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Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fire poses a significant risk to the safety, health, and property of people around the world. However, traditional ‘‘point sensor’’ fire detection techniques for indoor buildings based on air particles, air temperatures, and smoke have a low sensitivity, long response time, and poor stability. Therefore, video-based fire detection has become a particularly efficient and important method for detecting the early signs of a fire. Due to image blur, low illumination, flame-like interference and other factors, there is a certain error rate of fire recognition using video flame recognition methods. According to our previous study of a multi-feature flame recognition algorithm, a novel flame recognition algorithm based on free radical emission spectroscopy during combustion is investigated in this paper. First, multiple features are extracted from the video images by employing our proposed processing scheme. Then, the features are post-processed by a temporal smoothing algorithm to eliminate the error recognition rate, which is caused by the similar characteristics of objects between flame-like and real flame areas. In the temporal smoothing experiments, the proposed method achieves the true positive rates of 0.965 and 0.937 for butane flames and forest fire, respectively. Additionally, the spectral signals of OH, CH, C2 and other free radicals in the combustion objects were acquired by the spectrometer. The vibrational temperature and rotational temperature are calculated after identification of the A2Δ → X2Π transition of the CH (410-440 nm). The flames-like are completely rejected by the proposed method in the validation experiment. In the subsequent butane combustion experiment, the vibrational temperature of the butane was 4896 K, and the rotational temperature was 2290 K. The experimental results show that real fires can be precisely recognized and that the combustion temperature can be determined from the CH emission spectroscopy. This novel method provides a new viewpoint for fire detection and recognition. [ABSTRACT FROM AUTHOR]

In the original version of this article, the second author's first name was misspelled as Zhipeng. The correct spelling is Zipeng. The sixth author's first name was misspelled as Jirong. The correct spelling is Jinrong. The correct version is as follows: LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project Pengfei LIN1,4, Zipeng YU1,4, Hailong LIU1,4, Yongqiang YU1,4, Yiwen LI1,4, Jinrong JIANG2, Wei XUE3, Kangjun CHEN1, Qian YANG1,4, Bowen ZHAO1,4, Jilin WEI1,4, Mengrong DING1,4, Zhikuo SUN1,4, Yaqi WANG1,4, Yao MENG1,4, Weipeng ZHENG1,4, and Jinfeng MA11LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China 2Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China 3Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China 4College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China In the section "Data availability statement" on page 248 of the original version of this article, the URL of the data should be https://esgf-node.llnl.gov/projects/cmip6. [ABSTRACT FROM AUTHOR]

In Traditional Chinese Medicine (TCM), moisture content (MC) inspection using voltage level or a lock-in amplifier, with a features-based near-infrared light-emitting diode sensor is possible. Abundant absorption response in a wide frequency range and information in both the time-domain and frequency-domain can be obtained, with the square excitation method. However, planeness, heterogeneous particle sizes, and measurement noise negatively affect the time-domain feature during MC inspection. In this work, spectrum analysis (SA) for feature extraction is investigated, to precisely measure the MC of Dutong pills. The principal components for low and high frequencies, are aimed at counteracting the dimensional methods, which are used for supplying the lower dimensional features. The SA experimental results demonstrate that the low frequency components, ranging from the base to the 3rd harmonic components, have a high linear correlation with the MC. The calibration and validation experimental results reveal that the MC can be a monotonic function about the SA amplitudes or first principal component (PC1), with the proposed sensor. This method has the potential to be used for gauging automatic, in situ MCs, particularly for quality control and Process Analytical Technology in TCM. Future research opportunities include improving accuracy and application of the method under field conditions. [ABSTRACT FROM AUTHOR]

The selective catalytic reduction and non-selective catalytic reduction (SCR/SNCR) are the most popular de-NOx processes for coal-fired power plant, where the real-time temperature is a significant parameter. A new developed tunable diode laser spectroscopy used for measuring the temperature of ammonia (NH3) in the process of SCR/SNCR influenced by strong exhaust gas matrices CO2 and H2O was presented in this paper. Two lines near 6605 cm−1 were selected, with rather weak temperature dependency and minimal interface from CO2 and H2O according to HITRAN12 database. A homemade heating equipment for high temperature laser spectroscopy measurement was developed based on an ARM microcontroller. The temperature calibration experiments of absorption lines were carried out at variable concentrations under different temperatures. The spectral signals of 2.5%, 3.5% and 4.5% NH3 were observed for validation of the generalization and robustness of the sensor. The calibration and validation experimental results show that the maximum measurement error and global average error of the temperature sensor with the temperature ranging from 453 to 653 K are less than 2% and 1.38%, respectively. It demonstrates that our proposed sensor with high accuracy and linearity, and can be utilized to measure the temperature in SNCR/SCR process. [ABSTRACT FROM AUTHOR]

Tunable diode laser absorption spectroscopy (TDLAS) is an important technique for trace gas detection. The sensitivity of TDLAS system, especially for multi-pass absorption, is usually limited by optical fringes. It is an effective approach to suppressing optical fringes of spectral lines using digital filtering. The parameters derived from filtering simulations are key factors and they are related to the noise characteristic. In the paper, the precise Airy functions were used to simulate optical interference and the interference signal was effectively minimized by the wavelet transforms. The root-mean-square error and the residual standard deviation are introduced to quantify the suppression ratio of etalon fringes. It is demonstrated that the optimum wavelet function in denoising the observed CO2 lines is fk18, in comparison with haar, db02, coif1 etc. In addition, the absorption signals recorded by direct absorption spectroscopy and wavelength modulation spectroscopy at second-harmonic (WMS-2f) with a 10 m White-type cell were subjected to low-pass, averaging and fk18 wavelet filtering, respectively. The results show that only wavelet transform is capable of suppressing optical interference noise. The detection limit of WMS-2f can reach 7 ppm and the perfect calibration curves between signal intensity and gas concentration are obtained after wavelet filtering. To further demonstrate the feasibility of the approach, spectral signals at different pressures and temperatures were acquired and the etalon interference is substantially eliminated by fk18 wavelet at 13th level of decomposition. [ABSTRACT FROM AUTHOR]