Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook.

Observations and numerical models are mainly used to investigate the spatiotemporal distribution and vertical structure characteristics of aerosols to understand aerosol pollution and its effects. However, the limitations of observations and the uncertainties of numerical models bias aerosol calculations and predictions. Data assimilation combines observations and numerical models to improve the accuracy of the initial, analytical fields of models and promote the development of atmospheric aerosol pollution research. Numerous studies have been conducted to integrate multi-source data, such as aerosol optical depth and aerosol extinction coefficient profile, into various chemical transport models using various data assimilation algorithms and have achieved good assimilation results. The definition of data assimilation and the main algorithms will be briefly presented, and the progress of aerosol assimilation according to two types of aerosol data, namely, aerosol optical depth and extinction coefficient, will be presented. The application of vertical aerosol data assimilation, as well as the future trends and challenges of aerosol data assimilation, will be further analysed.

Advances in coastal ocean boundary layer detection technology and equipment in China.

Accurate and comprehensive knowledge of the atmospheric environment and its evolution within the coastal ocean boundary layer are necessary for understanding the sources, chemical mechanisms, and transport processes of air pollution in land, sea, and atmosphere. We present an overview of coastal ocean boundary layer detection technology and equipment in China and summarize the progress and main achievements in recent years. China has developed a series of coastal ocean boundary layer detection technologies, including Light Detection and Ranging (LIDAR), turbulent exchange analyzer, air-sea flux analyzer, stereoscopic remote sensing of air pollutants, and oceanic aerosol detection equipment to address the technical bottleneck caused by harsh environmental conditions in coastal ocean regions. Advances in these technologies and equipment have provided scientific assistance for addressing air pollution issues and understanding land-sea-atmosphere interactions over coastal ocean regions in China. In the future, routine atmospheric observations should cover the coastal ocean boundary layer of China.

Atmospheric environment monitoring technology and equipment in China: A review and outlook.

Accurate monitoring of the atmospheric environment and its evolution are important for understanding the sources, chemical mechanisms, and transport processes of air pollution and carbon emissions in China, and for regulatory and control purposes. This study gives an overview of atmospheric environment monitoring technology and equipment in China and summarizes the major achievements obtained in recent years. China has made great progress in the development of atmospheric environment monitoring technology and equipment with decades of effort. The manufacturing level of atmospheric environment monitoring equipment and the quality of products have steadily improved, and a technical & production system that can meet the requirements of routine monitoring activities has been initiated. It is expected that domestic atmospheric environment monitoring technology and equipment will be able to meet future demands for routine monitoring activities in China and provide scientific assistance for addressing air pollution problems.

Retrieval of weak non-resonant photoacoustic signal with the chaotic oscillator algorithm.

Photoacoustic (PA) spectroscopic technique has become a popular tool for trace gas detection and is especially suitable for in situ measurement of sulfur hexafluoride (SF6) decomposition components in gas insulated switchgear (GIS). However, the concentrations of SF6 decomposition components are generally very low and the resulting PA signals are too weak to be accurately retrieved with traditional methods. In this study, we proposed a Lyapunov exponent based chaotic oscillator algorithm to retrieve the weak PA signals of SF6 decomposition components. Retrieval of weak PA signals from strong noise background was achieved for both simulation and measurement perspectives. The results were compared with those based on phase-locked amplification technique. Both simulation and measurement results concluded that the proposed chaotic oscillator algorithm is superior to the phase-locked amplification in terms of accuracy, sensitivity and stability. Since most trace gases have weak absorption signatures in the atmosphere (below 1%), this study can provide valuable insights in dealt with such weak signals in remote sensing of atmosphere.

Ground-based high-resolution remote sensing of sulphur hexafluoride (SF6) over Hefei, China: characterization, optical misalignment, influence, and variability.

