emission plumes can be covered. In this article, we first introduce the design of a miniaturised NDIR payload, which is compatible with a lightweight UAV to achieve a single system weighing less than 4 kg. Then, we test our design via comparisons against another NDIR payload to determine its accuracy (−0.82 ppm and −0.44 ppm) and precision (0.12 ppm and −0.03 ppm) in measurements of two vertical concentration profiles. Finally, we deployed four UAVs on two major anthropogenic emission source monitoring campaigns with coordinated flight patterns. To fully understand the benefit of multi-UAV carbon monitoring, we attempted two flight patterns and computed power plant emission rates via the cross-sectional flux method. While all flights successfully captured the concentration enhancements downwind of the power plants, the single-sectional flight pattern measured an emission rate of 10ktCO2/day which is 44% less than that reported monthly and the multi-sectional flight pattern yielded relatively varied results (8.5ktCO2/day on average, which is 54% less) for the respective sections due to wind underestimations, plume section undersampling and wind fluctuations.

Combo chloro-photosynthetic device and applications for greenhouse gas reduction campaign and smart agriculture

The increasing carbon dioxide (CO2) levels in the air pose a direct threat to all living organisms and the environment. Leveraging the ability of plants to absorb CO2 is one of the most effective methods for countering these rising CO2 levels. The present study aimes to develop a combo photosynthetic and chlorophyll-a sensor based on Non-Dispersive Infrared (NDIR) spectroscopy and an optical method. This sensor enables simultaneous, intensive measurement of net photosynthesis and chlorophyll-a content and yields accurate information. Comparative analysis of the efficacy of the sensors to that of a commercial instrument demonstrated that the measurement values obtained from the developed photosynthetic and chlorophyll-a sensors were not significantly different from those acquired with the commercial instrument (portable photosynthesis system LI-6400) and chlorophyll metre (SPAD-502), with a 95 % confidence level. Furthermore, the developed photosynthetic sensor could be used as a new correlation unit for chlorophyll-a content and net photosynthesis. Therefore, the sensor can be used to propose effective plantation processes to reduce atmospheric CO2 levels and in smart farming systems to control the quality of yields.

Non-dispersive infrared SF6 sensor with temperature compensation using ISSA_BP neural network

Sulfur hexafluoride (SF6) is a widely used gas in the power industry, and its concentration monitoring is of great importance in power systems. In this study, a non-dispersive infrared (NDIR) gas sensor was developed for monitoring SF6 with a response time (t90) of 3–4 s. A dual-channel structure was designed to minimize the influence of other factors such as light sources. However, the sensor’s output signal is susceptible to temperature drift and non-linear characteristics. To address these challenges, a new compensation algorithm of improved sparrow search algorithm based on the backpropagation neural network (ISSA_BP) is presented to improve the temperature dependence and to correct the nonlinear errors of the sensors. The ISSA_BP algorithm extracts features from sensor-collected signals and predicts the concentration of SF6 gas by the BP neural network. The levy flight strategy and sine-cosine factor are employed within the sparrow search algorithm (SSA) to improve the efficiency and accuracy of the method. The experimental results show that the proposed model outperforms the state-of-the-art approaches, achieving an average relative error of 0.02 within the range of −10°C to 45°C and gas concentrations from 0 ppm to 5000 ppm, which is 3% lower than the industry standard. Compared with traditional approaches, the measurement accuracy is improved approximately by 0.02–0.03, confirming that the proposed algorithm has a high reference value for temperature compensation and nonlinear calibration, which is applicable in the production of infrared sensors for industrial settings.

The River Runner: a low-cost sensor prototype for continuous dissolved greenhouse gas measurements

