Xiangchen Kong

Xiangchen Kong


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

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

Representative Publications

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2 January 2020 in Atmosphere
Verified
Journal Article
Open access
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ALAnkang Liu
Ankang Liu
Honglei WangHonglei Wang
Honglei Wang
YCYi Cui
Yi Cui
LSlijuan shen
lijuan shen
YYY. Yin
Y. Yin
XKXiangchen Kong
Xiangchen Kong
Particle size distribution, water soluble ions, and black carbon (BC) concentration in a long-term haze-fog episode were measured using a wide-range particle spectrometer (WPS), a monitor for aerosols and gases (MARGA), and an aethalometer (AE33) in Nanjing from 16 to 27 November, 2018. The observation included five processes of clean, mist, mix, haze, and fog. Combined with meteorological elements, the HYSPLIT model, and the IMPROVE model, we analyzed the particle size distribution, chemical composition, and optical properties of aerosols in different processes. The particle number size distribution (PNSD) in five processes differed: It was bimodal in mist and fog and unimodal in clean, mix, and haze. The particle surface area size distribution (PSSD) in different processes showed a bimodal distribution, and the second peak of the mix and fog processes shifted to a larger particle size at 480 nm. The dominant air masses in five processes differed and primarily originated in the northeast direction in the clean process and the southeast direction in the haze process. In the mist, mix, and fog processes local air masses dominated. NO3− was the primary component of water soluble ions, with the lowest proportion of 45.6% in the clean process and the highest proportion of 53.0% in the mix process. The ratio of NH4+ in the different processes was stable at approximately 23%. The ratio of SO42− in the clean process was 26.2%, and the ratio of other processes was approximately 20%. The average concentration of BC in the fog processes was 10,119 ng·m−3, which was 3.55, 1.80, 1.60, and 1.46 times that in the processes of clean, mist, mix, and haze, respectively. In the different processes, BC was primarily based on liquid fuel combustion. NO3−, SO42−, and BC were the main contributors to the atmospheric extinction coefficient and contributed more than 90% in different processes. NO3− contributed 398.43 Mm−1 in the mix process, and SO42− and BC contributed 167.90 Mm−1 and 101.19 Mm−1, respectively, during the fog process.

23 December 2019 in Atmosphere
Verified
Journal Article
Open access
PDF file
DBDongping Bai
Dongping Bai
Honglei WangHonglei Wang
Honglei Wang
YTYue Tan
Yue Tan
YYY. Yin
Y. Yin
ZWZhijun Wu
Zhijun Wu
XKXiangchen Kong
Xiangchen Kong
To clarify the aerosol optical properties under different pollution levels and their impacting factors, hourly organic carbon (OC), elemental carbon (EC), and water-soluble ion (WSI) concentrations in PM2.5 were observed by using monitoring for aerosols and gases (MARGA) and a semicontinuous OC/EC analyzer (Model RT-4) in Wuhan from 9 to 26 January 2018. The aerosol extinction coefficient (bext) was reconstructed using the original Interagency Monitoring of Protected Visual Environment (IMPROVE) formula with a modification to include sea salt aerosols. A good correlation was obtained between the reconstructed bext and measured bext converted from visibility. bext presented a unimodal distribution on polluted days (PM2.5 mass concentrations > 75 μg⋅m−3), peaking at 19:00. bext on clean days (PM2.5 mass concentrations < 75 μg⋅m−3) did not change much during the day, while on polluted days, it increased rapidly starting at 12:00 due to the decrease of wind speed and increase of relative humidity (RH). PM2.5 mass concentrations, the aerosol scattering coefficient (bscat), and the aerosol extinction coefficient increased with pollution levels. The value of bext was 854.72 Mm−1 on bad days, which was 4.86, 3.1, 2.29, and 1.28 times of that obtained on excellent, good, acceptable, and poor days, respectively. When RH < 95%, bext exhibited an increasing trend with RH under all pollution levels, and the higher the pollution level, the bigger the growth rate was. However, when RH > 95%, bext on acceptable, poor and bad days decreased, while bext on excellent and good days still increased. The overall bext in Wuhan in January was mainly contributed by NH4NO3 (25.2%) and organic matter (20.1%). The contributions of NH4NO3 and (NH4)2SO4 to bext increased significantly with pollution levels. On bad days, NH4NO3 and (NH4)2SO4 contributed the most to bext, accounting for 38.2% and 27.0%, respectively.