It is a challenge to retrieve atmospheric sulphur hexafluoride (SF6) with high resolution solar spectra because it has only one single retrieval micro window and has interfered with many factors in the retrieval. Optical misalignment is one of the key factors that affect the accuracy of SF6 retrieval. In this study, we first present a long term time series of the SF6 total column over Hefei, China, between January 2017 and December 2020, retrieved by mid-infrared (MIR) solar spectra recorded by ground-based high-resolution Fourier transform infrared spectroscopy (FTIR). The sensitivities of the total column, root mean square of fitting residual (RMS), total error budgets, degrees of freedom for signal (DOFs), and vertical mixing ratio (VMR) profile with respect to different levels of optical misalignment for SF6 retrieval were assessed. The SF6 total column is sensitive to optical misalignment. In order to avoid inconsistencies in the total column due to optical misalignment, we use the true instrumental line shape (ILS) derived from regular low-pressure HBr cell measurements to retrieve the time series of SF6. The total column of SF6 over Hefei presents strong seasonal dependent features. The maximum monthly average value of (3.57 ± 0.21) × 1014 molecules*cm-2 in summer is (7.60 ± 3.50) × 1013 molecules*cm-2 (21.29 ± 9.80) % higher than the minimum monthly average value of (2.81 ± 0.14) × 1014 molecules*cm-2 in winter. The annual average SF6 total columns in 2017-2020 are (3.02 ± 0.17), (3.50 ± 0.18), (3.25 ± 0.18), and (3.08 ± 0.16) × 1014 molecules*cm-2, respectively, which are close to each other. It indicates that SF6 total column over Hefei is stable in the past four years. Our study can improve the current understanding for ground-based high-resolution remote sensing of SF6 and also contribute to generate new reliable remote sensing data in this sparsely monitored region for investigations of climate change, global warming, and air pollution.

Retrieval of vertical profiles and tropospheric CO2 columns based on high-resolution FTIR over Hefei, China.

High-resolution solar absorption spectra, observed by ground-based Fourier Transform Infrared spectroscopy (FTIR), are used to retrieve vertical profiles and partial or total column concentrations of many trace gases. In this study, we present the tropospheric CO2 columns retrieved by mid-infrared solar spectra over Hefei, China. To reduce the influence of stratospheric CO2 cross-dependencies on tropospheric CO2, an a posteriori optimization method based on a simple matrix multiplication is used to correct the tropospheric CO2 profiles and columns. The corrected tropospheric CO2 time series show an obvious annual increase and seasonal variation. The tropospheric CO2 annual increase rate is 2.71 ± 0.36 ppm yr-1, with the annual peak value in January, and CO2 decreases to a minimum in August. Further, the corrected tropospheric CO2 from GEOS-Chem simulations are in good agreement with the coincident FTIR data, with a correlation coefficient between GEOS-chem model and FTS of 0.89. The annual increase rate of XCO2 observed from near-infrared solar absorption spectra is in good agreement with the tropospheric CO2 but the annual seasonal amplitude of XCO2 is only about 1/3 of dry-air averaged mole fractions (DMF) of tropospheric CO2. This is mostly attributed to the seasonal variation of CO2 being mainly dominated by sources near the surface.

Eukaryotic translation initiation factor 3 subunit b is a novel oncogenic factor in prostate cancer.

Prostate cancer, the second most common cancer among male adults, affects millions globally. We sought to investigate the expression and contribution of Eukaryotic translation initiation factor 3 subunit b (EIF3B) in prostate cancer. Expression of EIF3B was analyzed in both human prostate patient tissues and prostate cancer cell lines. Small interfering RNA (siRNA) knockdown of EIF3B was introduced into prostate cancer cell line PC-3 and LNCaP, followed by examination of cell viability, proliferation and apoptosis using the MTT, cell counting and terminal deoxynucleotidyl transferase dUTP nick end labeling assays, respectively. An in vivo xenograft tumor mouse model was employed to address the role of EIF3B in tumorigenesis as well. Finally, a gene microarray analysis was performed to search for differentially expressed genes upon EIF3B knockdown. EIF3B was upregulated in prostate tumor tissues and prostate cancer cell lines. EIF3B knockdown inhibited viability and proliferation of prostate cancer cells, as well as promoted cell apoptosis. In the in vivo mouse model, inoculation of EIF3B knockdown PC-3 cells displayed inhibited growth of xenograft tumors. In addition, potential signaling pathways that might be involved in EIF3B action in prostate cancer were identified by the gene microarray. EIF3B is a novel oncogenic factor in prostate cancer both in vitro and in vivo, which could be employed as a novel therapeutic target in the treatment against prostate cancer.

Ground-based FTIR observation of hydrogen chloride (HCl) over Hefei, China, and comparisons with GEOS-Chem model data and other ground-based FTIR stations data.