Abstract. Freshwater ecosystems are sources of the two most relevant greenhouse gases (GHGs): CO2 and CH4. Understanding the importance of freshwater ecosystems in the global carbon cycle and their role in global warming trends requires the accurate quantification of gas fluxes from the water phase to the atmosphere. These fluxes depend on the gas exchange velocity and the concentration gradient between the phases, which both cause high spatio-temporal variability in fluxes. On a global scale, the estimation of fluxes is limited by the lack of cheap and accurate methods to measure dissolved gas concentrations. Low-cost sensors, as an alternative to expensive gas analysers, are available; however, to date, the in situ performance of such sensors has been poorly examined. Here, we present an inexpensive data-logging sensor prototype that provides continuous measurements of dissolved CO2 and CH4 in submerged environments. Gas measurements are done in a confined gas space, which is rapidly equilibrated with the water phase through a single-layer polytetrafluoroethylene (PTFE) membrane, by a miniature non-dispersive infrared (NDIR) sensor for CO2 (Sunrise sensor, Senseair, Sweden) and a cheap metal oxide sensor for CH4 (TGS2611-E, Figaro Engineering Inc., Japan). Pressure, temperature and humidity are measured to correct raw sensor readings. For freshwater, the dissolved gas concentration is directly obtained from the measured molar fraction and temperature and pressure readings. In air, we measured the molar fraction of CO2 in a range from 400 to 10 000 ppm and the molar fraction of CH4 in a range from 2 to 50 ppm with an accuracy of ± 58 and ± 3 ppm respectively. We successfully used our prototype to measure diurnal variations in dissolved CO2 in a natural stream. We further calibrated the CH4 sensor for in situ use at concentrations ranging from 0.01 to 0.3 µmol L−1. Underwater, we were able to measure the molar fraction of CH4 in the prototype head with an accuracy of ± 13 ppm in the range from 2 to 172 ppm. The underwater measurement error of CH4 is always higher than for the same concentration range in air, and CH4 is highly overestimated below 10 ppm. At low CH4, humidity was the most important influence on the TGS2611-E sensor output in air, whereas temperature became the predominant factor underwater. We describe the response behaviour of low-cost sensors in submerged environments and report calibration methods to correct for temperature and humidity influence on the sensor signal if used underwater. Furthermore, we provide do-it-yourself instructions to build a sensor for submerged continuous measurements of dissolved CO2 and CH4. Our prototype does not rely on an external power source, and we anticipate that such robust low-cost sensors will be useful for future studies of GHG emissions from freshwater environments.

Sub-ppm NDIR [formula omitted] gas sensor using ICEEMDAN-SG joint denoising algorithm

Due to the excellent insulation and arc extinguishing properties of SF6 gas, it is widely used in power equipment such as gas insulated switchgear or gas circuit breaker. Therefore, detection of SF6 gas leakage with high sensitivity is necessary. Non dispersive infrared (NDIR) technology have advantages such as miniaturization, low power consumption, simple structure, low cost, and non-destructive testing, making it suitable for building large-scale sensor networks. However, NDIR sensors are susceptible to noise coming from the emitter, the detector and the circuits, which receives little research attention. In this study, we propose a new denoising method by combining improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) with Savitzky-Golay (S-G) to the noise suppression, which achieves a 7 dB signal-to-noise ratio improvement over the traditional wavelet threshold denoising, making the detection limit of the sensing system reach the level below 1 ppm.

Evaluation of a non-dispersive infrared spectrometer for quantifying organic and elemental carbon in diesel particulate matter.

Diesel particulate matter (DPM) is a common and well-known health hazard in the mining environment. The regulatory method for monitoring both the organic and elemental carbon (OC, EC) portions of DPM is a laboratory-based thermal-optical method with a typical turnaround time of one week. In order to evaluate exposure levels and take corrective action prior to overexposure, a portable real-time device capable of quantifying both OC and EC is needed. To that end, researchers from the National Institute for Occupational Safety and Health (NIOSH) designed and tested the feasibility of a device based on bandpass optical filters that target key infrared wavelengths associated with DPM and its spectroscopic baseline. The resulting device, referred to here as a non-dispersive infrared (NDIR) spectrometer could serve as the basis of a cost-effective, field-portable alternative to the laboratory thermal-optical method. The limits of quantification (LOD) indicate that the NDIR spectrometer can quantify EC, OC, and TC provided they are present at 20, 37, and 46 μg/m3 or more, respectively. In the event that the NDIR spectrometer is integrated with a sampler and filter tape the LOD is estimated to be reduced to 13, 7, and 10 μg/m3 for EC, OC, and TC, respectively. These LOD estimates assume a face velocity of 59 cm/s and a sampling time of 30 min.

