Stack Monitoring Research Articles

Assessment of the Spatial Distribution of Water Quality for Surface and Groundwater at Bonny Island, Nigeria

The aim of the study was to assess the spatial distribution of water quality for surface and ground water at Bonny Island in Rivers State, Nigeria. Surface and Groundwater samples were collected from 9 sampling locations and analyzed for physicochemical parameters, heavy metals, and petroleum hydrocarbons. The contaminants in the surface and groundwater were measured using a variety of methods. Heavy metals in the water were measured using gas chromatography, PAHs were measured using Atomic Absorption Spectrophotometry (ASS) while THC were measured using HACH DR/890 colorimeter. The water quality index (WQI) was calculated using the Weighted Arithmetic Index Method while Principal Component Analysis was used to understand the distribution of the physicochemical parameters, heavy metals, and petroleum hydrocarbons. The results showed that the WQI for both surface and groundwater samples ranged from 55.22 – 125.39, indicating poor to unfit water quality for consumption. In contrast, a control location away from the industrial activities had good water quality with WQI between 35.19 and 45.77. Principal component analysis revealed that the surface water in the industrial area were contaminated with lead, Poly Aromatic Hydrocarbon (PAHs), Total Petroleum Hydrocarbon which indicate oil and gas activities. High chloride, nitrate and sulphate levels were also observed in surface water close to the NLNG plant. Limiting further contamination of the surface and groundwater can be achieved by constant effluent and plume stack monitoring by regulatory agencies. Industrial stakeholder should set up subsidized clinics to provide treatment for any gastrointestinal illnesses or renal damage suffered by residents.

Using MQTT and Node-RED to monitor the ATLAS Meta-data Interface (AMI) stack and define metadata aggregation tasks in a pipelined way

ATLAS Metadata Interface (AMI) is a generic ecosystem for metadata aggregation, transformation and cataloging. Each sub-system of the stack has recently been improved in order to acquire messaging/telemetry capabilities. This paper describes the whole stack monitoring with the Message Queuing Telemetry Transport (MQTT) protocol and Node-RED, a tool for wiring together hardware/software devices. Finally, this paper shows how Node-RED is used to graphically define metadata aggregation tasks, in a pipelined way, without introducing any single point of failure.

Tar cracking enhancement by air sparger installation in the combustion zone of the downdraft gasifier

In the present article, experimental studies are performed on Imbert downdraft gasifier using two different air distribution systems (two-nozzle and air-sparger) for the combustion zone. A novel air distribution system (air-sparger) is designed to supply uniform air across the combustion zone for achieving uniform temperature and enhancing the tar cracking. The effect of operating parameters (Equivalence ratio, temperature, air flow rate, and biomass consumption) on the tar cracking and producer gas compositions are investigated. Tar is measured in the producer gas before and after the gas cleaning units using a stack monitoring system. The experiments are performed by varying the airflow rate between 3 and 7 Nm3 h−1, and the equivalence ratio varies from 0.24 to 0.38. The operating parameters and air-sparger have significantly influenced the zone's temperature, producer gas composition, and the tar content in the producer gas. The maximum temperature of the combustion zone and reduction zone increases from 764 to 975 °C and 467 to 760 °C respectively with the air-sparger compared to the two-nozzle conventional air distribution system at the airflow rate of 7 Nm3 h−1. The lower heating value of the producer gas and the cold gas efficiency of the gasifier increased from 4.28 to 4.37 MJ Nm−3 and 48.55–55.05%, respectively, with the air-sparger. The incorporation of air-sparger reduces tar in producer gas from 23.95 to 0.97 g Nm−3 before gas cleaning unit at the airflow rate of 7 Nm3 h−1. Air-sparger has shown the adequate potential to enhance tar cracking and improve the overall gasifier performance.

