CO2 Concentration Measurements Research Articles

Development of an off-axis cavity-enhanced absorption spectroscopy system with open-path configuration for gas sensing

A compact off-axis cavity-enhanced absorption spectroscopy system with open-path configuration is developed by using a narrow-band CW laser as light source. The open-path configuration can avoid absorption cell wall losses and sampling induced artifacts. The absolute reflectivity of the cavity mirrors is determined to be 99.8% by a simple and effective method, and an effective optical path length of 315.66 m is realized based on a 45 cm long high optical finesse open-path cavity. In order to confirm the ability of the system, a series of measurements of CO2 concentrations are performed by targeting a CO2 line at 5001.49 cm−1. According to the time series measurements of ambient CO2, a sensitivity is 7.819 ppm while the averaging time is 1 s, and an optimum sensitivity of 193 ppb can be achieved with an averaging time of 300 s. And two 24 h’ field continuous measurements are performed to demonstrate the stability of the reported system.

Development of a small unmanned aircraft system to derive CO<sub>2</sub> emissions of anthropogenic point sources

Abstract. A reduction of the anthropogenic emissions of CO2 (carbon dioxide) is necessary to stop or slow down man-made climate change. To verify mitigation strategies, a global monitoring system such as the envisaged European Copernicus anthropogenic CO2 monitoring mission (CO2M) is required. Those satellite data are going to be complemented and validated with airborne measurements. Unmanned aerial vehicle (UAV)-based measurements can provide a cost-effective way to contribute to these activities. Here, we present the development of an sUAS (small unmanned aircraft system) to quantify the CO2 emissions of a nearby point source from its downwind mass flux without the need for any ancillary data. Specifically, CO2 is measured by an NDIR (non-dispersive infrared) detector, and the wind speed and direction are measured with a 2-D ultrasonic acoustic resonance anemometer. By means of laboratory measurements and an in-flight validation at the ICOS (Integrated Carbon Observation System) atmospheric station Steinkimmen (STE) near Bremen, Germany, we estimate that the individual CO2 measurements have a precision of 3 ppm and that CO2 enhancements can be determined with an accuracy of 1.3 % or 0.9 ppm, whichever is larger. We introduce an anemometer calibration method to minimize the effect of rotor downwash on the wind measurements. This method derives the fit parameters of a linear calibration model accounting for scaling, rotation, and a potential constant bias. For this purpose, it analyzes wind measurements taken while following a suitable flight pattern and assuming stationary wind conditions. From the calibration and validation experiments, we estimate the single measurement precision of the horizontal wind speed to be 0.40 m s−1 and the accuracy to be 0.33 m s−1. By means of two flights downwind of the ExxonMobil natural gas processing facility in Großenkneten about 40 km west of Bremen, Germany, we demonstrate how the measurements of elevated CO2 concentrations can be used to infer mass fluxes of atmospheric CO2 related to the emissions of the facility.

Implementation of MPC for an all-air system in an educational building

The building sector has to significantly reduce the total energy use. A predictive control could be a solution to control an HVAC system more energy efficiently since it takes into account the current measurements and the future demand. In this study a predictive control framework is implemented in an educational building with two lecture rooms. The airflow rate is controlled by VAV boxes based on measurements of CO2 concentration and operative temperature. The dynamic model used for optimization of the control input is a grey-box model, previously identified using measurement data. Weather forecasts and weekly lecture schedules are used as forecasts for the optimization of future control actions. The control actions resulting from the optimization are written to the set points for supply air temperature and VAV damper position using the BACnet interface. Results of the first trial indicate that the predictive control is able to control the room temperature and CO2 concentration, even with uncertainty introduced by the forecasts. Prediction errors observed were 0.17 ˚C for room temperature and 87 ppm for indoor CO2 concentration.

The Study of Co2 Concentration in A Classroom During The Covid-19 Safety Measures

The COVID-19 crisis has affected the process of how the study procedures are organized at schools in Latvia. Three different options were available for the school to choose from. However, most schools have opted for option A which states that the classes are organized face-to-face but various safety measures must be ensured. Each class or group is equated to a closed set where there are no distance requirements. In turn, the distance between the classes must be observed. This means that students stay in the same class all day and are accompanied by teachers of the respective classes. This can lead to improper ventilation as for most of the schools in Latvia it is organized through the opening of windows. To test this, measurements of CO2 concentration were done in a classroom Secondary School in Daugavpils. The results showed that the CO2 concentration was very high and often reached and exceeded the maximum measuring capacity of the device - 4000 ppm. It indicates that following the special safety procedures cause a negative effect on IAQ as the classrooms are not properly ventilated. This can lead to a drop in the performance of pupils as well as stimulate the transmission of other infectious diseases. Further measurements are necessary to gather data from different schools and best practices must be found.

