Ultraviolet Differential Optical Absorption Research Articles

Detection of ultra-low concentration NH3, SO2, and NO using UV-DOAS combined with multidimensional spectral fusion

Since nitric oxide (NO), sulfur dioxide (SO2), and ammonia (NH3) in flue gas cause severe air pollution, accurate measurements of their concentrations are crucial for optimizing the efficiency of flue gas denitrification in coal-fired power plants and protecting the atmosphere. Due to their large absorption cross sections in the ultraviolet (UV) band, NH3, SO2, and NO in flue gas can be detected by UV Differential Optical Absorption Spectroscopy (UV-DOAS) techniques. However, spectral overlap and noise caused by short optical path limitations in the measurement are the main obstacles to achieve concentration inversion. Here, we propose a multidimensional spectral fusion method one-dimensional convolutional neural network combined with two-dimensional convolutional neural network (1D-2D-CNN) with the ability to invert concentration of NH3, SO2 and NO at ppb level with 0.5 m optical-length. To separate the absorption features, one-dimensional spectra are converted into two-dimensional time-frequency plots by continuous wavelet transform (CWT). After denoising the spectra by wavelet thresholding, one-dimensional and two-dimensional spectral features are extracted by 1D-2D-CNN model and fused for inversion. The experimental results show that the proposed system can effectively eliminate interferences from NH3, SO2, and NO, significantly improving the concentration inversion accuracy. The detection limits for NH3, SO2 and NO in the mixture are 0.95 ppb∙m, 6.31 ppb∙m, and 2.53 ppb∙m, respectively, demonstrating that our approach outperforms other reported methods for flue gas analysis. The proposed system is expected to be applied to ammonia slip monitoring of Selective Catalytic Reduction (SCR) in power plants.

Ppb-Level Ammonia Sensor for Exhaled Breath Diagnosis Based on UV-DOAS Combined with Spectral Reconstruction Fitting Neural Network.

Ammonia (NH3) in exhaled breath (EB) has been a biomarker for kidney function, and accurate measurement of NH3 is essential for early screening of kidney disease. In this work, we report an optical sensor that combines ultraviolet differential optical absorption spectroscopy (UV-DOAS) and spectral reconstruction fitting neural network (SRFNN) for detecting NH3 in EB. UV-DOAS is introduced to eliminate interference from slow change absorption in the EB spectrum while spectral reconstruction fitting is proposed for the first time to map the original spectra onto the sine function spectra by the principle of least absolute deviations. The sine function spectra are then fitted by the least-squares method to eliminate noise signals and the interference of exhaled nitric oxide. Finally, the neural network is built to enable the detection of NH3 in EB at parts per billion (ppb) level. The laboratory results show that the detection range is 9.50-12425.82 ppb, the mean absolute percentage error (MAPE) is 0.83%, and the detection accuracy is 0.42%. Experimental results prove that the sensor can detect breath NH3 and identify EB in simulated patients and healthy people. Our sensor will serve as a new and effective system for detecting breath NH3 with high accuracy and stability in the medical field.

An ultra-sensitive optical H2S sensor based on thermal conversion combined with UV-DOAS: Dynamic detection from ppm to ppb level

Hydrogen sulfide (H2S) as a common gas plays an important role in both industrial production and clinical pathology. Therefore, the realization of dynamic detection of trace H2S gas is of great significance. In this paper, an ultra-sensitive optical H2S sensor based on thermal conversion and ultraviolet differential optical absorption spectroscopy (UV-DOAS) is developed for dynamic measurement of H2S concentration. The H2S concentration can be derived from the measurement of the change in sulfur dioxide (SO2) concentration before and after conversion. First, the evaluation method of SO2 concentration based on UV-DOAS is presented, and the performance indicators of SO2 concentration measurement are given. Second, the conversion characteristics of H2S under different temperatures and flow rates are investigated, and H2S can be efficiently converted to SO2 in the flowing gas state by controlling the conversion conditions. Finally, the performance indicators of H2S sensor are evaluated. The sensor realizes H2S measurements with a detection limit of 14 ppb * m, while its sensitivity and reliability of measuring H2S concentration increase tenfold, making it suitable for dynamic measurements of trace H2S. In addition, the feasibility of the sensor for applications in atmospheric monitoring and human exhaled breath detection is demonstrated by practical tests.

