Volatile organic compounds (VOCs) are important precursors of urban secondary organic aerosol (SOA) and ozone (O3) pollution. Industrial parks are important sources for anthropogenic VOCs, with main fugitive emission of characteristic pollutants such as alkanes, alkenes and aromatic hydrocarbons and so on. To effectively control VOCs emission from industrial parks and evaluate the effects of control and treatment, it is necessary to monitor the flux and distribution of VOCs emission. Solar occultation flux (SOF) technique is currently one of the best available techniques for monitoring fugitive emission flux of field VOCs. The principle, method, development and applications of SOF technique are introduced in detail in this review, and the future application of SOF in monitoring VOCs emission flux from industrial parks in China is prospected as well.

A portable coherent lidar system has been developed, which has the advantages of compact structure, small volume, lightweight, and high degree of automation. The overall weight of the system is no more than 15 kg, and the lidar can work using only a battery. The system adopts a fast frequency processing algorithm to improve the processing speed of the Doppler frequency shift, and compared with the traditional processing methods, the processing time of radial wind speed of this system is reduced by three times. The performance of the system has been validated in field experiment, and it shows that the detection height of the system reaches 1.5 km and the detection range of wind speed is 0-50 m/s.

Based on the ground data, wind lidar data, wind profile radar data, and Guangzhou S-band dual polarization radar data from the Guangzhou mega city comprehensive observation experiment in June and July 2019, the WindPrintS4000 wind lidar and wind profile radar were observed and compared, and the detection performance of the wind lidar was comprehensively evaluated and analyzed under different precipitation intensity conditions. The results show that the observation performance of wind lidar and wind profile radar is consistent in non precipitation and non heavy precipitation periods, and can capture the characteristics of low-level wind field changes in the boundary layer during the transit of weather systems. However, compared with other methods,the wind lidar has lower cost, is more convenient and efficient, and is easier to select sites, which is more in line with the needs of dense observation network in mega cities; The detection height ofwind lidar is related to both precipitation and precipitation intensity, but it is more closely related to precipitation intensity. As precipitation intensity increases, the detection height of wind lidar generally shows a downward trend. Moreover, when the reflectivity factor of S-band dual polarization weather radar reaches over 50 dbz intensity of precipitation, wind lidar cannot perform routine observations like wind profile radar.

Uncooled infrared cameras are widely used in the field of gas leak detection due to the advantages of low cost, long life and stable performance. An excellent image denoising algorithm can effectively improve the sensitivity and accuracy of detection. Combining deep learning and transfer learning techniques, an infrared image denoising method for gas leakage based on deep transfer learning is proposed in this work. Firstly, the convolutional neural network model is trained using a static scene dataset. Then some model parameters are fixed, and the model is retrained through simulating the gas dataset. Finally, a model suitable for denoising infrared images of gas leakage is obtained. The experimental results show that the method can denoise gas infrared images captured by uncooled infrared camera. The denoised images have obvious gas profile information, and the location of the leak source can be distinguished at the same time. Therefore, it is believed that the proposed infrared image denoising method can benefit uncooled infrared cameras better accomplish the task of gas leak detection.

To address the problem of continuous and accurate measurement of atmospheric NO2 at night, a nighttime atmospheric NO2 detection system based on target reflection light is developed. The system mainly consists of a transmitting unit and a signal receiving unit, with a 3.5 W high-power semiconductor laser with a central wavelength of 445 nm as its light source, and according to the laser differential absorption characteristics of NO2 in the range of 440-450 nm, the laser detection wavelengths for NO2 are determined to be λon = 444.8 nm and λoff = 446.7 nm. Firstly, the sensitivity of wavelength and intensity of the semiconductor laser to its temperature and current was studied, and the quantitative relationship between the wavelength and intensity of laser and the temperature and current of laser was determined. Then basd on the quantitative relationship, the laser wavelength can be adjusted by controlling the temperature stability of the semiconductor laser while changing the current, and the influence of laser wavelength adjustment on laser intensity changes during the detection process can be eliminated. Finally, based on the constructed system, NO2 sample gas experiments were conducted, and the fitting values of NO2 differential absorption cross section were determined. After the determination of system parameters, field experiments were carried out at Anhui University and Science Island (the campus of Hefei Institutes of Physical Science, Chinese Academy of Sciences) respectively. NO2 nighttime concentration near the ground at two observation points was successfully obtained, and the measurement results were compared with the data from National Environmental Monitoring Station and the data from the long-path differential optical absorption spectroscopy (LP-DOAS) at Science Island respectively. It was found that the observation data of the developed system showed good consistency with the data of National Environmental Monitoring Station and the data of LP-DOAS, with coefficients of determination of 0.902 and 0.891, respectively, verifying the accuracy and reliability of the system. Furthermore, NO2 vertical distribution detection experiments were conducted, and NO2 concentration values at different heights were successfully obtained, proving the feasibility of the developed system in NO2 vertical distribution detection.