Analysis of Particulate Matter 2.5, carbon monoxide, carbon dioxide, CO/CO2 ratio and rate of fuel consumption from the use of biomass stove fueled by corncob and rice husk

This study was conducted to analyze PM2.5, CO and CO2 concentrations, CO/CO2 ratio, and the rate of fuel consumption due to the use of a biomass stove. Water Boiling Test Method was used to simulate cooking activities, which consisted of three phases, i.e., cold start (CS), hot start (HS), and simmering (SM). Biomass wastes used in this research were corncobs and rice husks. Based on the measurement results, for the corncob, PM2.5 concentrations were 239.823±60.83, 262.962±79.17, and 120.75±45.20μg/Nm3 at CM, HS, and SM phases, respectively. While for CO concentrations during the CM, HS, and SM phases were 36.984 ±3.67, 35.918±1.74, and 37.959±5.56 ppm, correspondingly. Moreover, 595,468±13.25, 611,492±7.73, and 565,205±18.50 ppm CO2 concentrations were detected during the CM, HS, and SM phases, respectively. Furthermore, for the rice husk biomass waste, PM2.5 concentrations of 158.579±14.07, 115.014±16.08, and 69.603±17.11 μg/Nm3 were observed during the CS, HS, and SM phases. While for CO concentrations during the CS, HS, and SM phases, the measured values were, in turn, 38.152±2.73, 38.152±5.02, and 36.422±4.72 ppm. Lastly, the measured CO2 concentrations were 593,647±8.28, 589,241±12.45, and 556,886±13.06 ppm for the CS, HS, and SM phases, respectively. PM2.5 and CO concentrations did not meet the air quality standards for both biomass wastes, while CO2 meets the air quality standard according to Indonesian Minister of Health Regulation No. 1077/2011. The CO/CO2 ratio of the biomass stove is above 0.02, while the specific fuel consumption rate, for corncob were 0.186, 0.135, and 0.238g/g, while for the rice husk were 0.238, 0.305, and 0.335g/g, during the cold start, hot start, and simmering phases.

Office Building’s Occupancy Prediction Using Extreme Learning Machine Model with Different Optimization Algorithms

Abstract Increasing energy efficiency requirements lead to lower energy consumption in buildings, but at the same time occupants’ influence on the energy balance of the building during the use phase becomes more crucial. The randomness of the building’s occupancy often leads to the mismatch of the predicted and measured energy demand, also called Energy Performance Gap. Therefore, prediction of occupancy is important both in the design and use phases of the building. The goal of the study is to apply Extreme Learning Machine (ELM) models with different optimisation algorithms – Genetic (GA-ELM) and Simulated Annealing (SA–ELM) for occupancy prediction in an office building based on measured CO2 concentrations. Both models show similar and high accuracy of prediction: R2 – 0.73–0.74 and RMSE – 1.8–1.9 for the whole measured period. Influence of population size, number of neurons, and number of iterations on results accuracy was also analysed and recommendations are given. It was concluded that both methods are suitable for occupancy prediction, but because of different simulation times, SA-ELM is recommended for the Building Management Systems (BMS), where higher speed is required.

Research on the measurement of CO2 concentration based on multi-band fusion model

Research on the measurement of CO2 concentration based on multi-band fusion model

Detection of Li-ion battery failure and venting with Carbon Dioxide sensors

Abstract Li-ion battery thermal runaway is a critical safety issue for Electric Vehicles. The proposed global technical regulation No. 20 by the United Nations on Electric Vehicle Safety requires an advanced warning 5 minutes prior to the evolution of hazardous conditions caused by thermal runaway. To achieve this 5-min advanced warning, a robust and sensitive detection methodology is required. Gas venting is often a precursor of thermal runaway, and therefore the use of gas-based detection method was evaluated in this paper to explore its response and implementation within a battery pack. The composition of battery vent-gas during a thermal runaway event includes CO2, CO, H2 and volatile organic compounds (VOCs). Among these gas species, there is still some debate about which is most suitable for detection. To resolve this debate, the composition of vent-gas under different testing conditions is summarized from the literature and CO2 is proposed as the target gas species due to its significant presence and early occurrence in all venting events. After evaluating available sensors, the Non-Dispersive Infrared (NDIR) CO2 sensor is considered due to its robustness and cost effectiveness. To further clarify the responsiveness of the NDIR CO2 sensor, an overcharging experiment leading to cell venting was conducted with a prototype gas sensor suite. The measured CO2 concentrations of over 30,000 ppm were detected with the gas sensor. Lastly, we demonstrate how a representative venting experiment of a single cell can be used to guide and set the sensed CO2 threshold that will trigger an alarm in a battery pack volume.