Application of bi-directional long short-term memory in separating NO and SO2 ultraviolet differential absorption spectrum signals

To safeguard the environment, it is crucial to monitor the emissions of nitrogen oxide (NO) and sulfur dioxide (SO2), harmful pollutants generated during fossil fuel combustion in industries. However, accurately measuring ultra-low concentrations of SO2 and NO remains a challenge. In this study, we developed an optical measurement system based on ultraviolet differential optical absorption spectroscopy (UV-DOAS) to address this issue. The 200–230 nm cross-sensitivity band was chosen for SO2 and NO. Experimental data with a mixed gas concentration range of 1–25 ppm for SO2 and NO was utilized. We proposed a fast algorithm based on Bi-directional Long Short-Term Memory (Bi-LSTM) to extract the differential optical density, overcoming the mutual interference between SO2 and NO. A nonlinear calibration model was employed to invert the separated differential absorption spectra and determine the gas concentrations. The results demonstrated a detection limit (DL) of 0.27 ppm and a full-scale error of 3.15 % for SO2, while for NO, the DL was 0.32 ppm and the full-scale error was 2.81 %. The uncertainties in SO2 and NO detection were calculated as 1.73 % and 1.96 %, respectively.

Ultrasensitive Online NO Sensor Based on a Distributed Parallel Self-Regulating Neural Network and Ultraviolet Differential Optical Absorption Spectroscopy for Exhaled Breath Diagnosis.

The concentration of fractional exhaled nitric oxide (FeNO) is closely related to human respiratory inflammation, and the detection of its concentration plays a key role in aiding diagnosing inflammatory airway diseases. In this paper, we report a gas sensor system based on a distributed parallel self-regulating neural network (DPSRNN) model combined with ultraviolet differential optical absorption spectroscopy for detecting ppb-level FeNO concentrations. The noise signals in the spectrum are eliminated by discrete wavelet transform. The DPSRNN model is then built based on the separated multipeak characteristic absorption structure of the UV absorption spectrum of NO. Furthermore, a distributed parallel network structure is built based on each absorption feature region, which is given self-regulating weights and finally trained by a unified model structure. The final self-regulating weights obtained by the model indicate that each absorption feature region contributes a different weight to the concentration prediction. Compared with the regular convolutional neural network model structure, the proposed model has better performance by considering the effect of separated characteristic absorptions in the spectrum on the concentration and breaking the habit of bringing the spectrum as a whole into the model training in previous related studies. Lab-based results show that the sensor system can stably achieve high-precision detection of NO (2.59-750.66 ppb) with a mean absolute error of 0.17 ppb and a measurement accuracy of 0.84%, which is the best result to date. More interestingly, the proposed sensor system is capable of achieving high-precision online detection of FeNO, as confirmed by the exhaled breath analysis.

A ppb-level online detection system for gas concentrations in CS2/SO2 mixtures based on UV-DOAS combined with VMD-CNN-TL model

Carbon disulfide (CS2) and sulfur dioxide (SO2) are the main decomposition products of sulfur hexafluoride (SF6). Detecting the concentrations of these products plays a key role in early fault warning in SF6 electrical equipment. In this study, we report an online ppb-level detection system for a mixture of CS2 and SO2 based on ultraviolet differential optical absorption spectroscopy (UV-DOAS) combined with VMD-CNN-TL model. First, important features are extracted and recombined from the differential absorption spectra by variational modal decomposition (VMD) to obtain the combined differential absorption spectra (CDAS) data and mixed-gas differential absorption spectra (MDAS) data. A multilayer 1D convolutional neural network (CNN) model is then pre-trained on CDAS. Next, the parameters of the model are fine-tuned using transfer learning (TL) based on MDAS. TL solves the small sample size problem in detecting mixed-gas concentrations using neural network models. Lab-based results indicate that the system enables stable detection of CS2 (3.81–179.24 ppb) and SO2 (19.21–942.73 ppb) with mean absolute errors of 0.51 ppb and 1.12 ppb, respectively, which are the best results reported so far. Furthermore, the feasibility of the sensor system is verified for detection of gas mixtures at ppb-level by field testing.

