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.

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.

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.

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.

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.

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.

Air Quality in the Harbin-Changchun Metropolitan Area in Northeast China: Unique Episodes and New Trends.

Because of the unique geographical, climate, and anthropogenic emission characteristics, it is meaningful to explore the air pollution in the Harbin-Changchun (HC) metropolitan area. In this study, the Air Quality Index (AQI) and the corresponding major pollutant were investigated for the HC cities, based on the air quality data derived from the China National Environmental Monitoring Center. The number of days with the air quality level of "good" gradually increased during recent years, pointing to an improvement of the air quality in HC. It was also found that ozone, a typical secondary pollutant, exhibited stronger inter-city correlations compared to typical primary pollutants such as carbon monoxide and nitrogen dioxide. In addition, for nearly all the HC cities, the concentrations of fine particulate matter (PM2.5) decreased substantially in 2020 compared to 2015. However, this was not the case for ozone, with the most significant increase of ozone observed for HC's central city, Harbin. This study highlights the importance of ozone reduction for further improving HC's air quality, and the importance of agricultural fire control for eliminating heavily-polluted and even off-the-charts PM2.5 episodes.

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 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.

Photo-induced copper-catalyzed alkynylation and amination of remote unactivated C(sp3)-H bonds.

A method for remote radical C-H alkynylation and amination of diverse aliphatic alcohols has been developed. The reaction features a copper nucleophile complex formed in situ as a photocatalyst, which reduces the silicon-tethered aliphatic iodide to an alkyl radical to initiate 1,n-hydrogen atom transfer. Unactivated secondary and tertiary C-H bonds at ß, γ, and δ positions can be functionalized in a predictable manner.

Ozone profile retrievals from TROPOMI: Implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China.

During the outbreak of the coronavirus disease 2019 (COVID-19) in China in January and February 2020, production and living activities were drastically reduced to impede the spread of the virus, which also caused a strong reduction of the emission of primary pollutants. However, as a major species of secondary air pollutant, tropospheric ozone did not reduce synchronously, but instead rose in some region. Furthermore, higher concentrations of ozone may potentially promote the rates of COVID-19 infections, causing extra risk to human health. Thus, the variation of ozone should be evaluated widely. This paper presents ozone profiles and tropospheric ozone columns from ultraviolet radiances detected by TROPOospheric Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) satellite based on the principle of optimal estimation method. We compare our TROPOMI retrievals with global ozonesonde observations, Fourier Transform Spectrometry (FTS) observation at Hefei (117.17°E, 31.7°N) and Global Positioning System (GPS) ozonesonde sensor (GPSO3) ozonesonde profiles at Beijing (116.46°E, 39.80°N). The integrated Tropospheric Ozone Column (TOC) and Stratospheric Ozone Column (SOC) show excellent agreement with validation data. We use the retrieved TOC combining with tropospheric vertical column density (TVCD) of NO2 and HCHO from TROPOMI to assess the changes of tropospheric ozone during the outbreak of COVID-19 in China. Although NO2 TVCD decreased by 63%, the retrieved TOC over east China increase by 10% from the 20-day averaged before the lockdown on January 23, 2020 to 20-day averaged after it. Because the production of ozone in winter is controlled by volatile organic compounds (VOCs) indicated by monitored HCHO, which did not present evident change during the lockdown, the production of ozone did not decrease significantly. Besides, the decrease of NOx emission weakened the titration of ozone, causing an increase of ozone.

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.

Spatiotemporal variation and source analysis of air pollutants in the Harbin-Changchun (HC) region of China during 2014-2020.

This study analyzed the characteristics of air pollution and specific pollution periods within the Harbin-Changchun (HC) metropolitan area during 2014-2020. Regarding annual, seasonal, and monthly variations of the six pollutants, the change trend in 11 cities of HC showed strong consistency in spatial distribution. The western cities (Songyuan, Daqing, and Siping) were vulnerable to dust storms from Inner Mongolia. The concentrations of all air pollutants, except O3-8h, showed downward fluctuation trends from 2014 to 2018 and remained stable from 2018 to 2020 in terms of annual variations. The inter-annual trend of significant reductions in SO2 and SO2/PM2.5 during the heating period indicated that strict emission reduction measures posed by the government were highly successful. The ratio of PM2.5/SO2 was used to identify open biomass burning (OBB), which showed a double peak (October-November (Oct-Nov), March-April (Mar-Apr)). The burning prohibition shifted the OBB from Oct-Nov to Mar-Apr.

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.

Copper-Catalyzed Photoinduced Enantioselective Dual Carbofunctionalization of Alkenes.

A photoinduced, copper-catalyzed, highly enantioselective dual alkylation/arylation and alkynylation of alkene is reported. A single chiral copper(I) complex serves to enable photoredox catalysis and induce enantioselectivity during the reaction. This reaction couples three different components under mild reaction conditions, exhibits a broad substrate scope, and provides facile access to chiral propargylic systems, including those featuring valuable fluorinated substituents.

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.