In this study, the characterization of Hydrogen Chloride (HCl) seasonal variations and inter-annual linear trend are presented for the first time over the polluted region at Hefei (117°10'E, 31°54'N), China. The time series of HCl were retrieved by the mid-infrared (MIR) solar spectra recorded by the ground-based high-resolution Fourier transform infrared spectroscopy (FTIR) between July, 2015 and April, 2019. The magnitude of HCl reaches a peak in January (2.70 ± 0.16) × 1015 molecules*cm-2 and a minimum in September (2.27 ± 0.09) × 1015 molecules*cm-2. The four-year time series of HCl total column show a negative linear trend of (-1.83 ± 0.13) %. The FTIR data are compared with GEOS-Chem data in order to evaluate the performance of the GEOS-Chem model to simulate HCl. In general, total column FTIR data and GEOS-Chem model data are in a good agreement with a correlation coefficient of 0.82. GEOS-Chem model data present a good agreement with FTIR data in seasonal variation and inter-annul trend. The maximum differences occur in January and April with mean differences of 4%-6%. We also present HCl time series observed by 6 NDACC stations (Bremen, Toronto, Rikubetsu, Izana, Reunion.maido, Lauder) in low-middle-latitude sites of the northern and southern hemispheres and Hefei stations in order to investigate the seasonal and annual trends of HCl in low-middle-latitude sites. The HCl total column at the northern hemisphere stations reached the maximum in the late winter or early spring and the minimum in the early winter or late autumn. In general, the seasonal variations of HCl over Hefei is similar to that in other northern hemisphere mid-latitude FTIR stations.

Photoinduced Decarboxylative Amino-Fluoroalkylation of Maleic Anhydride.

A photoinduced decarboxylative three-component coupling reaction involving amine, maleic anhydride, and fluorinated alkyl iodides has been developed, leading to synthetically valuable fluoroalkyl-containing acrylamides with a high E selectivity. A broad array of substrates including monoprotected amino acid are capable coupling partners. Preliminary mechanistic studies suggest a stepwise process. This reaction represents the first example of photoinduced decarboxylative difunctionalization of maleic anhydride.

FTIR time series of stratospheric NO2 over Hefei, China, and comparisons with OMI and GEOS-Chem model data.

We present the trend and seasonal variability of stratospheric NO2 column for the first time over the polluted atmosphere at Hefei, China, retrieved using Fourier transform infrared spectroscopy (FTIR) between 2015 and 2018. The FTIR observed stratospheric NO2 columns over Hefei show a peak in June and reach a minimum in January. The mean stratospheric NO2 column concentration in June is (3.49 ± 0.25) × 1015 molecules*cm-2, and is 39.20% ± 8.95% higher than that in January with a mean value of (2.51 ± 0.21) × 1015 molecules*cm-2. We find a negative trend of (-0.34 ± 0.05) %/yr in the FTIR observations of stratospheric NO2 column. The FTIR data are compared to the satellite OMI observations to assess the new data set quality and also applied to evaluate the GEOS-Chem model simulations. We find in general the OMI observations and GEOS-Chem model results are in good agreement with the coincident FTIR data, and they all show similar seasonal cycles with strong correlation coefficients of 0.84-0.86. The annual average OMI minus FTIR difference is (1.48 ± 5.33) × 1014 molecules*cm-2 (4.82% ± 17.37%), and average GEOS-Chem minus FTIR difference is (2.36 ± 2.33) × 1014 molecules*cm -2 (7.66% ± 7.49%). Their maximum differences occur in April and May with mean differences of 12-16%. We also found negative trends in the stratospheric NO2 column over Hefei for 2015-2018 with both OMI observations (-0.91 ± 0.09%/yr) and GEOS-Chem model results (-0.31 ± 0.05%/yr), demonstrating some consistency among them.

[Quality Optimization Method for Ambient CO(2) Inversion of High Resolution Fourier Transform Infrared Spectrum].

CO(2) retrievals with high quality facilitate resolving the sources and sinks of CO(2) are helpful in predicting the trend in climate change and understanding the global carbon cycle. Based on a nonlinear least squares spectral fitting algorithm, we investigate the optimization method for CO2 products derived from ground-based high resolution Fourier transform infrared spectra. The CO(2) vertical column densities (VCDs) are converted into column-averaged dry air mole fraction XCO(2) by using the fitted O(2) VCDs, and thus the system errors (e. g. pointing errors, ILS errors, zero-level offset) are corrected greatly. The virtual daily variation which is related to air mass factor is corrected with an empirical model. The spectra screening rule proposed in this paper can greatly improve the XCO2 quality. The CO(2) retrievals before and after the optimized method are compared using a typical CO(2) daily time series. After using the optimized method, the fitting error is reduced by 60%, and the two-hours-averaged precision is ~0.071% (equals to ~0.28 ppm), which is perfectly in line with the TCCON (the total carbon column observing network) threshold, i. e., less than 0.1%.

