The compressional magnetic component δB|| has been implemented in the gyrokinetic Particle-in-Cell (PIC) code GEM for the fully electromagnetic simulation of microscopic instabilities in high-β ...tokamak plasmas. The simulation model is formulated for the split-weight scheme that is based on the canonical momentum formulation of the gyrokinetic equation. A pseudo-spectral method is used to solve the coupled gyrokinetic field equations while preserving all finite-Larmor-radius (FLR) effects. The algorithm is verified by the method of manufactured solutions. Simulations of the ion-temperature-gradient-driven (ITG) mode, the kinetic balloon mode (KBM) and the trapped electron mode (TEM) are presented.
Nitrogen dioxide (NO.sub.2) is mainly affected by local emission and meteorology rather than long-range transport. Accurate knowledge of its long-term variabilities and drivers is significant for ...understanding the evolution of economic and social development, anthropogenic emission, and the effectiveness of pollution control measures on a regional scale. In this study, we quantity the long-term variabilities and the underlying drivers of NO.sub.2 from 2005-2020 over the Yangtze River Delta (YRD), one of the most densely populated and highly industrialized city clusters in China, using OMI spaceborne observations and the multiple linear regression (MLR) model. We have compared the spaceborne tropospheric results to surface in situ data, yielding correlation coefficients of 0.8 to 0.9 over all megacities within the YRD. As a result, the tropospheric NO.sub.2 column measurements can be taken as representative of near-surface conditions, and we thus only use ground-level meteorological data for MLR. The inter-annual variabilities of tropospheric NO.sub.2 vertical column density (NO.sub.2 VCD.sub.trop) from 2005-2020 over the YRD can be divided into two stages. The first stage was from 2005-2011, which showed overall increasing trends with a wide range of (1.91 ± 1.50) to (6.70 ± 0.10) x 10.sup.14 molec. cm.sup.-2 yr.sup.-1 (p0.01) over the YRD. The second stage was from 2011-2020, which showed overall decreasing trends of (-6.31 ± 0.71) to (-11.01 ± 0.90) x 10.sup.14 molec. cm.sup.-2 yr.sup.-1 (p0.01) over each of the megacities. The seasonal cycles of NO.sub.2 VCD.sub.trop over the YRD are mainly driven by meteorology (81.01 %-83.91 %), except during winter when anthropogenic emission contributions are pronounced (16.09 %-18.99 %). The inter-annual variabilities of NO.sub.2 VCD.sub.trop are mainly driven by anthropogenic emission (69.18 %-81.34 %), except for a few years such as 2018 which are partly attributed to meteorology anomalies (39.07 %-91.51 %). The increasing trends in NO.sub.2 VCD.sub.trop from 2005-2011 over the YRD are mainly attributed to high energy consumption associated with rapid economic growth, which causes significant increases in anthropogenic NO.sub.2 emission. The decreasing trends in NO.sub.2 VCD.sub.trop from 2011-2020 over the YRD are mainly attributed to the stringent clean air measures which either adjust high-energy industrial structure toward low-energy industrial structure or directly reduce pollutant emissions from different industrial sectors.
Photoacoustic (PA) spectroscopic technique has become a popular tool for trace gas detection and is especially suitable for in situ measurement of sulfur hexafluoride (SF 6 ) decomposition components ...in gas insulated switchgear (GIS). However, the concentrations of SF 6 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 SF 6 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.
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.
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•The GEOS-Chem-LightGBM model predicted continually FTIR HCHO total columns.•The GEOS-Chem-LightGBM model has significantly performance of HCHO predictions.•The discrepancy between model-to-measurement has been investigated by SHAP approach.•The machine learning method provides high-quality FTIR HCHO total columns.
Gaps remain in physics and engineering for CFETR design. This report will focus on the high performance long pulse/steady-state operation and the power exhausting issues. The possible operation ...windows for designed CFETR plasma to achieve its goal and related challenge are presented. Another part of this report is to summarize the endeavors on EAST experiment, which could possibly address the solutions to the critical issues above for future fusion reactors. Advances on EAST scenario development and divertor heat flux control are presented.
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.
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•First ozone profiles are retrieved from TROPOMI based on the optimization estimation.•The mean biases of the retrieved profile are within 15% with soft calibration.•The TOC over east China increase by 10% from pre-lockdown to post-lockdown.•The decrease of NOx emission causes an increase of ozone in eastern China.
Demonstrates a mobile passive differential optical absorption spectroscopy (DOAS) based remote sensing method for quantifying the emission fluxes of soot pollutants. Reconstructed the spatial ...distribution of NO2 concentrations in mobile measurement area and surrounding areas by using TROPOMI satellite data and analyzed the spatial distribution of NO2 concentrations along the direction of the wind field.
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•Demonstrates a mobile passive differential optical absorption spectroscopy (DOAS) based remote sensing method for quantifying the emission fluxes of soot pollutants.•Using NO2 net emission flux combined with CAMS model to calculate NOx net emission flux.•Reconstructed the spatial distribution of NO2 concentrations in mobile measurement area and surrounding areas by using TROPOMI satellite data and analyzed the spatial distribution of NO2 concentrations along the direction of the wind field.
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.
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