Contributions to the explosive growth of PM<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China
<p>The explosive growth of PM<span class="inline-formula"><sub>2.5</sub></span> mass usually results in extreme PM<span class="inline-formula"><sub>2.5</sub></span> levels and severe haze pollution in eastern China, and is gen...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2018-12-01
|
Series: | Atmospheric Chemistry and Physics |
Online Access: | https://www.atmos-chem-phys.net/18/17717/2018/acp-18-17717-2018.pdf |
id |
doaj-37d57d222431439793eff2fa2aebcc75 |
---|---|
record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
H. Wang H. Wang Y. Peng Y. Peng X. Zhang X. Zhang H. Liu M. Zhang H. Che Y. Cheng Y. Zheng Y. Zheng |
spellingShingle |
H. Wang H. Wang Y. Peng Y. Peng X. Zhang X. Zhang H. Liu M. Zhang H. Che Y. Cheng Y. Zheng Y. Zheng Contributions to the explosive growth of PM<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China Atmospheric Chemistry and Physics |
author_facet |
H. Wang H. Wang Y. Peng Y. Peng X. Zhang X. Zhang H. Liu M. Zhang H. Che Y. Cheng Y. Zheng Y. Zheng |
author_sort |
H. Wang |
title |
Contributions to the explosive growth of PM<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China |
title_short |
Contributions to the explosive growth of PM<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China |
title_full |
Contributions to the explosive growth of PM<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China |
title_fullStr |
Contributions to the explosive growth of PM<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China |
title_full_unstemmed |
Contributions to the explosive growth of PM<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China |
title_sort |
contributions to the explosive growth of pm<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in beijing–tianjin–hebei, china |
publisher |
Copernicus Publications |
series |
Atmospheric Chemistry and Physics |
issn |
1680-7316 1680-7324 |
publishDate |
2018-12-01 |
description |
<p>The explosive growth of PM<span class="inline-formula"><sub>2.5</sub></span> mass usually results in extreme PM<span class="inline-formula"><sub>2.5</sub></span> levels and severe haze
pollution in eastern China, and is generally underestimated by current
atmospheric chemistry models. Based on one such model, GRAPES_CUACE, three
sensitivity experiments – a “background” experiment (EXP1), an “online
aerosol feedback” experiment (EXP2), and an “80 % decrease in the
turbulent diffusion coefficient of chemical tracers” experiment, based on
EXP2 (EXP3) – were designed to study the contributions of the
aerosol–radiation feedback (AF) and the decrease in the turbulent diffusion
coefficient to the explosive growth of PM<span class="inline-formula"><sub>2.5</sub></span> during a “red alert”
heavy haze event in China's Jing–Jin–Ji (Beijing–Tianjin–Hebei) region.
The results showed that the turbulent diffusion coefficient calculated by
EXP1 was about 60–70 m<span class="inline-formula"><sup>−2</sup></span> s<span class="inline-formula"><sup>−1</sup></span> on a clear day and
30–35 m<span class="inline-formula"><sup>−2</sup></span> s<span class="inline-formula"><sup>−1</sup></span> on a haze day. This difference in the diffusion
coefficient was not enough to distinguish between the unstable atmosphere on
the clear day and the extremely stable atmosphere during the PM<span class="inline-formula"><sub>2.5</sub></span>
explosive growth stage. Furthermore, the inversion calculated by EXP1 was
obviously weaker than the actual inversion from sounding observations on the
haze day. This led to a 40 %–51 % underestimation of PM<span class="inline-formula"><sub>2.5</sub></span> by
EXP1; the AF decreased the diffusion coefficient by about 43 %–57 %
during the PM<span class="inline-formula"><sub>2.5</sub></span> explosive growth stage, which obviously strengthened
the local inversion. In addition, the local inversion indicated by EXP2 was
much closer to the sounding observations than that indicated by EXP1. This
resulted in a 20 %–25 % reduction of PM<span class="inline-formula"><sub>2.5</sub></span> negative errors in
the model, with errors as low as <span class="inline-formula">−16</span> % to <span class="inline-formula">−11</span> % in EXP2. However,
the inversion produced by EXP2 was still weaker than the actual observations,
and the AF alone could not completely explain the PM<span class="inline-formula"><sub>2.5</sub></span> underestimation.