[Sensitivity Study of Aerosol Properties from Observation of Atmospheric Ring Effect].

Ring effect is defined as the phenomenon that the depth of solar Fraunhofer lines in scattered light is less than those observed in direct sunlight. The aerosol could change the light path and the scattering properties in the atmospheric, and influence Raman Scattering Possibility of the photons, and finally affect the filling-up effect. Aerosol parameters (aerosol optical depth, boundary layer height, single scattering albedo, asymmetric factor) could be obtained by observation of the Ring effect in different aerosol condition. The Ring effect is measured by ground-based MAX-DOAS instrument under clear days and the measurement results is compared with McAritim results. The comparison has a good agreement. Radiation transfer model McArtim is used to study the sensitivity of the Ring effect to the aerosol parameters. The study shows that in most conditions, aerosol optical depth (AOD) and boundary layer (bh) height has a great influence to RSP, and in 90 degree elevation angle, RSP has a decrease of 24.6% when AOD varies from 0.1 to 1, and a decrease of 4.4% when bh varies from 1km to 3 km. The study shows RSP is more sensitive to AOD and boundary layer height, which may provide a new method for aerosol profile.

Quantifying emission fluxes of atmospheric pollutants from mobile differential optical absorption spectroscopic (DOAS) observations.

This study demonstrates a mobile passive differential optical absorption spectroscopy (DOAS) based remote sensing method for quantifying the emission fluxes of soot pollutants. First, the mobile DOAS system scans the plume emitted from urban sources. Then, the DOAS method retrieves the total columns of pollutant gases along the measurement path. Combining the longitude, latitude, and mobile speed recorded by vehicle GPS, the net emission fluxes of NO2 and SO2 in the measurement area are calculated by coupling with the wind field data. The NO2 flux in the region is combined with the NO to NO2 concentration ratio in the Copernicus Atmospheric Monitoring Service (CAMS) model to calculate NOx net emission flux in the measurement period. We conducted the mobile DOAS measurements in the coal production area and obtained the distribution of pollutant gases along the measurement path. Meanwhile, the NO2 concentration distribution of the city and surrounding areas were reconstructed by using TROPOMI satellite data. During the mobile measurement, the net NO2 emission flux measured by mobile DOAS are in good agreement with satellite observations (R2 = 0.66). This study verified that the flux calculation method based on mobile DOAS can be used to detect urban soot pollutant gas emissions.

Realization of thousand-second improved confinement plasma with Super I-mode in Tokamak EAST.

Mastering nuclear fusion, which is an abundant, safe, and environmentally competitive energy, is a great challenge for humanity. Tokamak represents one of the most promising paths toward controlled fusion. Obtaining a high-performance, steady-state, and long-pulse plasma regime remains a critical issue. Recently, a big breakthrough in steady-state operation was made on the Experimental Advanced Superconducting Tokamak (EAST). A steady-state plasma with a world-record pulse length of 1056 s was obtained, where the density and the divertor peak heat flux were well controlled, with no core impurity accumulation, and a new high-confinement and self-organizing regime (Super I-mode = I-mode + e-ITB) was discovered and demonstrated. These achievements contribute to the integration of fusion plasma technology and physics, which is essential to operate next-step devices.

[Measurement and analysis of nitric oxide gas based on the algorithm of non-dispersive ultra-violet].

Using photodiode array (PDA) detector and spectrometer, a method on the basis of algorithm of nondispersive ultraviolet (NDUV) is described to measure and analyze nitric oxide (NO) gas. With the introduction of light source impact factor and absorption spectrum impact factor, fitting equation and correlation coefficient between absorbance and concentration was acquired through comparative analysis on the total intensity of nitric oxide absorption and non-absorption spectrum, which are collected in different integration times and within different wavelength width. The results show that second order fitting correlation coefficient related to absorbance and concentration is above 0.999 9 and the error of concentrations between the concentration calculated by fitting equation and the standard concentration is less than 3% through using suitable fitting order, fitting wavelength width and analysis method.

[The correction of cloud effect on satellite near-infrared measurement].

The cloud effect correction is very significant to satellite remote sensing of atmospheric trace gases from near-infrared spectrum, even with a small amount of cloud, the remaining effects can still cause retrieval error even reaching up to 100%. Atmospheric carbon monoxide (CO) is one of the most important pollutants in the troposphere. This study, takeing CO as the example, described the cloud effect and the cloud correction on retrieval result from SCIAMACHY measurement. To validate the correction method, we compared both corrected and uncorrected results with the independent ground based FTIR measurements. After the correction, the agreement between satellite observations and FTIR measurements further improves.

