Wenjing Lu

Ms. Wenjing Lu


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 June 2023 in Remote Sensing
Verified
Journal Article
Open access
PDF file
YGYuhang Guo
Yuhang Guo
XLXiaoying Li
Xiaoying Li
TCTianhai Cheng
Tianhai Cheng
SLShenshen Li
Shenshen Li
XZXinyuan Zhang
Xinyuan Zhang
WFWeifang Fang
Weifang Fang
Atmospheric profiles are important input parameters for atmospheric radiative transfer models and atmospheric parameter inversions. The construction of regionally representative reference atmospheric profiles can provide basic data for global atmospheric and environmental research. Most reference atmospheric profile databases commonly used lag behind in updating frequency. These databases usually have limited spatial and temporal resolution and differ greatly from the real atmospheric state. To present the real atmospheric state, this article constructs the Global Reference Atmospheric Profile Database (GRAP) based on ACE-FTS satellite products of 2021 and 2022, AIRS satellite products and ERA5 reanalysis data of 2022 u6sing a random forest regression model and a hierarchical mean algorithm. The radiance spectrum of FY-3E HIRAS-II using different profile databases was simulated and compared with the measured spectrum. The results show that GRAP spectral simulations fit better with the measured HIRAS-II spectrum. Comparing the CO2, CH4, O3 and N2O profiles of GRAP, AFGL, MIPAS, RTTOV and NDACC ground station profiles in equatorial, mid-latitude summer and polar winter, the results show that GRAP has high spatial and temporal resolution and better fits the current real atmospheric state. Comparing the temperature profiles of eight regions in China, the results illustrate that GRAP is a better representation of the state of the atmosphere in the Chinese region. GRAP can provide fundamental atmospheric data for radiative transfer studies and atmospheric parameter inversions.

26 February 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
WLWenjing Lu
Wenjing Lu
XLXiaoying Li
Xiaoying Li
SLShenshen Li
Shenshen Li
TCTianhai Cheng
Tianhai Cheng
YGYuhang Guo
Yuhang Guo
WFWeifang Fang
Weifang Fang
Accurately assessing the impact of anthropogenic carbon dioxide (CO2) emissions on CO2 concentrations is essential for understanding regional climate change, particularly in high-emission countries like China. This study employed the GEOS-Chem chemical transport model to simulate and compare the spatiotemporal distributions of XCO2 of three anthropogenic CO2 emission inventories in mainland China for the 2018–2020 period and analyzed the effects of emission variations on atmospheric CO2 concentrations. In eastern China, particularly in the Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) regions, column-averaged dry air mole fractions of CO2 (XCO2) can exceed 420 ppm during peak periods, with emissions from these areas contributing significantly to the national total. The simulation results were validated by comparing them with OCO-2 satellite observations and ground-based monitoring data, showing that more than 70% of the monitoring stations exhibited a correlation coefficient greater than 0.7 between simulated and observed data. The average bias relative to satellite observations was less than 1 ppm, with the Emissions Database for Global Atmospheric Research (EDGAR) showing the highest degree of agreement with both satellite and ground-based observations. During the study period, anthropogenic CO2 emissions resulted in an increase in XCO2 exceeding 10 ppm, particularly in the North China Plain and the YRD. In scenarios where emissions from either the BTH or YRD regions were reduced by 50%, a corresponding decrease of 1 ppm in XCO2 was observed in the study area and its surrounding regions. These findings underscore the critical role of emission control policies in mitigating the rise in atmospheric CO2 concentrations in densely populated and industrialized areas. This research elucidates the impacts of variations in anthropogenic emissions on the spatiotemporal distribution of atmospheric CO2 and emphasizes the need for improved accuracy of CO2 emission inventories.