Source Term Analysis of Xenon (STAX): An effort focused on differentiating man-made isotope production from nuclear explosions via stack monitoring

An overview of the hardware and software developed for the Source Term Analysis of Xenon (STAX) project is presented which includes the data collection from two stack monitoring systems installed at medical isotope production facilities, infrastructure to transfer data to a central repository, and methods for sharing data from the repository with users. STAX is an experiment to collect radioxenon emission data from industrial nuclear facilities with the goal of developing a better understanding of the global radioxenon background and the effect industrial radioxenon releases have on nuclear explosion monitoring. A final goal of this work is to utilize collected data along with atmospheric transport modeling to calculate the contribution of a peak or set of peaks detected by the International Monitoring System (IMS) to provide desired discriminating information to the International Data Centre (IDC) and National Data Centers (NDCs). Types of data received from the STAX equipment are shown and collected data was used for a case study to predict radioxenon concentrations at two IMS stations closest to the Institute for RadioElements (IRE) in Belgium. The initial evaluation of results indicate that the data is very valuable to the nuclear explosion monitoring community.

Airborne estimation of SO2 emissions rates from a coal-fired power plant using two top-down methods: A mass balance model and Gaussian footprint approach

In this study, two top-down methods—mass balance and Gaussian footprint—were used to determine SO2 emissions rates via three airborne sampling studies over Korea's largest coal power plant in October 2019 and 2020. During the first two flights in October 2019, mass balance approaches significantly underestimated the SO2 emissions rates by 75 % and 28 %, respectively, as obtained from the real-time stack monitoring system. Notably, this large discrepancy accounted for the insufficient number of transects altitudes and high levels of background SO2 along the upwind side. Alternatively, the estimated SO2 emissions rates of the third flight (October 2020) displayed a difference of <10 % from rea-time monitoring data (630 vs. 690 kg·hr−1), owing to the enhanced vertical resolution with increased transects and lower background SO2 levels. In contrast to the mass balance method, Gaussian footprints offered significantly improved accuracy (relative error: 41 %, 32 %, and 2 % for Flights 1, 2, and 3, respectively). This relatively good performance was attributed to prior emissions knowledge via the Clean Air Policy Support System (CAPSS) emissions inventory and its unique ability to accurately estimate stack-level SO2 emissions rates. Theoretically, the Gaussian footprint was less prone to sparse transects and upwind background levels. However, it can be substantially influenced by atmospheric stability and consequently by effective stack heights and dispersion parameters; basically, all factors with minimal-to-no influence on the mass balance approach. Conversely, the mass balance method was the only plausible approach to estimate unidentified source emissions rates when well-defined prior emission information was unknown. Here, the footprint approach supplemented the mass balance method when the emission inventories were known, and employing both strategies approaches greatly enhanced the integrity of top-down emissions inventories from the power plant sources, thus, supporting their potential for ensuring operational compliance with SO2 emissions regulation.

Air Quality Impact Assessment of a Waste-to-Energy Plant: Modelling Results vs. Monitored Data

The impact of the emissions from a municipal Waste-to-Energy (WtE) plant in Northern Italy on local air quality was assessed using the CALMET-CALPUFF atmospheric dispersion modelling system. Model simulations were based on hourly emission rates measured by continuous stack monitoring systems and considered both air quality-regulated pollutants (nitrogen oxides, particulate matter, toxic elements, benzo(a)pyrene), and other trace pollutants typical of WtE plants (dioxins, furans, and mercury). The model results were compared to both long-term observations from the air quality monitoring network and with short-term measurements from dedicated monitoring campaigns in the vicinity of the WtE plant, in both warm and cold season conditions. Modelling and observational results showed that the estimated plant contributions are very limited. This suggests that the observed concentration levels were the result of the contribution of all the sources distributed over the area and that they were not solely driven by the activity of the plant. Estimated contributions from the plant’s emissions were usually at least two orders of magnitudes lower than the ambient levels at the nearest monitoring site and even lower at the farthest sites.

Experimental Determination of Excitation Function Curves through the Measurement of Thick Target Yields in Liquid Targets: The Examples of the 68Zn(p,n)68Ga and 64Zn(p,α)61Cu Nuclear Reactions

The present work describes a method to determine excitation function curves and, therefore, cross-sections, making use of the irradiation of liquid targets at distinct energies in a biomedical cyclotron. The method relies on the derivative of experimentally measured thick target yield curves to determine the corresponding excitation function curves. The technique is presented as a valid and practical alternative to the commonly used activation method combined with the stack monitor technique, whose implementation in liquid targets offers practical difficulties. The working principle is exemplified by presenting the results obtained for the clinically relevant 68Zn(p,n)68Ga and the 64Zn(p,α)61Cu nuclear reactions, obtained though the irradiation of liquid targets containing dissolved natural zinc.