Using machine learning approach to reproduce the measured feature and understand the model-to-measurement discrepancy of atmospheric formaldehyde.

The solar absorption spectrometry in the infrared spectral region, using high-resolution Fourier transform infrared (FTIR) spectrometer, has been established as a powerful tool in atmospheric science. These observations cannot be performed continuously, for example, clouds prevent observations. On the other hand, chemical transport models give continuously data. Their results depend on the knowledge of emission inventories, the chemistry involved, and the meteorological fields, yielding to potential biases between measurements and simulations. In our study we concentrated on Formaldehyde (HCHO) and used machine learning approach to fill the gap between the observations, performed on an irregular time scale and having their measurement lacks, and model data, giving continuous data, but having potential variable biases. The proposed machine learning approach is based on the Light Gradient Boosting Machine (LightGBM) algorithm and created by using GEOS-Chem simulations, meteorological fields, emission inventory, and is referred to as the GEOS-Chem-LightGBM model. The results of established GEOS-Chem-LightGBM model have generated consistent HCHO predictions with the ground-based FTIR and satellite (OMI and TROPOMI) observations. In order to understand the GEOS-Chem model to measurement discrepancy, we have investigated the contribution of each input variable to GEOS-Chem-LightGBM model HCHO predictions through the SHapely Additive exPlanations (SHAP) approach. We found that the GEOS-Chem model underestimates the sensitivities of HCHO total column to most photochemical variables, contributing to lower amplitudes of diurnal cycle and seasonal cycle by the GEOS-Chem model. By correcting the model-to-measurement discrepancy, the sensitivities of HCHO total column to all variables by the GEOS-Chem-LightGBM became to be in good agreement with the FTIR observations. As a result, GEOS-Chem-LightGBM model has significantly improved the performance of HCHO predictions compared to the GEOS-Chem alone. The proposed GEOS-Chem-LightGBM model can be extendible to other atmospheric constituents obtained by various measurement techniques and platforms, and is expected to have wide applications.

Observations of atmospheric CO2 and CO based on in-situ and ground-based remote sensing measurements at Hefei site, China.

The characteristics of long time series of CO2 and CO surface concentrations, tropospheric and total column dry-air mole fractions (DMF) from May 2015 to December 2019 were investigated. Both CO2 and CO show different seasonality for the three datasets. The annual increasing trend of CO2 is similar for all three datasets. However, the annual decreasing trend of CO for surface concentration is high compared to the other two measurements, mainly due to the improved combustion efficiency from power generation in recent years. The correlation between the tropospheric and total atmospheric CO2 and CO is higher than that between the surface concentration and tropospheric CO2 and CO. This is because the tropospheric and total atmospheric results both have common vertical profiles for CO2 and CO respective mole fractions that were observed in troposphere. Furthermore, the enhancement ratios of CO2 to CO derived from the three datasets during the period from 2016 to 2019 were compared. The ratio of ∆CO2 to ∆CO has an obvious increase with altitude each year, which means that the combustion efficiencies obtained from the three datasets are different. All ratios for the three datasets showed a slight increasing trend in recent years, which is attributed to increased combustion efficiency due to governmental measures for energy savings and emission reductions.

[Research on the method of interference correction for nondispersive infrared multi-component gas analysis].

A method of interference correction for nondispersive infrared multi-component gas analysis was described. According to the successive integral gas absorption models and methods, the influence of temperature and air pressure on the integral line strengths and linetype was considered, and based on Lorentz detuning linetypes, the absorption cross sections and response coefficients of H2O, CO2, CO, and NO on each filter channel were obtained. The four dimension linear regression equations for interference correction were established by response coefficients, the absorption cross interference was corrected by solving the multi-dimensional linear regression equations, and after interference correction, the pure absorbance signal on each filter channel was only controlled by the corresponding target gas concentration. When the sample cell was filled with gas mixture with a certain concentration proportion of CO, NO and CO2, the pure absorbance after interference correction was used for concentration inversion, the inversion concentration error for CO2 is 2.0%, the inversion concentration error for CO is 1.6%, and the inversion concentration error for NO is 1.7%. Both the theory and experiment prove that the interference correction method proposed for NDIR multi-component gas analysis is feasible.