DEVELOPMENT OF CALIBRATION GAS MIXTURES (CARBON DIOXIDE AND OXYGEN IN NITROGEN MATRIX) AT A TYPICAL CONCENTRATION RANGE OF MODIFIED ATMOSPHERE PACKAGING

Measurement of carbon dioxide (CO2), oxygen (O2), and nitrogen (N2) concentration in modified atmosphere packaging (MAP) food is critical to be carried out by the food industry. A slight variation in concentrations of CO2, O2, and N2 in food packaging may have a significant impact on product quality and safety for human health. Accurate and reliable measurement of CO2, O2, and N2 concentrations in food packaging is crucial, and it can only be achieved by calibrating the gas analyzer. This study aimed to develop gas mixtures for the calibration of CO2, O2, and N2 gas analyzers at a typical concentration range of modified atmosphere packaging. The calibration gas mixtures were prepared gravimetrically by following ISO 6142. The concentration ranges of CO2, O2, and N2 for calibration gas mixtures were set at 9-19% mol/mol, 1-5% mol/mol, and 74-88% mol/mol, respectively. Each parent gas was identified for its impurities using gas chromatography with a pulsed discharge helium ionization detector (GC-PDHID). The compositions of CO2, O2, and N2 in the mixtures were verified by evaluating the internal consistency within the prepared gas mixtures using gas chromatography with a thermal conductivity detector (GC-TCD). The short term stability of the prepared gas mixtures was evaluated using an equal division method. The result showed that good internal consistency was achieved between the gravimetrical and GC’s verification values, having linear regression coefficient (R2) ≥ 0.999. The t-test result has shown that CO2 has better short term stability than O2 and N2. In conclusion, the developed calibration gas mixtures at a typical concentration range of modified atmosphere packaging have shown satisfying results for CO2 component. However, further evaluation is still required to minimize the instability of O2 and N2 components.

Comparison of direct and indirect determinations of dynamic ventilation rate in a modern dairy free stall barn

Reliable estimation of the ventilation rate (VR) in intensive livestock buildings is necessary for studying building environmental control strategies and predicting indoor air quality and air emissions. As direct air exchange measurements are time-consuming and expensive, it is environmentally inefficient to measure livestock building VR continuously in practice. Hence, indirect VR estimation methods have been widely used in modelling environmental control and air emissions, and also to measure airflow in the field. The accuracy of indirect measurement methods needs to be evaluated by comparing with direct measurements. In this study, the direct and indirect methods of determining hourly and daily mean VRs were applied to a mechanically-ventilated dairy free stall barn monitored by the 24-month National Air Emissions Monitoring Study. The direct method was used to continuously monitor fan rotational speeds, and differential static pressures, coupled with periodic in-situ fan performance assessments, to calculate the VR. The indirect method consisted of estimating the VR using CO2 concentration measurements and the CO2 mass balance method. The average daily and hourly means (mean±SD) of directly measured barn ventilation rates for two years were (246±73) m3/s and (245±77) m3/s, respectively. The average daily and hourly means (mean±SD) of barn ventilation rates estimated by the CO2 mass balance method were (287±93.4) m3/s and (287±118) m3/s, respectively. Correlation analyses showed a strong correlation between the indirect CO2 mass balance method and direct measurement methods (r=0.93 for daily means and r=0.85 for hourly means). Keywords: dynamic ventilation rate, modern dairy, free stall barn, carbon dioxide, mass balance, dairy cow, direct and indirect determination, comparison DOI: 10.25165/j.ijabe.20201306.5767 Citation: Zou B, Heber A J, Shi Z X, Du S H, Jin Y, Lim T T. Comparison of direct and indirect determinations of dynamic ventilation rate in a modern dairy free stall barn. Int J Agric & Biol Eng, 2020; 13(6): 41–46.