Combined direct-sun ultraviolet and infrared spectroscopies at Popocatépetl volcano (Mexico)

Volcanic plume composition is strongly influenced by both changes in magmatic systems and plume-atmosphere interactions. Understanding the degassing mechanisms controlling the type of volcanic activity implies deciphering the contributions of magmatic gases reaching the surface and their posterior chemical transformations in contact with the atmosphere. Remote sensing techniques based on direct solar absorption spectroscopy provide valuable information about most of the emitted magmatic gases but also on gas species formed and converted within the plumes. In this study, we explore the procedures, performances and benefits of combining two direct solar absorption techniques, high resolution Fourier Transform Infrared Spectroscopy (FTIR) and Ultraviolet Differential Optical Absorption Spectroscopy (UV-DOAS), to observe the composition changes in the Popocatépetl’s plume with high temporal resolution. The SO2 vertical columns obtained from three instruments (DOAS, high resolution FTIR and Pandora) were found similar (median difference <12%) after their intercalibration. We combined them to determine with high temporal resolution the different hydrogen halide and halogen species to sulfur ratios (HF/SO2, BrO/SO2, HCl/SO2, SiF4/SO2, detection limit of HBr/SO2) and HCl/BrO in the Popocatépetl’s plume over a 2.5-years period (2017 to mid-2019). BrO/SO2, BrO/HCl, and HCl/SO2 ratios were found in the range of (0.63 ± 0.06 to 1.14 ± 0.20) × 10−4, (2.6 ± 0.5 to 6.9 ± 2.6) × 10−4, and 0.08 ± 0.01 to 0.21 ± 0.01 respectively, while the SiF4/SO2 and HF/SO2 ratios were found fairly constant at (1.56 ± 0.25) × 10−3 and 0.049 ± 0.001. We especially focused on the full growth/destruction cycle of the most voluminous lava dome of the period that took place between February and April 2019. A decrease of the HCl/SO2 ratio was observed with the decrease of the extrusive activity. Furthermore, the short-term variability of BrO/SO2 is measured for the first time at Popocatépetl volcano together with HCl/SO2, revealing different behaviors with respect to the volcanic activity. More generally, providing such temporally resolved and near-real-time time series of both primary and secondary volcanic gaseous species is critical for the management of volcanic emergencies, as well as for the understanding of the volcanic degassing processes and their impact on the atmospheric chemistry.

Study on the concentration retrieval of SO2 and NO2 in mixed gases based on the improved DOAS method.

NO2 and SO2 are important components of air pollutants, and their absorption spectra are superimposed at 193-253 nm. The superposed spectra affect the gas concentration retrieval based on the ultraviolet differential optical absorption spectroscopy (DOAS) method. In this study, a suitable wavelength band was chosen for concentration retrieval, moreover, the characteristics of the quasi-periodic variation of absorption cross-section with wavelength was given sufficient attention and then the superposed spectra were separated by the Fast Fourier transform (FFT) method. The concentration of the gases to be measured was calculated according to the relationship between the amplitude of absorbance after FFT and the gas concentration. The experimental results prove that by using an absorption cell with a 700 mm optical path, the relative deviation absolute value of the retrieval concentration of SO2 in a NO2 and SO2 gas mixture is less than 1.471%, and that of NO2 in a NO2 and SO2 gas mixture is less than 7.207%. The method has good adaptability, high detection precision, whether single SO2, NO2 or a mixture of both, and important reference value for the development of DOAS and future research on the high-precision detection of more types of mixed gases in the ultraviolet band, such as gas mixtures of NO2, SO2 and NO in flue gas.

Quantification of C5-PFK Gas Mixture Based on Ultraviolet Differential Optical Absorption Spectroscopy (UV-DOAS)

C5 perfluoroketone (C5-PFK) has recently attracted attention as an ecofriendly gas insulating medium. Its concentration plays a key role in the dielectric strength of the gas mixture. Currently, there is no relevant detection method for C5-PFK concentration for engineering applications. Herein, we explore the spectral absorption curve of the C5-PFK molecule based on the density functional theory (DFT). A quantitative detection technology for C5-PFK concentration using ultraviolet differential optical absorption spectroscopy (UV-DOAS) is proposed for the first time. The calibration curve determined by the standard concentration of C5-PFK gas demonstrated high linearity with a linear determination coefficient (<inline-formula> <tex-math notation="LaTeX">${R}^{{2}}$ </tex-math></inline-formula>) above 0.9999. We also find that with this technique, the relative error of the concentration of C5-PFK in the gas mixture prepared by the Dalton partial pressure method, and that of the calibration curve, which can reach 8.1&#x0025;, can be determined. With the gas supplement and detection method proposed in this study, the accuracy of the partial pressure method is similar to that of the gravimetric method. The results of this article could guide the rapid preparation of the C5-PFK gas mixture and the online monitoring of C5-PFK concentration changes in engineering applications.