Hydrogen cyanide (HCN) is an important product released during cigarette combustion, which seriously endangers human health. However, traditional methods such as gas chromatography are difficult to achieve real-time measurements during the combustion process. In this work, the evolution of released HCN during cigarette combustion is researched by employing laser absorption spectroscopy (TDLAS) technique, where a distributed feedback laser with a central wavelength of 1.53 μm is selected as the light source. In the experimental system, a Herriott multi-path cell is used to increase the effective optical path of the laser, with 35 reflections and 17.5 m effective optical path, At the same time, the embedded system is used to collect and filter the absorption signal of the original demodulation, and finally the HCN concentration is calculated according to the measured spectral signal. In addition, wavelength modulation and demodulation spectroscopy are applied to improve the detection sensitivity and stability of the system. Calibration experiments show that the determination coefficient R2 of HCN is 0.9974 in the concentration range of 0.001%-0.01%. The system continuously monitors 0.002% standard HCN gas for 1000 s, and Allan variance analysis shows that the theoretical detection limit of the system reaches 22 × 10-9 within 55 s integration time, verifying the stability of the detection system. In order to study the evolution of HCN produced under different smoking conditions, experiments are conducted to simulate the release of HCN from cigarette combustion under different sampling flow rates from 100 ml/min to 400 ml/min and oxygen atmosphere of 17%, 22%, 30% and 40%. The results show that the HCN concentration released during cigarette combustion per unit time is positively correlated with sampling flow rate and oxygen concentration, while the total amount of HCN released during the entire combustion process is negatively correlated with oxygen concentration. This work provides a basis for further research on the generation mechanism of cigarettes are burned to produce HCN. and also provides an effective reference for the measurement of HCN and other trace gases in smoke in the near-infrared band.

High sensitivity of ammonia detection from different emission sources can provide certain reference for environmental management and medical diagnosis. However, current ammonia sensors have the disadvantages of weak absorption line of ammonia in the near infrared band, high cost of mid-infrared light source and generally large volume. A photoacoustic sensor based on broadband light source was proposed in this work. For this system, the selected working wavelength is around 2239 nm, where the line intensity of ammonia is 10-20 cm/molecule, which can effectively avoid the interference of CO2 and H2O. The results show that, the resonance frequency of the photoacoustic cell is 1830 Hz, the linear fitting of the measured signals of ammonia with different concentrations can reach 0.98976 under the conditions of room temperature, one atmosphere pressure and optical power of 2.46 mW, indicating the good linear response characteristic of the system, and Allan variance analysis show that the optimal integration time of the system is 100 s. It is shown that the developed sensor can meet the detection requirements of ammonia from different emission sources, and has important reference for realizing high sensitivity detection of ammonia.

The characteristics and meteorological causes of ozone (O3) pollution in Xuancheng City, China, were analyzed based on the ambient air quality monitoring data in 2020 and the meteorological observation data of the same period. The results indicated that the 90th percentile of the maximum daily sliding 8-hour average mass concentration of O3 (MDA8-90) in 2020 was 137 μg/m3, with an increase of 2.2% compared to 2019. The monthly variation of MDA8-90 showed an "M" type, with the peak appearing in September (164 μg/m3). The diurnal variation showed a unimodal pattern, with the peak at 16:00 and the trough at 07:00. Under different weather conditions, the peak value of O3 mass concentration was the highest on sunny days, and decreased sequentially on cloudy, overcast sky and rainy days. O3 mass concentration revealed a positive correlation with temperature and a significant negative correlation with relative humidity and NO2 concentration. Specifically, meteorological conditions with air temperatures > 25 ℃, relative humidity < 50%, and a wind speed < 2 m/s were closely related to high concentrations of O3. In addition, the potential source contribution function model (PSCF) was used to analyze the impact of pollution transport on the O3 mass concentration in Xuancheng and the distribution characteristics of potential transport sources. The results showed that the potential sources of O3 at different stages were significantly different in various periods of the year. The main potential sources of O3 from June to August were distributed in the East China Sea and the northern part of Zhejiang Province, while the main potential sources of O3 from September to November were distributed at the junction of Jiangsu, Anhui, Henan and Shandong, as well as the junction of Jiangxi and Hubei Province.

In order to verify the application effect of surface reflectance data of hyperspectral automatic field observation equipment, the application and verification of in-orbit calibration data of Gaofen-2 (GF-2) satellite remote sensor are carried out based on the reflectance-based method. Firstly, we systematically introduces the calibration field and the working mode and performance index of various automatic observation equipment, and demonstrates the calculation method of observation data and surface reflectance data of the instrument. Then, regarding to the calibration requirements of GF-2 satellite remote sensor, the in-orbit calibration of GF-2 panchromatic and multi-spectral (PMS) remote sensor is completed using satellite atmospheric data products and synchronous observation images of GF-2 remote sensor. Finally, based on the obtained calibration coefficients, the image data of remote sensors in different time periods are verified. The application verification of two different land surfaces shows that, the overall relative deviation of satellite apparent radiance is better than 2%, which verifies the feasibility of hyperspectral equipment in the in-orbit calibration of satellite remote sensors.