Correlations between thermal satisfaction and non-thermal conditions of indoor environmental quality: Bayesian inference of a field study of offices

The judgment of thermal comfort is a cognitive process influenced by physical, psychological and other factors. Prior studies have suggested that occupants who are generally satisfied with many non-thermal conditions of indoor environmental quality (IEQ) are also more likely to be satisfied with thermal conditions as well. This paper applies Bayesian logistic regression to identify and predict the independent relationship between non-thermal metrics of IEQ, such as CO2 concentrations, noise levels, and light levels, and perceived thermal comfort. The study is the first to do so with respect to a large field study. The regression analysis is done against a dataset of objective and subjective IEQ measurements collected from 779 occupants of open-plan offices in large Canadian and US cities. The results suggest there is evidence supporting a view that measurements of indoor CO2 concentrations and indoor speech intelligibility are correlated with perceived thermal satisfaction. For example, a posteriori predictions drawn from the regression model suggest that, under the same psychrometric conditions (i.e., operative temperature = 23 °C, relative humidity = 30%, etc.), occupants experiencing indoor CO2 concentrations of 500 ppm were ~30 ± 8% more likely to state they felt thermally satisfied than occupants experiencing indoor conditions at 900 ppm.

Field Evaluation of Column CO2 Retrievals From Intensity‐Modulated Continuous‐Wave Differential Absorption Lidar Measurements During the ACT‐America Campaign

AbstractWe present an evaluation of airborne intensity‐modulated continuous‐wave (IM‐CW) lidar measurements of atmospheric column CO2 mole fractions during the Atmospheric Carbon and Transport–America (ACT‐America) project. This lidar system transmits online and offline wavelengths simultaneously on the 1.57111‐μm CO2 absorption line, with each modulated wavelength using orthogonal swept frequency waveforms. After the spectral characteristics of this system were calibrated through short‐path measurements, we used the HITRAN spectroscopic database to calculate the average‐column CO2 mole fraction (XCO2) from the lidar‐measured optical depths. Using in situ measurements of meteorological parameters and CO2 concentrations for calibration data, we demonstrate that our lidar CO2 measurements were consistent from season to season and had an absolute calibration error (standard deviation) of 0.80 ppm when compared to XCO2 values calculated from in situ measurements. By using a 10‐s or longer moving average, a precision of 1 ppm or better was obtained. The estimated CO2 measurement precision for 0.1‐, 1‐, 10‐, and 60‐s averages was determined to be 3.4, 1.2, 0.43, and 0.26 ppm, respectively. These correspond to measurement signal‐to‐noise ratios of 120, 330, 950, and 1,600, respectively. The drift in XCO2 over 1‐hr of flight time was found to be below 0.1 ppm. These analyses demonstrate that the measurement stability, precision, and accuracy are all well below the thresholds needed to study synoptic‐scale variations in atmospheric XCO2.

Experimental measurements of CO2 concentrations in sleeping rooms

People spend nearly one-third of their life on sleeping. Several factors can affect bedroom air quality and comfort of sleep, such as temperature, relative humidity and air quality. The most common indicator of indoor air quality is the concentration of carbon dioxide, its presence in indoor environment being strictly related to respiration and human metabolism. Since 2002, when the European Parliament and Council approved the directive on energy performance of buildings, EU member countries launched various programs for refurbishment of buildings and HVAC (Heating, Ventilation and Air Conditioning) systems, in order to reduce the energy consumption. Unfortunately, the renovation operations, such as replacing old windows with new tight ones or thermal insulation of the facades, lead to tightly sealed interior spaces. Insufficient infiltration of fresh air and limited natural ventilation result into increased pollutant concentration and deterioration of the indoor microclimate. Permissible concentration of carbon dioxide in the closed spaces according to World Health Organization is 1000 ppm. When the level exceeds this threshold, occupants may complain of headaches, drowsiness, lack of concentration and fatigue. The present study shows the measurements of carbon dioxide concentrations conducted in several sleeping rooms located in refurbished buildings, with or without mechanical ventilation system for fresh air supply, as well as suggested measures.