Design and fabrication of poly-Si/SiO2 Fabry–Perot filter for nondispersive IR CO2 sensors

The relationship between the transmittance and FWHM of a Fabry–Perot filter for a nondispersive carbon dioxide (CO2) sensor was investigated as a function of the number of distributed Bragg reflector (DBR) pairs consisting poly-Si and SiO2 thin films. Given the significant prior research on the fabrication of high-performance Fabry–Perot filters, this study is focused on the relationship between the transmittance and FWHM that can be achieved by controlling the reflectance of the DBR pairs. Each layer of the filter was simulated adequately as the poly-Si and SiO2-based DBR pairs, and poly-Si and SiO2 were deposited on the soda–lime substrate by RF sputtering and low-pressure chemical vapor deposition based on the simulation results. The fabricated filter showed a transmittance of 43.7% and FWHM of 125 nm at 4.26 μm. The NDIR CO2 sensor with Fabry–Perot filter showed enhanced selectivity to CH4 and CO compared with normalized CO2 response.

Measurement of Light-Duty Vehicle Exhaust Emissions with Light Absorption Spectrometers

Light-duty vehicle emission regulations worldwide set limits for the following gaseous pollutants: carbon monoxide (CO), nitric oxides (NOX), hydrocarbons (HCs), and/or non-methane hydrocarbons (NMHCs). Carbon dioxide (CO2) is indirectly limited by fleet CO2 or fuel consumption targets. Measurements are carried out at the dilution tunnel with “standard” laboratory-grade instruments following well-defined principles of operation: non-dispersive infrared (NDIR) analyzers for CO and CO2, flame ionization detectors (FIDs) for hydrocarbons, and chemiluminescence analyzers (CLAs) or non-dispersive ultraviolet detectors (NDUVs) for NOX. In the United States in 2012 and in China in 2020, with Stage 6, nitrous oxide (N2O) was also included. Brazil is phasing in NH3 in its regulation. Alternative instruments that can measure some or all these pollutants include Fourier transform infrared (FTIR)- and laser absorption spectroscopy (LAS)-based instruments. In the second category, quantum cascade laser (QCL) spectroscopy in the mid-infrared area or laser diode spectroscopy (LDS) in the near-infrared area, such as tunable diode laser absorption spectroscopy (TDLAS), are included. According to current regulations and technical specifications, NH3 is the only component that has to be measured at the tailpipe to avoid ammonia losses due to its hydrophilic properties and adsorption on the transfer lines. There are not many studies that have evaluated such instruments, in particular those for “non-regulated” worldwide pollutants. For this reason, we compared laboratory-grade “standard” analyzers with FTIR- and TDLAS-based instruments measuring NH3. One diesel and two gasoline vehicles at different ambient temperatures and with different test cycles produced emissions in a wide range. In general, the agreement among the instruments was very good (in most cases, within ±10%), confirming their suitability for the measurement of pollutants.

Validation and field application of a low-cost device to measure CO2 and evapotranspiration (ET) fluxes

Abstract. Mitigating the global climate crisis and its consequences, such as more frequent and severe droughts, is one of the major challenges for future agriculture. Therefore, identifying land use systems and management practices that reduce greenhouse gas (GHG) emissions and promote water use efficiency (WUE) is crucial. This, however, requires accurate and precise measurements of carbon dioxide (CO2) fluxes and evapotranspiration (ET). Despite that, commercial systems to measure CO2 and ET fluxes are expensive and thus often exclude research in ecosystems within the Global South. This is especially true for research and data of agroecosystems in these areas, which are to date still widely underrepresented. Here, we present a newly developed low-cost, non-dispersive infrared (NDIR)-based CO2 and ET flux measurement device (∼ EUR 200) that provides reliable, accurate and precise CO2 and ET flux measurements in conjunction with manually operated closed chambers. To validate the system, laboratory and field validation experiments were performed, testing multiple different low-cost sensors. We demonstrate that the system delivers accurate and precise CO2 and ET flux measurements using the K30 FR NDIR (CO2) and SHT31 (RH, relative humidity) sensor. An additional field trial application demonstrated its longer-term stability (&gt; 3 months) and ability to obtain valid net ecosystem C balances (NECBs) and WUE. This was the case, even though environmental conditions at the field trial application site in sub-Saharan Africa were rather challenging (e.g., extremely high temperatures, humidity and rainfall). Consequently, the developed low-cost CO2 and ET flux measurement device not only provides reasonable results but also might help with democratizing science and closing current data gaps.