Optical Path Optimal Length for Ultraviolet Ammonia Detection With a Compact and Flexible Gas-Absorption Cell

A flexible and detachable gas-absorption cell with variable optical path length was designed to obtain the optical path optimal length for gas detection based on ultraviolet differential optical absorption spectroscopy. A model of the gas-absorption cell structure was established based on Lambert-Beer law. This model demonstrates the effect of different optical path lengths on ammonia detection, and the optical path optimal length of the proposed system is 1.6 m. A gas detection system was developed with the proposed gas-absorption cell, and the feasibility and stability of the system were evaluated at different ammonia concentrations. Owing to the influence of light loss induced by spherical concave mirror reflection and ammonia absorption, the detection results for ammonia at a concentration of 17 ppm are more accurate when the optical path length is 1.6 m versus 0.8 and 2.4 m. The error is less than 0.6% that is consistent with the simulation results. When the optical path length is 1.6 m, the linearity between the detection and the standard values reaches 0.9993. The standard deviation of the detection results is less than 0.3 ppm, indicating good stability of the system. The minimum detection limit of 0.43 ppm per meter is achieved. Water has a slight influence on the results of ammonia concentration detection. When the relative humidity is 7.5%, the response time of the system is 120 s that becomes longer with the increase of relative humidity. This method can be used to detect other gases with high precision.

Temperature-compensated ppb-level sulfur dioxide detection system based on fourier transform ultraviolet differential optical absorption spectrum method

Sulfur dioxide (SO2) is a toxic gas which poses a great threat on environmental protection and human health even at low concentration. Hence, considerable attention has been devoted to achieve accurate SO2 monitoring at ppb level. In this work, we report on a ppb-level SO2 detection system via deep ultraviolet differential optical absorption spectroscopy (DUV-DOAS). A novel concentration-retrieval algorithm and spectral data-processing method were proposed to overcome the ubiquitous cross-sensitivity. The differential optical density (DOD) signal of SO2 component was identified and decomposed by FFT (fast Fourier transform) from overall DOD signal of gas mixture, followed by a reconstruction by IFFT (Inverse fast Fourier transform) after frequency domain filtering. Via this method, SO2 DOD signal was accurately extracted regardless of strong interference from NO, NO2 and NH3, indicating a remarkably enhanced SO2 selectivity. Besides, a detection limit (DL) of 4 ppb and a quantitation limit (QL) of 20 ppb were achieved, which are among the best cases of related reports thus far. Moreover, a compensation model was offered to compensate for deviations caused by gas temperature variation and thus enhance the system accuracy and adaptability.

An ultra-sensitive detection system for sulfur dioxide and nitric oxide based on improved differential optical absorption spectroscopy method.

A highly sensitive detection system for sulfur dioxide (SO2) and nitric oxide (NO) was developed via deep ultraviolet differential optical absorption spectroscopy (DUV-DOAS). The wavelength range of 200-230nm was used which was rarely used before as result of severe cross sensitivity to SO2 and NO, in this work, this problem was overcame. A system detection limit (DL) of 60ppb for SO2 has been reached which was among the best ones. Meanwhile, a novel method based on spectrum superposition theory was proposed to decompose the differential optical density (DOD) of NO from that of gas mixture in cross sensitive band. The advantage of this method is that the most sensitive absorption peak of NO was used, which cannot be used by conventional methods due to the cross sensitive to SO2. A system DL of 7ppb for NO has been achieved which is among the best ones reported before. Furthermore, the effect of gas temperature and humidity on concentration retrieval has also been studied, gas temperature and humidity compensation models have also been proposed. The experimental results show that the compensation models succeed in compensating the deviation caused by gas temperature and humidity. The environmental adaptability of the system has been enhanced. This work achieves the aim of monitoring ultra-low concentration of SO2 and NO in a complex environment simultaneously.