High-precision laser spectrometer for multiple greenhouse gas analysis in 1 mL air from ice core samples

Abstract. The record of past greenhouse gas composition from ice cores is crucial for our understanding of global climate change. Future ice core projects will aim to extend both the temporal coverage (extending the timescale to 1.5 Myr) and the temporal resolution of existing records. This implies a strongly limited sample availability, increasing demands on analytical accuracy and precision, and the need to reuse air samples extracted from ice cores for multiple gas analyses. To meet these requirements, we designed and developed a new analytical system that combines direct absorption laser spectroscopy in the mid-infrared (mid-IR) with a quantitative sublimation extraction method. Here, we focus on a high-precision dual-laser spectrometer for the simultaneous measurement of CH4, N2O, and CO2 concentrations, as well as δ13C(CO2). Flow-through experiments at 5 mbar gas pressure demonstrate an analytical precision (1 σ) of 0.006 ppm for CO2, 0.02 ‰ for δ13C(CO2), 0.4 ppb for CH4, and 0.1 ppb for N2O, obtained after an integration time of 100 s. Sample–standard repeatabilities (1 σ) of discrete samples of 1 mL STP (Standard Temperature and Pressure) amount to 0.03 ppm, 2.2 ppb, 1 ppb, and 0.04 ‰ for CO2, CH4, N2O, and δ13C(CO2), respectively. The key elements to achieve this performance are a custom-developed multipass absorption cell, custom-made high-performance data acquisition and laser driving electronics, and a robust calibration approach involving multiple reference gases. The assessment of the spectrometer capabilities in repeated measurement cycles of discrete air samples – mimicking the procedure for external samples such as air samples from ice cores – was found to fully meet our performance criteria for future ice core analysis. Finally, this non-consumptive method allows the reuse of the precious gas samples for further analysis, which creates new opportunities in ice core science.

Biases in open-path carbon dioxide flux measurements: Roles of instrument surface heat exchange and analyzer temperature sensitivity

Eddy covariance (EC) measurements of ecosystem-atmosphere carbon dioxide (CO2) exchange provide the most direct assessment of the terrestrial carbon cycle. Measurement biases for open-path (OP) CO2 concentration and flux measurements have been reported for over 30 years, but their origin and appropriate correction approach remain unresolved. Here, we quantify the impacts of OP biases on carbon and radiative forcing budgets for a sub-boreal wetland. Comparison with a reference closed-path (CP) system indicates that a systematic OP flux bias (0.54μmolm−2s−1) persists for all seasons leading to a 110% overestimate of the ecosystem CO2 sink (cumulative error of 78 gC m−2). Two potential OP bias sources are considered: Sensor-path heat exchange (SPHE) and analyzer temperature sensitivity. We examined potential OP correction approaches including: i) Fast temperature measurements within the measurement path and sensor surfaces; ii) Previously published parameterizations; and iii) Optimization algorithms. The measurements revealed year-round average temperature and heat flux gradients of 2.9 °C and 16 W m−2 between the bottom sensor surfaces and atmosphere, indicating SPHE-induced OP bias. However, measured SPHE correlated poorly with the observed differences between OP and CP CO2 fluxes. While previously proposed nominally universal corrections for SPHE reduced the cumulative OP bias, they led to either systematic under-correction (by 38.1 gC m−2) or to systematic over-correction (by 17-37 gC m−2). The resulting budget errors exceeded CP random uncertainty and change the sign of the overall carbon and radiative forcing budgets. Analysis of OP calibration residuals as a function of temperature revealed a sensitivity of 5μmolm−3K−1. This temperature sensitivity causes CO2 calibration errors proportional to sample air fluctuations that can offset the observed growing season flux bias by 50%. Consequently, we call for a new OP correction framework that characterizes SPHE- and temperature-induced CO2 measurement errors.

Variation of volcanic gas composition at a poorly accessible volcano: Sakurajima, Japan

Volcanic gas compositions are estimated based on volcanic plume measurement with Multi-GAS at a frequently erupting Sakurajima volcano by application of airborne methods and automatic monitoring station on the flank during 2013–2019. The airborne measurements of CO2 and H2O concentrations often suffer from large fluctuation of background likely due to entrainment of the atmosphere derived from different altitude. By removing the background effect, a representative volcanic CO2/SO2 mole ratio is estimated as 0.4 ± 0.1 and we did not observe clear temporal variation. The volcanic H2O/SO2 ratios are estimated as 30–70 with a large uncertainty because of the strong atmospheric perturbation. The SO2/H2S ratios show quite a large variation ranging from 1 to 800. The large SO2/H2S ratios larger than 30 are observed during ash eruption and are suggested as a result of oxidation by atmosphere on hot ashes. The small ratios less than 10 are observed when frequency of explosions is low. Variation of the SO2/H2S ratios of the small values can be caused by variation of degassing pressure, however, the small variation of the CO2/SO2 ratio suggests a limited range of the pressure variation.

