Real-Time Monitoring of SO₂ Emissions Using a UV Camera with Built-in NO₂ and Aerosol Corrections

Abstract

Nitrogen dioxide (NO₂) absorption correction of the sulfur dioxide (SO₂) camera was demonstrated for the first time. The key to improving the measurement accuracy is to combine a differential optical absorption spectroscopy (DOAS) instrument with the SO₂ camera for the real-time NO₂ absorption correction and aerosol scattering correction. This method performs NO₂ absorption correction by the correlation between the NO₂ column density measurement of the DOAS and the NO₂ optical depth of the corresponding channel from the SO₂ camera at a narrow wavelength window around 310 and 310 nm. The error of correction method is estimated through comparison with only using the second channel of the traditional SO₂ camera to correct for aerosol scattering and it can be reduced by 11.3% after NO₂ absorption corrections. We validate the correction method through experiments and demonstrate it to be of greatly improved accuracy. The result shows that the ultraviolet (UV) SO₂ camera system with NO₂ absorption corrections appears to have great application prospects as a technology for visualized real-time monitoring of SO₂ emissions.

1. Introduction

Emissions of polluting gases from industries and ships have brought severe air pollution, particularly in developed and coastal areas. Atmospheric pollutants from industries and ships are mainly generated from fuel combustion. The main product of combustion includes sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon dioxide (CO₂), and particles [1,2,3]. SO₂ is of special importance and interest. As a toxic gas, SO₂ is responsible for many deleterious effects on human health, the environment, and the climate. SO₂ emissions contribute to the formation of sulfate aerosols and small particles, which may penetrate deeply into the lungs, and, in sufficient quantity, can contribute to health problems. Increased SO₂ in the Earth’s atmosphere can alter the radiation balance by intercepting scattered light. However, its far distance and low concentration make SO₂ emissions difficult to measure by using the existing techniques.

The existing optical techniques for SO₂ concentration measurements are an effective tool for high concentrations or fixed sources or near distances. Raman scattering lidar and differential absorption lidar are active detection methods [4,5] that can realize stereoscopic detection of pollutant space and have distance resolution capability. However, their spatial resolution is low and cannot meet the requirements of portable and mobile applications. For the sake of portability and engineering, passive detection methods have emerged. Fourier transform infrared spectroscopy and Fourier function analysis are characterized by multi-component analysis, wide measurement range, and fast analysis speed [6,7,8]. Differential optical absorption spectroscopy (DOAS) provides fast response and real-time monitoring to characterize and obtain data [9,10,11]. Recent advancements in spectroscopic techniques allow remote analysis of many species. Non-imaging measurement techniques allow us to measure the total column density of the trace gas along a single direction within the plume. Imaging DOAS (I-DOAS) combines the advantages of DOAS with imaging capabilities [12,13]. This technique allows the spectroscopic measurement of 2D pollutant gas distributions and improves the accuracy of quantitative measurement. A drawback of scanning DOAS systems is a relatively long time to acquire a 2D image of the trace gas distribution.

The development of remote sensing techniques based on a novel ultraviolet (UV) SO₂ camera system [14] for trace gas measurement has emerged. The SO₂ camera is increasingly used in SO₂ emission due to its ability to remotely measure the 2D distribution of SO₂ path concentrations in space and the emission rate over time in real-time. The measurement of 2D SO₂ distribution in volcanic plumes has been realized by using a single UV camera. UV cameras have been increasingly established [15,16]. The University of Heidelberg discussed the theoretical basis of UV cameras and calibration issues, including the measurement principle, data evaluation, and solar zenith angle [17]. They used the 3D backward Monte Carlo radiative transfer model to describe the spectral radiance transmitted through the filter [18]. Christoph Kern et al. used seven different UV cameras and four different filters to continuously monitor the volcanic plumes in real-time [19]. Osorio, M et al. proposed a new two-image method (2-IM) to acquire background images and quantify SO₂ emissions from industrial sources [20]. However, UV cameras are mostly used to measure higher concentrations of SO₂ emissions from volcanic sources. Few measurements of emissions with low concentrations from industries and ships have been performed with UV cameras. Some persistent problems may arise when UV camera systems are used to measure the SO₂ emissions of industrial and ship sources.

UV SO₂ cameras are used to measure the SO₂ absorption in a narrow wavelength (310 nm), and the effect of aerosol scattering can be partially corrected by measuring the weak absorption of SO₂ around 330 nm. The measured signal is the integral intensity of the incident spectrum over the filter transmittance window. SO₂ cameras are certainly limited by the fact that only one trace gas can be measured and the other spectral interferences and the effect of aerosol scattering on the particulate matter can potentially lead to an inaccurate measurement.