Clustered Single-Board Devices with Docker Container Big Stream Processing燗rchitecture

The expanding amounts of information created by Internet of Things (IoT) devices places a strain on cloud computing, which is often used for data analysis and storage. This paper investigates a different approach based on edge cloud applications, which involves data filtering and processing before being delivered to a backup cloud environment. This Paper suggest designing and implementing a low cost, low power cluster of Single Board Computers (SBC) for this purpose, reducing the amount of data that must be transmitted elsewhere, using Big Data ideas and technology. An Apache Hadoop and Spark Cluster that was used to run a test application was containerized and deployed using a Raspberry Pi cluster and Docker. To obtain system data and analyze the setup’s performance a Prometheus-based stack monitoring and alerting solution in the cloud based market is employed. This Paper assesses the system’s complexity and demonstrates how containerization can improve fault tolerance and maintenance ease, allowing the suggested solution to be used in industry. An evaluation of the overall performance is presented to highlight the capabilities and limitations of the suggested architecture, taking into consideration the suggested solution’s resource use in respect to device restrictions.

Galvanodynamic Electrochemical Impedance Spectroscopy on a Solid Oxide Cell Stack for In-Operando Diagnostics

Introduction Lifetime expectations and uncertainties regarding end-of-life performance hinder widespread deployment of fuel cell technology. Conventional cell performance diagnostic methodologies rely upon either ex-situ measurements, which lack an immediate connection with the physical degradation phenomena, or upon single cell in-operando electrochemical impedance spectroscopy (EIS), which often is troubled by challenges of feature identification of the spectra and uncomplete representation of the full stack operating conditions in large scale systems [1]. To address these problems, we propose to use electrochemical impedance spectroscopy techniques as diagnostic and prognostic tools to predict the cause-effect relationship between degradation phenomena and stack operating conditions. This experimental methodology can be potentially integrated into commercial systems for stack state of health monitoring during continuous operation. Experimental methods Through experimental study on a solid oxide fuel cell (SOFC) short stack, we explore the potential use of electrochemical impedance spectroscopy (EIS) for in-operando diagnosis. We identify the mechanisms contributing to this system EIS, by carrying out pristine cell/stack tests at different operating conditions (gas partial pressure, current, temperature).We collect experimental data on a 6-cell short-stack with active area of 80 cm2 per cell. Each anode-supported cell features a Ni-YSZ fuel electrode (240 μm), a Sr-doped LaMnO3 (LSM) oxygen electrode (40 μm) and an 8 mol% Y2O3 stabilized Zirconia (YSZ) electrolyte (8 μm). In our experimental setup, the first (reference electrode, i.e., cathode of cell no.1) and last (i.e., anode of cell no.6) electrodes are connected to the counter and working electrode leads of the potentiostat, respectively. This allows connecting the diagnostic system in parallel with the load and the stack, while performing floating ground galvanodynamic EIS measurements. This configuration enables the load to impose the operating current of the stack, while the potentiostat modulates the signal without any current in its main circuit. Reference and working sensing connections to individual cells in the stack are independent on the potentiostat leads.We operate the stack with mixtures of hydrogen, nitrogen and steam at the fuel electrode and mixtures of oxygen and nitrogen/helium at the oxygen electrode. We control the operating temperature via an electric furnace, while monitoring the stack temperatures with a set of six thermocouples, as reported in [2]. Discussion Figure 1 compares the measured EIS spectra for each cell in the short stack at beginning of life and after a major degrading event. With continuous stack monitoring, we are able to identify how degradation phenomena differently impact the state of health of the cells during the stack normal operation. This allows identifying the most degrading operating conditions of the system in real-time, hence informing the operational planning and lifetime maximization strategies of the system. Conclusions Preliminary results suggest that our methodology can provide meaningful insights regarding the cause and nature of the physical processes at the origin of degradation phenomena in solid oxide cells. This process is particularly interesting as a non-disruptive diagnostic and prognostic tool for commercial scale systems that need to optimize their operating conditions to either maximize their lifetime or meet a performance target at end-of-life.Figure 1 – (left) Beginning of life and (right) degraded cell plot comparison of experimental EIS for a 6-cell short stack at 1 A. Tstack=750°C, Anode flow=1.2 Nl min-1 (N2/H2=50/50%), Cathode flow=18.9 Nl min-1 (Air)[1] A. Baldinelli, L. Barelli, G. Bidini, A. Di Cicco, R. Gunnella, M. Minicucci, A. Trapananti, 2019, p. 020012.[2] L. Mastropasqua, S. Campanari, J. Brouwer, J. Power Sources 2017, 371, 225–237. Figure 1