Quantitative detection of trace H2S based on ultraviolet differential optical absorption spectroscopy

As an important decomposition component of SF6, H2S can provide an important information for the evaluation of insulation state of SF6 gas insulated equipment. Since H2S has obvious absorption in the ultraviolet (UV) range of 190∼230 nm, the UV absorption spectrum detection platform is established to realize its detection. In this paper, SF6 decomposition component detection platform based on UV spectroscopy was built, and the UV absorption spectrum of H2S was obtained. Since the UV absorption spectrum directly obtained by the instrument is susceptible to spectral scattering and high frequency noise, the detection sensitivity is low. Therefore, this paper uses the UV differential algorithm to obtain the UV absorption spectrum of H2S. After experimental tests, the R2 of the fitted line is as high as 0.999. Moreover, the method has good repeatability for detection of H2S, the results show that the absolute error does not exceed 0.2 μL/L. The noise is calculated by randomly collecting 30 sets background spectrum, and the detection limit is 0.590 μL/L when the signal-to-noise ratio is 1. A method for detecting H2S gas concentration based on UV differential absorption spectroscopy is proposed, which is suitable for on-line monitoring of trace H2S in the decomposition components of SF6 gas insulated equipment.

Quantitative analysis of SO2, H2S and CS2 mixed gases based on ultraviolet differential absorption spectrometry.

SO2, H2S and CS2 are the decomposition components of insulating gas SF6. The detection of these gases is significant for the online monitoring and fault diagnosis of SF6 electrical equipment. In this study, an ultraviolet differential optical absorption spectrometry (UV-DOAS) platform for detecting the concentration of SO2, H2S and CS2 mixed gases was established and a quantitatively detecting method was proposed. Firstly, the concentration of SO2 was calculated by the spectrum data at 300 nm band. Then the gas mixture spectra of H2S and CS2 at 200 nm band were obtained after linear deduction of SO2 spectrum. By wavelet extraction and fourier transform, the spectral information of H2S and CS2 was separated and the concentrations of the two gases were calculated. The method can detect the concentrations of SO2 (1-20 ppm), H2S (1-20 ppm) and CS2 (0.01-2 ppm) ternary gas mixture and the detection limits of SO2, H2S and CS2 are 0.44 ppm, 0.49 ppm and 3.23 ppb. This method has good detection sensitivity and high detection precision, which is suitable for the on-line monitoring of SF6 gas insulated equipment.

Detection of Ozone and Nitric Oxide in Decomposition Products of Air-Insulated Switchgear Using Ultraviolet Differential Optical Absorption Spectroscopy (UV-DOAS).

Air-insulated switchgear cabinets play a role in the protection and control of the modern power grid, and partial discharge (PD) switchgear is a long-term process in the non-normal operation of one of the situations; thus, condition monitoring of the switchgear is important. The air-insulated switchgear during PD enables the decomposition of air components, namely, O3 and NO. A set of experimental platforms was designed on the basis of the principle of ultraviolet differential optical absorption spectroscopy (UV-DOAS) to detect O3 and NO concentrations in air-insulated switchgear. Differential absorption algorithm and wavelet transform were used to extract effective absorption spectra; a linear relationship between O3 and NO concentrations and absorption spectrum data were established. O3 detection linearity was up to 0.9992 and the detection limit was at 3.76 ppm. NO detection linearity was up to 0.9990 and the detection limit was at 0.64 ppm. Results indicate that detection platform is suitable for detecting trace O3 and NO gases produced by PD of the air-insulated switchgear.

Ultraviolet differential optical absorption spectrometry: quantitative analysis of the CS2 produced by SF6 decomposition

The occurrence of partial discharge or partial overthermal fault in sulfur hexafluoride (SF6)-insulated electrical equipment frequently causes SF6 and solid insulation materials to decompose into various products. One of the most characteristic products of this process is carbon disulfide (CS2). The internal fault type and severity of the fault in the insulation equipment can be detected through the accurate quantitative detection of CS2. A device for simultaneously determining and quantifying gaseous CS2 via ultraviolet differential optical absorption spectrometry is developed in this study. A Sym14 wavelet transform and fast Fourier transform (FFT) are applied to process the spectral data of the feature regions, namely 190 nm to 210 nm. The concentration of CS2 is determined, and the detection limit of the developed device is identified. A good linear relationship is observed between the characteristic peaks of FFT and the concentration of CS2 after the operational parameters are optimized. Along the light path at 600 mm, the average detection limit for CS2 is 8.65 ppb based on three times the standard deviation of the system noises. The proposed device, which exhibits high sensitivity and effective cost, addresses the urgent demand for the monitoring and diagnosis of SF6-insulated electrical equipment via online detection of trace CS2.