This work aims to correct NO₂ absorption for real-time measurement of SO₂ emissions with UV cameras. This proposed method performs NO₂ absorption correction by the correlation between the NO₂ column density measurement of the DOAS and the NO₂ optical depth of the corresponding channel from the SO₂ camera at a narrow wavelength window around 310 and 310 nm. Theoretical simulation analysis shows that different NO₂ column densities have a relatively large influence on the error of SO₂ column density measured by the UV camera. In this paper, we briefly described the theoretical basis for pertinent aspects of spectral consideration. The basic principles of UV SO₂ camera methodology and the simulation of error analysis are described. The main experimental results are obtained from a plant in Wuhan. In order to further enhance the measurement accuracy, the Mie scattering corrections are made. The following discusses the measurement uncertainty of SO₂ column density. Then, we show the SO₂ error on NO₂ absorption corrections.

2. Spectral Consideration

When scattered solar radiation passes through industrial and ship emission plumes, light is scattered and absorbed along the path. This condition is caused by absorption within the band due to other gases (such as NO₂, O₃), scattering of particles, and multiple scattering. In the UV region, the O₃ absorption [blue line in Figure 1a] blocks part of the scattered solar spectra and the UV cannot break through the ozone at a wavelength shorter than 300 nm. In Figure 1a (red line), the relative scattered solar spectral intensity reaches the ground at a spectral resolution of 0.1 nm, which is calculated on MODTRAN [21]. The UV cameras are used to measure the SO₂ emissions in a narrow wavelength band centered at 310 nm, which is the region of the scattered solar spectral intensity with an increasing magnitude as the wavelength increases. The spectral interference from other major emission products (such as NO₂) should be considered for measuring SO₂ emissions. The measurement of SO₂ emission from industries and ships cannot be ignored due to the extremely high NO₂ absorption interference. Figure 1b shows the SO₂ absorption spectrum (blue line) and NO₂ absorption spectrum (red line) in the spectral range of 280–360 nm.

As shown in Figure 1b, the absorption band of SO₂ overlaps with the absorption band of NO₂, and the absorption cross-sections of SO₂ and NO₂ are comparable in the chosen spectral window. We calculated the SO₂ column density (CD) error caused by the interference of NO₂ absorption. In accordance with the Beer–Lambert law to resolve the SO₂ signal, the signal channel and the reference channel can be expressed as:

$$I({\lambda }_{on},{\lambda }_{off})=I_0({\lambda }_{on})\cdot exp\left[-({\sigma }_{S{O}_2}({\lambda }_{on},{\lambda }_{off})\cdot S_{S{O}_2})-({\sigma }_{N{O}_2}({\lambda }_{on},{\lambda }_{off})\cdot S_{N{O}_2})-{\tau }_{Mie}({\lambda }_{on},{\lambda }_{off})\right]$$

(1)

where the incident spectral radiation intensity $I$ and radiation intensity $I_0$ are the intensity images after and before traversing the plume at wavelength $\lambda$, ${\sigma }_{S{O}_2}({\lambda }_{on})$ is the absorption cross-section of SO₂, $S_{S{O}_2}$ is the SO₂ CD or the integral of SO₂ concentration along the effective optical path, ${\sigma }_{N{O}_2}({\lambda }_{on})$ is the absorption cross-section of NO₂, and $S_{N{O}_2}$ is its CD. ${\tau }_{S{O}_2}$ is the apparent absorbance, which is the difference between the optical depth (OD) for ${\lambda }_{on}$ and ${\lambda }_{off}$. No aerosols are assumed to be present in the emission plume. We obtain an expression for the SO₂ optical depth:

$${\tau }_{S{O}_2}={\tau }_{310}-{\tau }_{330}=\ln \left(\frac{I({\lambda }_{on})}{I_0({\lambda }_{on})}\right)-k_{N{O}_2}\cdot \ln \left(\frac{I({\lambda }_{off})}{I_0({\lambda }_{off})}\right)$$

(2)

where ${\kappa }_{N{O}_2}={\tau }_{N{O}_2}({\lambda }_{on})/{\tau }_{N{O}_2}({\lambda }_{off})={\sigma }_{N{O}_2}({\lambda }_{on})/{\sigma }_{N{O}_2}({\lambda }_{off})$ is the ratio between the integral of NO₂ absorption cross-section at two region wavelengths of narrow-band filters. In this work, ${\lambda }_{on}$ is 310 nm, and ${\lambda }_{off}$ is 330 nm with narrow-band filters in the center wavelength.