New safe reliable design methodologies examined by fault injection testing and Monte Carlo simulation: tolerating shared-memory interferences in multicore architectures

Nowadays, the automotive industry utilises multicore processors to meet autonomous driving requirements. This imposes a higher complexity on the development and the verification of software applications. Compliance to the ISO 26262 safety standard increases this complexity. In this paper, means of shared-memory interferences that affect Automotive Safety Integrity Level (ASIL)-D multicore architectures have been addressed. This work proposes new safety mechanisms to detect and react to systematic and random transient memory faults as follows: 1) an enhanced software partitioning design pattern; 2) a new methodology on the memory protection unit; 3) an improved stack monitoring mechanism. New safe and reliable design configurations are introduced. The proposed safety mechanisms have been evaluated for Aurix multicore targets with suggestions to have a fully compliant architecture followed with ISO 26262 methods and principles of tolerating memory interferences. A novel fault injection platform is presented to show the experimental results with a Monte Carlo simulation proof of concept.

Design and implementation of a battery management system for lithium-ion batteries in electric vehicles

The persistent need for eco-friendly and sanitary means of transportation are propelling the use of electric vehicles (EVs). Li-ion batteries, which are far advanced than its counterparts, are widely deployed in EVs. Unfortunately, it can be catastrophic if they are not utilised inside the boundaries set by their safety operation area. Therefore, a battery management system (BMS) is significant to protect the battery from damage, to extend battery life and also to ensure that the battery is ready to be used despite the environmental conditions. The proposed project aims to model an efficient BMS to maximise their performance and efficiency with battery stack monitor LTC6811 for monitoring battery pack, and STM32F303 Cortex M4 microcontroller. The proposed system performs measurement of cell voltage, current, temperature, state of charge, state of health, remaining useful life determination, monitoring and controlling the charge/discharge characteristics and cell balancing.

Spectroscopic noble gas stack monitor with continuous unattended operation and analysis

A spectroscopic stack monitoring system for the measurement of noble gasses discharged from medical isotope production facility and nuclear power plant stacks has been designed and a prototype constructed. The prototype is based on a Marinelli beaker style HPGe measurement operating in a continuous acquisition mode. Continuous acquisition is accomplished with novel software and hardware which allows for unattended acquisition, analysis, and storage of data over multiple workflow definitions. As a direct result of the multiple averaging times and the use of the transistor reset preamplifier, the dynamic range of the system covers nearly 8 orders of magnitude.

Online Total Harmonic Distortion Analysis for Solid Oxide Fuel Cell Stack Monitoring in System Applications

AbstractThe applicability of online total harmonic distortion analysis (THDA) for the operation and monitoring of solid oxide fuel cell (SOFC) power systems is investigated by experiments as well as analysis of the algorithm, with a focus on the relationship between stack fuel utilization rate and the corresponding THD index. An online THDA algorithm is implemented in a programmable logic controller (PLC) and operated with a 6 kW SOFC power system demonstration unit. Laboratory experiments on the solid oxide fuel cell technology are carried out to determine key parameters for the algorithm. The embedded implementation of the THDA algorithm, including several modifications to reduce its computational load, and its parameterization is analyzed and the program code is given in the Appendix. The experimental results verify that THDA can be a reliable means for quantitatively monitoring the fuel utilization rate experienced by the stack and that the algorithm is simple to implement on an embedded controller.

