Characterization of vertical distribution and radiative forcing of ambient aerosol over the Yangtze River Delta during 2013-2015.

Aerosol direct radiative forcing Planetary boundary layer Vertical structure Yangtze River Delta region

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
10 Feb 2019
Historique:
received: 08 08 2018
revised: 14 09 2018
accepted: 20 09 2018
pubmed: 5 10 2018
medline: 5 10 2018
entrez: 5 10 2018
Statut: ppublish

Résumé

As the central part of eastern China, the Yangtze River Delta (YRD) region, with its rapid economic growth and industrial expansion, has experienced severe air quality issues. In this study, the monthly variation and interaction between aerosol direct radiative forcing (ADRF) and aerosol vertical structure during 2013-2015 over the YRD were investigated using ground-based observations from a Micro Pulse Lidar (MPL) and a CE-318 sun-photometer. Combining satellite products from MODIS and CALIPSO, and reanalysis wind fields, an integrated discussion of a biomass burning episode in Hangzhou during August 2015 was conducted by applying analysis of optical properties, planetary boundary layer (PBL), spatial-temporal and vertical distributions, backward trajectories, Potential Source Contribution Function (PSCF), and Concentration Weighted Trajectory (CWT). The results reveal that a shallower PBL coincides with higher scattering extinction at low altitude, resulting in less heating to the atmosphere and radiative forcing to the surface, which in turn further depresses the PBL. In months with a deeper PBL, the extinction coefficient decreases rapidly with altitude, showing stronger atmospheric heating effects and ADRF to the surface, facilitating the turbulence and vertical diffusion of aerosol particles, which further reduces the extinction and raises the PBL. Because of the hygroscopic growth facilitated by high relative humidity, June stands out for its high scattering extinction coefficient and relatively low PBL, and the reduced ADRF at the surface and the enhanced cooling effect on near-surface layer in turn depresses the PBL. Absorptive aerosols transported from biomass burning events located in Zhejiang, Jiangxi, and Taiwan provinces at 1.5 km, result in high ADRF efficiency for atmospheric heating. And the enhanced heating effect on near-surface layer caused by absorptive particles facilitates PBL development in August over the YRD.

Identifiants

pubmed: 30286352
pii: S0048-9697(18)33712-4
doi: 10.1016/j.scitotenv.2018.09.262
pii:
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1846-1857

Informations de copyright

Copyright © 2018 Elsevier B.V. All rights reserved.

Auteurs

Tianze Sun (T)

State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Huizheng Che (H)

State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China. Electronic address: chehz@cma.gov.cn.

Bing Qi (B)

Hangzhou Meteorological Bureau, Hangzhou 310051, China.

Yaqiang Wang (Y)

State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China.

Yunsheng Dong (Y)

Key Laboratory of Environment Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science, Hefei 230031, China.

Xiangao Xia (X)

Laboratory for Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; School of Geoscience University of Chinese Academy of Science, Beijing 100049, China. Electronic address: xxa@mail.iap.ac.cn.

Hong Wang (H)

State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China.

Ke Gui (K)

State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China.

Yu Zheng (Y)

Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Hujia Zhao (H)

State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China.

Qianli Ma (Q)

Lin'an Regional Air Background Station, Lin'an 311307, China.

Rongguang Du (R)

Hangzhou Meteorological Bureau, Hangzhou 310051, China.

Xiaoye Zhang (X)

State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China.

Classifications MeSH