Figure 2 shows the simulated SO₂ CD measurement error under the influence of NO₂ CD. With the significant increase in NO₂ CD towards high concentration, the signal channel (${\lambda }_{on}$) SO₂ OD is particularly influenced by the NO₂ CD. This error is the main source for measuring SO₂ emissions. It is important to eliminate the influence of NO₂ absorption in the plume.

Figure 2b shows the calculated error varying with the NO₂ CD at different SO₂ CDs. The error is approximately the monotone function of NO₂ CD, and the relation between them is particularly affected by the NO₂ CD. The error clearly increases with the increase in NO₂ CD. Therefore, the error of measuring SO₂ CD can be effectively eliminated if the ratio of the two NO₂ ODs of two channels is known.

3. Methodology

3.1. Experiment Instrument

To verify the accuracy of the theoretical analysis and simulation, we used SO₂ cameras to acquire images of SO₂ emissions from the plant near Wuhan on 16 July 2021. The SO₂ camera system is shown in Figure 3. Figure 3a shows a photograph of the SO₂ camera system and the DOAS system. The main part of the instrument (see green dotted line area in Figure 3a) is the DOAS system, a lens, and spectrometer-connected fiber. As well as two cameras (blue dotted line area in Figure 3a), each with a lens and a bandpass filter (310 nm and 330 nm). From outside the plant, we can observe one stack from which SO₂ emissions are monitored (red dotted line area in Figure 3a). Figure 3b shows a schematic diagram of the SO₂ camera system (correspond to the blue dotted line in Figure 3a). The SO₂ cameras (Prime 95B Blue) used for these experiments have the most sensitive scientific back-illuminated CMOS sensor (1200 × 1200 pixels, 11 μm × 11 μm pixel size) manufactured by Photometrics (Tucson, AZ, USA). The quantum efficiency of approximately 50–55% at 310 and 330 nm of each SO₂ camera is high from 200–1000 nm. The UV lens (UV1054B) of 105 mm focal length (Universe Kogaku America Inc., Oyster Bay, NY, USA) with a total field of view (FOV) of 9.8° and F-number of 4.0 were mounted in front of each camera. Two UV narrow-band filters (ASAHI SPECTRA, Torrance, CA, USA), with a central wavelength of 310 (XBPA310) and 330 nm (XBPA330) and full width at half maximum of 10 nm, were used for the measurements. Two narrow-band filters were mounted between the lens and the cameras. This setup was chosen to reduce the influences from the illumination angle. Two cameras were fixed side by side to simultaneously capture the current polluting gases of industrial emissions by using a function generator (Tektronix AFG 3022B, Beaverton, OR, USA) with a frequency of 1–5 Hz. For comparison, a DOAS system was installed on the two UV cameras. The DOAS system consisted of an Ocean Optics Maya (Dunedin, FL, USA) 2000Pro spectrometer with a spectral range between 247 and 390 nm and a resolution of 0.035 nm, a 600 μm optical fiber, and a telescope with the same quartz lens as the UV camera.

The SO₂ camera system is portable. The location (approximately 500 m from the plant through a laser rangefinder) was chosen to be as close as possible to the plant plume emissions (red dotted line area in Figure 3a) to reduce light dilution effects. The exposure times (approximately 0.1 s for 310 nm and 0.06 s for 330 nm) were used to acquire images at approximately 50–60% of the intensity saturation level. The camera with a 310 nm narrow-band filter required long exposure times due to the low intensity of solar radiation. The UV cameras and DOAS system were controlled through panning and tilting. The exposure time of the camera system should be multiple times, especially for the measurement of industrial emissions, to overcome the mechanical complexity of the camera system and the influence of the zenith angle. The images were captured with acquisition rates of 5 Hz, with an additional collection of dark images prior to the capturing of plume sequences. The acquisition and subtraction of a dark frame are required to correct the dark current and electronic noise on the UV camera system. Figure 4a,b shows a pair of the raw images (${\lambda }_{on}$ and ${\lambda }_{off}$) of an industrial plume. The raw images were processed following the protocols, which are already described in the literature [20], including the subtraction of a dark current and image matching. Simultaneously, the background sky images (${\lambda }_{on}$ and ${\lambda }_{off}$) of the plume can be constructed from the raw plume images by plume segmentation and interpolation. Figure 4c,d shows a pair of the generated artificial background sky images (${\lambda }_{on}$ and ${\lambda }_{off}$) resulting from the 2-IM method.