An Assessment of Air Sampling Location for Stack Monitoring in Nuclear Facility

An Assessment of Air Sampling Location for Stack Monitoring in Nuclear Facility

성능이 향상된 Stack Monitoring System의 설계

본 논문에서는 성능이 향상된 Stack Monitoring System을 설계한다. Stack Monitoring System의 증폭기(AMP)에 들어오는 펄스성 잡음을 차단하기 위하여, 차폐 및 전원부 임피던스를 낮추고 전원회로를 분리하여 노이즈를 차단한다. 신틸레이션 검출기 특성을 최대한 장치에 매칭하기 위한 가변 고전압, 이득(Gain), 상쇄(Offset), 한계(Threshold) 등을 설정 할 수 있는 제어부를 설계한다. 또한 300 ~ 1,500V의 가변 고전압 전원회로를 구성하여 다양한 신틸레이션 검출기에 적용가능 한 가변 전압 공급 장치를 설계한다. 성능이 향상된 Stack Monitoring System은 다종의 신틸레이션 검출기가 각각의 특성을 고려하여 동작하게 함으로서 효율적이고 높은 신뢰성을 보장한다. 개발된 Stack Monitoring System의 측정 불확도에 대하여 공인 시험기관의 장비를 사용하여 실험한 결과 우수한 성능을 나타내었다. In this paper, we designed the stack monitoring system with improved performance. To block the incoming pulse noise to the amplifier, shield and the power supply impedance are reduced and the power circuit is isolated. The control unit is developed with variable high voltage, adaptive gain, offset and threshold in order to match the scintillation detector characteristic to the apparatus. 300-1500V variable high voltage power circuit is configured applicable to various scintillation detector. Stack monitoring system with improved performance guarantee the efficiency and the reliability by considering the characteristic of various scintillation detector. Developed stack monitoring system is evaluated with certified testing equipment and shows excellent performance with respect to the uncertainty of the sensor test results.

International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station

The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward. An understanding of natural and man-made radionuclide backgrounds can be used in accordance with the provisions of the treaty (such as event screening criteria in Annex 2 to the Protocol of the Treaty) for the effective implementation of the verification regime.Fission-based production of 99Mo for medical purposes also generates nuisance radioxenon isotopes that are usually vented to the atmosphere. One of the ways to account for the effect emissions from medical isotope production has on radionuclide samples from the IMS is to use stack monitoring data, if they are available, and atmospheric transport modeling. Recently, individuals from seven nations participated in a challenge exercise that used atmospheric transport modeling to predict the time-history of 133Xe concentration measurements at the IMS radionuclide station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice.Some of the models predicted the highest measured concentrations quite well. A model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. None of the submissions based only on the stack monitoring data predicted the small measured concentrations very well. Modeling of sources by other nuclear facilities with smaller releases than medical isotope production facilities may be important in understanding how to discriminate those releases from releases from a nuclear explosion.

Tritium dynamics in soils and plants grown under three irrigation regimes at a tritium processing facility in Canada

The dynamics of tritium released from nuclear facilities as tritiated water (HTO) have been studied extensively with results incorporated into regulatory assessment models. These models typically estimate organically bound tritium (OBT) for calculating public dose as OBT itself is rarely measured. Higher than expected OBT/HTO ratios in plants and soils are an emerging issue that is not well understood. To support the improvement of models, an experimental garden was set up in 2012 at a tritium processing facility in Pembroke, Ontario to characterize the circumstances under which high OBT/HTO ratios may arise. Soils and plants were sampled weekly to coincide with detailed air and stack monitoring. The design included a plot of native grass/soil, contrasted with sod and vegetables grown in barrels with commercial topsoil under natural rain and either low or high tritium irrigation water. Air monitoring indicated that the plume was present infrequently at concentrations of up to about 100 Bq/m3 (the garden was not in a major wind sector). Mean air concentrations during the day on workdays (HTO 10.3 Bq/m3, HT 5.8 Bq/m3) were higher than at other times (0.7–2.6 Bq/m3). Mean Tissue Free Water Tritium (TFWT) in plants and soils and OBT/HTO ratios were only very weakly or not at all correlated with releases on a weekly basis. TFWT was equal in soils and plants and in above and below ground parts of vegetables. OBT/HTO ratios in above ground parts of vegetables were above one when the main source of tritium was from high tritium irrigation water (1.5–1.8). Ratios were below one in below ground parts of vegetables when irrigated with high tritium water (0.4–0.6) and above one in vegetables rain-fed or irrigated with low tritium water (1.3–2.8). In contrast, OBT/HTO ratios were very high (9.0–13.5) when the source of tritium was mainly from the atmosphere. TFWT varied considerably through time as a result of SRBT's operations; OBT/HTO ratios showed no clear temporal pattern in above or below ground plant parts. Native soil after ∼20 years of operations at SRBT had high initial OBT that persisted through the growing season; little OBT formed in garden plot soil during experiments. High OBT in native soil appeared to be a signature of higher past releases at SRBT. This phenomenon was confirmed in soils obtained at another processing facility in Canada with a similar history. The insights into variation in OBT/HTO ratios found here are of regulatory interest and should be incorporated in assessment models to aid in the design of relevant environmental monitoring programs for OBT.