Based on EXP2, the 80 % decrease in the turbulent diffusion coefficient
of chemical tracers in EXP3 resulted in near-zero turbulent diffusion,
referred to as a “turbulent intermittence” atmospheric state, which
subsequently resulted in a further 14 %–20 % reduction of the
PM<span class="inline-formula"><sub>2.5</sub></span> underestimation; moreover, the negative PM<span class="inline-formula"><sub>2.5</sub></span> errors were
reduced to <span class="inline-formula">−11</span> % to 2 %. The combined effects of the AF and the
decrease in the turbulent diffusion coefficient explained over 79 % of
the underestimation of the explosive growth of PM<span class="inline-formula"><sub>2.5</sub></span> in this study. The
results show that online calculation of the AF is essential for the
prediction of PM<span class="inline-formula"><sub>2.5</sub></span> explosive growth and peaks during severe haze in
China's Jing–Jin–Ji region. Furthermore, an improvement in the planetary
boundary layer scheme with respect to extremely stable atmospheric
stratification is essential for a reasonable description of local “turbulent
intermittence” and a more accurate prediction of PM<span class="inline-formula"><sub>2.5</sub></span> explosive growth
during severe haze in this region of China.</p> |
url |
https://www.atmos-chem-phys.net/18/17717/2018/acp-18-17717-2018.pdf |
work_keys_str_mv |
AT hwang contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT hwang contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT ypeng contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT ypeng contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT xzhang contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT xzhang contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT hliu contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT mzhang contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT hche contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT ycheng contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT yzheng contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina AT yzheng contributionstotheexplosivegrowthofpmsub25submassduetoaerosolradiationfeedbackanddecreaseinturbulentdiffusionduringaredalertheavyhazeinbeijingtianjinhebeichina |
_version_ |
1725281259985305600 |
spelling |
doaj-37d57d222431439793eff2fa2aebcc752020-11-25T00:42:38ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-12-0118177171773310.5194/acp-18-17717-2018Contributions to the explosive growth of PM<sub>2.5</sub> mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, ChinaH. Wang0H. Wang1Y. Peng2Y. Peng3X. Zhang4X. Zhang5H. Liu6M. Zhang7H. Che8Y. Cheng9Y. Zheng10Y. Zheng11State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaState Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaState Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, ChinaCenter for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences (CAS), Xiamen 361021, ChinaState Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, ChinaBeijing Meteorological Bureau, Beijing 100089, ChinaState Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, ChinaState Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, ChinaState Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China<p>The explosive growth of PM<span class="inline-formula"><sub>2.5</sub></span> mass usually results in extreme PM<span class="inline-formula"><sub>2.5</sub></span> levels and severe haze pollution in eastern China, and is generally underestimated by current atmospheric chemistry models. Based on one such model, GRAPES_CUACE, three sensitivity experiments – a “background” experiment (EXP1), an “online aerosol feedback” experiment (EXP2), and an “80 % decrease in the turbulent diffusion coefficient of chemical tracers” experiment, based on EXP2 (EXP3) – were designed to study the contributions of the aerosol–radiation feedback (AF) and the decrease in the turbulent diffusion coefficient to the explosive growth of PM<span class="inline-formula"><sub>2.5</sub></span> during a “red alert” heavy haze event in China's Jing–Jin–Ji (Beijing–Tianjin–Hebei) region. The results showed that the turbulent diffusion coefficient calculated by EXP1 was about 60–70 m<span class="inline-formula"><sup>−2</sup></span> s<span class="inline-formula"><sup>−1</sup></span> on a clear day and 30–35 m<span class="inline-formula"><sup>−2</sup></span> s<span class="inline-formula"><sup>−1</sup></span> on a haze day. This difference in the diffusion coefficient was not enough to distinguish between the unstable atmosphere on the clear day and the extremely stable atmosphere during the PM<span class="inline-formula"><sub>2.5</sub></span> explosive growth stage. Furthermore, the inversion calculated by EXP1 was obviously weaker than the actual inversion from sounding observations on the haze day. This led to a 40 %–51 % underestimation of PM<span class="inline-formula"><sub>2.5</sub></span> by EXP1; the AF decreased the diffusion coefficient by about 43 %–57 % during the PM<span class="inline-formula"><sub>2.5</sub></span> explosive growth stage, which obviously strengthened the local inversion. In addition, the local inversion indicated by EXP2 was much closer to the sounding observations than that indicated by EXP1. This resulted in a 20 %–25 % reduction of PM<span class="inline-formula"><sub>2.5</sub></span> negative errors in the model, with errors as low as <span class="inline-formula">−16</span> % to <span class="inline-formula">−11</span> % in EXP2. However, the inversion produced by EXP2 was still weaker than the actual observations, and the AF alone could not completely explain the PM<span class="inline-formula"><sub>2.5</sub></span> underestimation. Based on EXP2, the 80 % decrease in the turbulent diffusion coefficient of chemical tracers in EXP3 resulted in near-zero turbulent diffusion, referred to as a “turbulent intermittence” atmospheric state, which subsequently resulted in a further 14 %–20 % reduction of the PM<span class="inline-formula"><sub>2.5</sub></span> underestimation; moreover, the negative PM<span class="inline-formula"><sub>2.5</sub></span> errors were reduced to <span class="inline-formula">−11</span> % to 2 %. The combined effects of the AF and the decrease in the turbulent diffusion coefficient explained over 79 % of the underestimation of the explosive growth of PM<span class="inline-formula"><sub>2.5</sub></span> in this study. The results show that online calculation of the AF is essential for the prediction of PM<span class="inline-formula"><sub>2.5</sub></span> explosive growth and peaks during severe haze in China's Jing–Jin–Ji region. Furthermore, an improvement in the planetary boundary layer scheme with respect to extremely stable atmospheric stratification is essential for a reasonable description of local “turbulent intermittence” and a more accurate prediction of PM<span class="inline-formula"><sub>2.5</sub></span> explosive growth during severe haze in this region of China.</p>https://www.atmos-chem-phys.net/18/17717/2018/acp-18-17717-2018.pdf |