The measurement accuracy of the SO₂ CD from industrial emissions is affected by the NO₂ absorption. Industrial emissions were measured when the plume entered the camera FOV within the plant. The camera system can be calibrated by using the real-time continuous calibration method of Wu [22,23]. In the particular case of assuming the absence of aerosols in the plume, the SO₂ CD density from industrial emissions obtained from the real-time continuous calibration method is shown in Figure 5. Figure 5a shows the SO₂ image ignoring the effect of NO₂ absorption, and Figure 5b shows the SO₂ image using the second channel to correct the NO₂ absorption. Ignoring the NO₂ absorption leads to an overestimation of the emissions.

3.2. Mie Scattering Corrections

As illustrated in Figure 5, the effect of NO₂ absorption can lead to an inaccurate SO₂ image measurement. The result of the SO₂ image obtained by the two methods differed twice. This finding may be the result of the NO₂ absorption correction based on the use of a second channel. However, when scattered solar radiation reaches a camera after passing through a plume from a stack, it contains several trace gases (SO₂ and NO₂) and aerosol. Assuming that aerosol scattering is independent of wavelength, the second channel of the traditional camera is mostly used to correct plume aerosols in the stack. Therefore, a second channel is used to correct the aerosol or NO₂ absorption. Although a second channel certainly reduces the influence of aerosol scattering and NO₂ absorption on SO₂ camera measurements, it does not completely remove it. This condition is a limitation of the SO₂ camera. However, this problem can be overcome by correcting NO₂ absorption and aerosol scattering. The OD of SO₂ by applying two band-pass filters can be expressed as:

$${\tau }_{S{O}_2}={\tau }_{310}-{\tau }_{330}=\left(\ln \frac{I({\lambda }_{on})}{I_0({\lambda }_{on})}-{\tau }_{N{O}_2}({\lambda }_{on})\right)-{\kappa }_{Mie}\cdot \left(\ln \frac{I({\lambda }_{off})}{I_0({\lambda }_{off})}-{\tau }_{N{O}_2}({\lambda }_{off})\right)$$

(3)

where ${\kappa }_{Mie}={\tau }_{Mie}({\lambda }_{on})/{\tau }_{Mie}({\lambda }_{off})={({\lambda }_{on}/{\lambda }_{off})}^{-\alpha }$ is the ratio between the scattering cross-section at two different wavelengths ${\lambda }_{on}$ and ${\lambda }_{off}$. ${\tau }_{Mie}({\lambda }_{on})$ and ${\tau }_{Mie}({\lambda }_{off})$ are the plume aerosol ODs (AODs). Data analysis was conducted and is summarized in Figure 6.

For two band-pass filters, correcting the effects of NO₂ absorption and aerosol scattering at the same time is impossible. The corresponding signal channel (${\lambda }_{on}$) and the corresponding reference channel (${\lambda }_{off}$) are influenced by NO₂ absorption and aerosol scattering. Here, the spectral data were analyzed by using DOAS to obtain the NO₂ CD. The two cameras simultaneously capture the plume with the same FOV, and the spectrometer measures the spectral information of the plume area with the same FOV of the camera. This process was to accurately determine the area in which the DOAS optical FOV is directed and obtains the best correlation between the corresponding channel NO₂ OD from the SO₂ camera and the NO₂ CD measured by DOAS. Using Equation (1), the relationship between the column density of NO₂ and the optical density ${\tau }_{N{O}_2}$ is obtained. Figure 7 shows the calculated relationship curve between the signal and reference channel NO₂ CD of the SO₂ cameras and the NO₂ OD. The signal channel (red line) and the reference channel (blue line) NO₂ OD of the SO₂ cameras are derived from the NO₂ CD measurement by DOAS. The NO₂ CD is converted to NO₂ OD by multiplying with the factor obtained from the relationship curve. The subtraction of the NO₂ OD is required to correct the NO₂ absorption in the two channels. Figure 8b shows the concentration image of the SO₂ plume obtained by UV cameras with the NO₂ absorption and aerosol scattering considered. For comparison, Figure 8a shows the SO₂ CD from UV cameras with only aerosol scattering considered. A second channel is used to correct the plume aerosols because the SO₂ CD is underestimated because of the presence of NO₂ absorption in the plumes. Therefore, this method using DOAS with the SO₂ camera makes the real-time NO₂ absorption correction. The accuracy of this method is significantly improved by the NO₂ absorption correction.

The accuracy of the SO₂ CD depends on the difference between the NO₂ OD measured by DOAS and the NO₂ OD of the corresponding channels on the SO₂ camera. Simultaneously, it can be found that only using the second channel from the SO₂ camera to correct for aerosol scattering results in an underestimation of the SO₂ measurement. However, this method is practical for emission plume monitoring from industrial sources and ships, especially for SO₂ CD measurement with NO₂ absorption correction.