Real-time stack monitoring at the BaTek medical isotope production facility

Radioxenon emissions from fission-based radiopharmaceutical production are a major source of background concentrations affecting the radioxenon detection systems of the international monitoring system (IMS). Collection of real-time emissions data from production facilities makes it possible to screen out some medical isotope signatures from the IMS radioxenon data sets. This paper describes an effort to obtain and analyze real-time stack emissions data with the design, construction and installation of a small stack monitoring system developed by a joint CTBTO-IDC, BATAN, and Pacific Northwest National Laboratory team at the BaTek medical isotope production facility near Jakarta, Indonesia.

Source term estimates of radioxenon released from the BaTek medical isotope production facility using external measured air concentrations

BATAN Teknologi (BaTek) operates an isotope production facility in Serpong, Indonesia that supplies 99mTc for use in medical procedures. Atmospheric releases of 133Xe in the production process at BaTek are known to influence the measurements taken at the closest stations of the radionuclide network of the International Monitoring System (IMS). The purpose of the IMS is to detect evidence of nuclear explosions, including atmospheric releases of radionuclides. The major xenon isotopes released from BaTek are also produced in a nuclear explosion, but the isotopic ratios are different. Knowledge of the magnitude of releases from the isotope production facility helps inform analysts trying to decide if a specific measurement result could have originated from a nuclear explosion. A stack monitor deployed at BaTek in 2013 measured releases to the atmosphere for several isotopes. The facility operates on a weekly cycle, and the stack data for June 15–21, 2013 show a release of 1.84 × 1013 Bq of 133Xe. Concentrations of 133Xe in the air are available at the same time from a xenon sampler located 14 km from BaTek. An optimization process using atmospheric transport modeling and the sampler air concentrations produced a release estimate of 1.88 × 1013 Bq. The same optimization process yielded a release estimate of 1.70 × 1013 Bq for a different week in 2012. The stack release value and the two optimized estimates are all within 10% of each other. Unpublished production data and the release estimate from June 2013 yield a rough annual release estimate of 8 × 1014 Bq of 133Xe in 2014. These multiple lines of evidence cross-validate the stack release estimates and the release estimates based on atmospheric samplers.

Quantitative Determination of Methanol and Ethanol with Synthetic Calibration Spectra in Passive Fourier Transform Infrared Remote Sensing Measurements

A spectral synthesis strategy is introduced to help obtain estimates of path-integrated concentrations in passive Fourier transform infrared (FT-IR) remote sensing measurements conducted during field-monitoring experiments. Obtaining quantitative information from passive infrared data is challenging because of the joint effects of temperature and concentration on spectral intensities. The collection of calibration data for use in modeling spectral intensities for a given set of experimental conditions is also costly and labor intensive. In the work presented here, a radiance model is defined for use in synthesizing calibration spectra that serve as inputs to partial least-squares (PLS) models that relate spectral intensities to path-integrated concentrations. The field data for which quantitative estimates are desired are used to estimate the background temperature associated with a given time and set of experimental conditions. Sample temperatures can be obtained through either experimental measurement or by estimating one calibration release. Given these temperatures, calibration data can be synthesized and the PLS model developed. This methodology is tested with stack monitoring data obtained from controlled releases of pure and mixture samples of heated ethanol and methanol. Experiments were conducted across 6 days with stack temperatures of 150 to 200 °C and with path-integrated concentrations in the range of 10 to 300 parts per million meters. Median relative errors in the estimates of path-integrated concentration were typically in the range of 20% or less, with the best results observed at the higher stack temperatures.