South Philadelphia passive sampler and sensor study

ABSTRACTFrom June 2013 to March 2015, in total 41 passive sampler deployments of 2 wk duration each were conducted at 17 sites in South Philadelphia, PA, with results for benzene discussed here. Complementary time-resolved measurements with lower cost prototype fenceline sensors and an open-path ultraviolet differential optical absorption spectrometer were also conducted. Minimum passive sampler benzene concentrations for each sampling period ranged from 0.08 ppbv to 0.65 ppbv, with a mean of 0.25 ppbv, and were negatively correlated with ambient temperature (–0.01 ppbv/°C, R2 = 0.68). Co-deployed duplicate passive sampler pairs (N = 609) demonstrated good precision with an average and maximum percent difference of 1.5% and 34%, respectively. A group of passive samplers located within 50 m of a refinery fenceline had a study mean benzene concentration of 1.22 ppbv, whereas a group of samplers located in communities >1 km distant from facilities had a mean of 0.29 ppbv. The difference in the means of these groups was statistically significant at the 95% confidence level (p < 0.001). A decreasing gradient in benzene concentrations moving away from the facilities was observed, as was a significant period-to-period variation. The highest recorded 2-wk average benzene concentration for the fenceline group was 3.11 ppbv. During this period, time-resolved data from the prototype sensors and the open-path spectrometer detected a benzene signal from the west on one day in particular, with the highest 5-min path-averaged benzene concentration measured at 24 ppbv.Implications: Using a variation of EPA’s passive sampler refinery fenceline monitoring method, coupled with time-resolved measurements, a multiyear study in South Philadelphia informed benzene concentrations near facilities and in communities. The combination of measurement strategies can assist facilities in identification and mitigation of emissions from fugitive sources and improve information on air quality complex air sheds.

Optical methods for monitoring harmful gas in animal facilities

Animal facilities produce large amounts of harmful gases such as ammonia, hydrogen sulfide, and methane, many of which have a pungent odor. The harmful gases produced by animal housing not only affect the health of people and livestock but also pollute the air. The detection of the harmful gases can effectively improve efficiency of livestock production and reduce environmental pollution. More and more optical detection methods are applied to the detection of the harmful gases produced by animal housing. This summarizes optical detection methods for monitoring the harmful gases in animal housing recently, including nondispersive infrared gas analyzer, ultraviolet differential optical absorption spectroscopy, Fourier transform infrared spectroscopy, and tunable diode laser absorption spectroscopy. The basic principle and the characteristics of these methods are illustrated and the applications on the detection of harmful gases in animal housing are described. Meanwhile, the research of harmful gases monitoring for livestock production based on these methods were listed. The current situation and future development of the detection methods for harmful gases generated by animal housing were summarized by comparing the advantages and disadvantages of each method.

煤质硫含量紫外差分吸收测量方法研究

煤质硫含量紫外差分吸收测量方法研究

Real-time monitoring of benzene, toluene, and p-xylene in a photoreaction chamber with a tunable mid-infrared laser and ultraviolet differential optical absorption spectroscopy

We describe the implementation of a mid-infrared laser-based trace gas sensor with a photoreaction chamber, used for reproducing chemical transformations of benzene, toluene, and p-xylene (BTX) gases that may occur in the atmosphere. The system performance was assessed in the presence of photoreaction products including aerosol particles. A mid-infrared external cavity quantum cascade laser (EC-QCL)-tunable from 9.41-9.88 μm (1012-1063 cm(-1))-was used to monitor gas phase concentrations of BTX simultaneously and in real time during chemical processing of these compounds with hydroxyl radicals in a photoreaction chamber. Results are compared to concurrent measurements using ultraviolet differential optical absorption spectroscopy (UV DOAS). The EC-QCL based system provides quantitation limits of approximately 200, 200, and 600 parts in 10(9) (ppb) for benzene, toluene, and p-xylene, respectively, which represents a significant improvement over our previous work with this laser system. Correspondingly, we observe the best agreement between the EC-QCL measurements and the UV DOAS measurements with benzene, followed by toluene, then p-xylene. Although BTX gas-detection limits are not as low for the EC-QCL system as for UV DOAS, an unidentified by-product of the photoreactions was observed with the EC-QCL, but not with the UV DOAS system.