Application of planar optodes to measure CO2 gradients in the rhizosphere of unsaturated soils

Soil respiration is tightly linked to rhizosphere processes, which are characterized by high spatial variability. We tested whether planar optodes can be applied to capture this spatial variability of CO2 in the rhizosphere. Maize (Zea mays) was grown in rhizoboxes and CO2 concentration around roots was measured at three volumetric soil water contents (VWC) using planar optodes. Gradients of CO2 were clearly visible around root tips but less pronounced around mature root parts probably due to high root respiration and microbial activity around tips. Saturating the soil from 21% VWC increased the measured CO2 concentration from 0.23 to 1.47 μmol CO2 L−1. Statistical comparisons between VWC levels indicated that small changes in soil WC might strongly affect CO2 measurements. However, provided that the soil moisture is kept constant, optode measurements of CO2 can be used in moist soil samples to quantify relative differences in CO2 concentration between treatments or soil regions.

CFD analysis for evaluating and optimizing spatial distribution of CO2 concentration in a strawberry greenhouse under different CO2 enrichment methods

A deeper understanding of the spatial distribution of CO2 concentration inside cultivation facilities (e.g., greenhouses and plant factories) is necessary for the quantitative evaluation and/or the improvement in the performance and efficiency of artificial CO2 enrichment methods. We developed 3D computational fluid dynamics (CFD) models for two CO2 enrichment methods in a strawberry greenhouse – one was for overall greenhouse enrichment, as the usual method, and the other was for localized crop enrichment. We confirmed the model validation by comparing the simulated and measured CO2 concentrations in the greenhouse. With regard to the entire enrichment condition, CO2 accumulated at the upper part of the greenhouse through convection due to the high temperature of CO2 generated while there was low CO2 concentration around the crops. This could be regarded as an ineffectual situation. However, such situation can be alleviated by lowering the temperature of CO2. On the other hand, we found that crop-local enrichment can increase CO2 concentration only around crops albeit with less effect on those at the upper part. Thus, changing the enrichment strategy as well as the equipment could greatly optimize the distribution of CO2 in a greenhouse, thereby improving the efficiency of CO2 enrichment.

Using long-term measurements of airflow, electrical power, indoor temperature, and CO2-concentration for evaluating sizing and performance of an all-air HVAC system in an office building - a case study

Monitoring performance of heating, ventilation, and air-conditioning (HVAC) during building operation enables to evaluate the appropriateness of the system’s design. Such insights can help to reduce energy consumption while ensuring satisfying indoor conditions in the monitored building. Additionally, such insight can help to improve future HVAC design. The aim of this paper is to present a case study demonstrating how HVAC engineers can evaluate whether the monitored air-handling units (AHUs) were appropriately sized and performed as intended based on design requirements regarding energy-efficiency, thermal conditions, and indoor air quality (IAQ). Three months of measurements of airflow, electrical power, indoor temperature, and CO2-concentrations were collected from an office building with six AHUs. The results showed that three of the AHUs were appropriately sized and satisfied the thermal condition, IAQ and energy-efficiency requirements. The remaining three AHUs were apparently appropriately sized and satisfied IAQ requirements, but they did not satisfy the required energy-efficiency and thermal conditions. The applied approach seemed to be suitable for supporting building operating managers for on-going performance monitoring as it was able to identify discrepancies from intended performance. But it remains the task for the operating personnel to identify the cause of the identified discrepancies.

Industrial application of apodized gas sensor for on-line and in situ measurement of CO and CO2 concentration

The performance of an apodized gas sensor is demonstrated through simultaneous detection of CO and CO2 absorption lines around 1.57 µm in the recuperator channel of a gas-fired industrial furnace at Shahid Montazeri power plant (SMPP) industry. This led to the concentration measurement of targeted molecules as less than ~ 1% and 9.5%, respectively, at atmospheric pressure and 350 °C, indicating close consistency with the reference data reported by SMPP. A minimum detectable absorption of ~ 0.4 × 10−3, corresponding to a detection sensitivity of ~ 4.8 × 10−9 cm−1 Hz−1/2 is measured in this application.