4. SO₂ CD Error

The error measured by the SO₂ camera is an extremely important quantity for accuracy. The measurement uncertainty of the SO₂ CD can be determined through propagation of error analysis. The dominant sources of uncertainty during the measurements are the system error ($\Delta S_1$, uncertainty of 11.3%) and the random error ($\Delta S_2$, uncertainty of 7.48%). The SO₂ CD error $\Delta S$ can be expressed as:

$$\Delta S=\sqrt{{(\frac{\partial S}{\partial S_1}\cdot \Delta S_1)}^2+{(\frac{\partial S}{\partial S_2}\cdot \Delta S_2)}^2}$$

(4)

The absorption in the second channel is due to NO₂ and aerosols. However, the correction procedure for the second channel is only used to correct for plume aerosols. The influence of NO₂ absorption on SO₂ camera measurements is not completely removed. The system error of the SO₂ CD measurement is calculated under the influence of NO₂ CD. The random error of SO₂ CD is derived from light intensities $I({\lambda }_{on})$, $I_0({\lambda }_{on})$, $I({\lambda }_{off})$, and $I_0({\lambda }_{off})$, which are referred to as the apparent quantities. The random error of the SO₂ OD $\Delta {\tau }_{S{O}_2}$ is obtained from the relation.

$$\Delta {\tau }_{S{O}_2}=\sqrt{{(\frac{\partial \tau }{\partial I({\lambda }_{on})}\cdot \Delta I({\lambda }_{on}))}^2+{(\frac{\partial \tau }{\partial I_0({\lambda }_{on})}\cdot \Delta I_0({\lambda }_{on}))}^2+{(\frac{\partial \tau }{\partial I({\lambda }_{off})}\cdot \Delta I({\lambda }_{off}))}^2+{(\frac{\partial \tau }{\partial I_0({\lambda }_{off})}\cdot \Delta I_0({\lambda }_{off}))}^2}$$

(5)

where $\partial \tau /\partial I({\lambda }_{on})$, $\partial \tau /\partial I_0({\lambda }_{on})$, $\partial \tau /\partial I({\lambda }_{off})$, and $\partial \tau /\partial I_0({\lambda }_{off})$ represent the polarization of OD to light intensity, and $\Delta I$ is the amount of change in light intensity. The random errors of the SO₂ OD are due to: (1) photon noise, which can be reduced by combining pixels. This precision can be improved to approximately twice by averaging 4 adjacent pixels and reducing the image size to 0.25 pixels. (2) the light dilution effect and the main source of the random error on UV SO₂ camera measurements is related to the scattering of ambient photons [24].

The time series of the error of the SO₂ CD corrected for aerosol scattering using the second channel of the UV SO₂ camera is shown in Figure 9. The error of the SO₂ CD is under 14%. The variation of SO₂ CD error is mostly due to the change of NO₂ CD in the SO₂ emission plume.

5. Conclusions

In this work, we first put forward an SO₂ camera for the real-time NO₂ absorption corrections to improve the measurement accuracy of SO₂ emissions. The instrument was designed with NO₂ absorption corrections and aerosol scattering corrections to improve the accuracy of the SO₂ CD. The theoretical analysis for the spectral interference of industrial SO₂ emissions is given in detail, and the error of NO₂ absorption interference is simulated. The UV SO₂ camera system with NO₂ absorption corrections is developed to measure the SO₂ CD of an industrial plume in Wuhan, and a series of experimental results are obtained to verify the accuracy of this theoretical analysis. The 2-IM method is utilized to obtain the artificial background sky images, SO₂ CD, and the error of the SO₂ CD. The traditional camera system only used the second channel to correct the interference of aerosol scattering, which underestimates the SO₂ emissions due to the interference of NO₂ absorption in the plume. We compare the experimental results with and without the effect of NO₂ absorption correction. The SO₂ CD errors between them are effectively reduced by 11.3% after NO₂ absorption corrections. Therefore, an effective means to improve the accuracy of the SO₂ CD is to combine the UV SO₂ cameras and a spectrometer to measure the plume at the same time, which can effectively overcome the interference of NO₂ absorption and aerosol scattering. This new method can provide a good temporal resolution for real-time NO₂ absorption corrections, especially for measuring the plumes from industries and ships. This promising method may greatly improve the measurement accuracy of SO₂ emissions and provide the most convenient option for rapid measurements of industrial and ship SO₂ emissions in the foreseeable future.