Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters

We used the nested grid version of the global three-dimensional Goddard Earth Observing System chemical transport model (GEOS-Chem) to examine the interannual variations (IAVs) of aerosols over heavily polluted regions in China for years 2004–2012. The role of variations in meteorological parameter...

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Main Authors: Q. Mu, H. Liao
Format: Article
Language:English
Published: Copernicus Publications 2014-09-01
Series:Atmospheric Chemistry and Physics
Online Access:http://www.atmos-chem-phys.net/14/9597/2014/acp-14-9597-2014.pdf
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spelling doaj-b9e881507d9e4e7489fa2ae94e16a4f02020-11-24T23:01:24ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242014-09-0114189597961210.5194/acp-14-9597-2014Simulation of the interannual variations of aerosols in China: role of variations in meteorological parametersQ. Mu0H. Liao1State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, ChinaState Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, ChinaWe used the nested grid version of the global three-dimensional Goddard Earth Observing System chemical transport model (GEOS-Chem) to examine the interannual variations (IAVs) of aerosols over heavily polluted regions in China for years 2004–2012. The role of variations in meteorological parameters was quantified by a simulation with fixed anthropogenic emissions at year 2006 levels and changes in meteorological parameters over 2004–2012. Simulated PM<sub>2.5</sub> (particles with a diameter of 2.5 μm or less) aerosol concentrations exhibited large IAVs in North China (NC; 32–42° N, 110–120° E), with regionally averaged absolute percent departure from the mean (APDM) values of 17, 14, 14, and 11% in December-January-February (DJF), March-April-May (MAM), June-July-August (JJA), and September-October-November (SON), respectively. Over South China (SC; 22–32° N, 110–120° E), the IAVs in PM<sub>2.5</sub> were found to be the largest in JJA, with the regional mean APDM values of 14% in JJA and of about 9% in other seasons. The concentrations of PM<sub>2.5</sub> over the Sichuan Basin (SCB; 27–33° N, 102–110° E) were simulated to have the smallest IAVs among the polluted regions examined in this work, with APDM values of 8–9% in all seasons. All aerosol species (sulfate, nitrate, ammonium, black carbon, and organic carbon) were simulated to have the largest IAVs over NC in DJF, corresponding to the large variations in meteorological parameters over NC in this season. Process analyses were performed to identify the key meteorological parameters that determined the IAVs of different aerosol species in different regions. While the variations in temperature and specific humidity, which influenced the gas-phase formation of sulfate, jointly determined the IAVs of sulfate over NC in both DJF and JJA, wind (or convergence of wind) in DJF and precipitation in JJA were the dominant meteorological factors to influence IAVs of sulfate over SC and the SCB. The IAVs in temperature and specific humidity influenced gas-to-aerosol partitioning, which were the major factors that led to the IAVs of nitrate aerosol in China. The IAVs in wind and precipitation were found to drive the IAVs of organic carbon aerosol. We also compared the IAVs of aerosols simulated with variations in meteorological parameters alone with those simulated with variations in anthropogenic emissions alone; the variations in meteorological fields were found to dominate the IAVs of aerosols in northern and southern China over 2004–2012. Considering that the IAVs in meteorological fields are mainly associated with natural variability in the climate system, the IAVs in aerosol concentrations driven by meteorological parameters have important implications for the effectiveness of short-term air quality control strategies in China.http://www.atmos-chem-phys.net/14/9597/2014/acp-14-9597-2014.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Q. Mu
H. Liao
spellingShingle Q. Mu
H. Liao
Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters
Atmospheric Chemistry and Physics
author_facet Q. Mu
H. Liao
author_sort Q. Mu
title Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters
title_short Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters
title_full Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters
title_fullStr Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters
title_full_unstemmed Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters
title_sort simulation of the interannual variations of aerosols in china: role of variations in meteorological parameters
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2014-09-01
description We used the nested grid version of the global three-dimensional Goddard Earth Observing System chemical transport model (GEOS-Chem) to examine the interannual variations (IAVs) of aerosols over heavily polluted regions in China for years 2004–2012. The role of variations in meteorological parameters was quantified by a simulation with fixed anthropogenic emissions at year 2006 levels and changes in meteorological parameters over 2004–2012. Simulated PM<sub>2.5</sub> (particles with a diameter of 2.5 μm or less) aerosol concentrations exhibited large IAVs in North China (NC; 32–42° N, 110–120° E), with regionally averaged absolute percent departure from the mean (APDM) values of 17, 14, 14, and 11% in December-January-February (DJF), March-April-May (MAM), June-July-August (JJA), and September-October-November (SON), respectively. Over South China (SC; 22–32° N, 110–120° E), the IAVs in PM<sub>2.5</sub> were found to be the largest in JJA, with the regional mean APDM values of 14% in JJA and of about 9% in other seasons. The concentrations of PM<sub>2.5</sub> over the Sichuan Basin (SCB; 27–33° N, 102–110° E) were simulated to have the smallest IAVs among the polluted regions examined in this work, with APDM values of 8–9% in all seasons. All aerosol species (sulfate, nitrate, ammonium, black carbon, and organic carbon) were simulated to have the largest IAVs over NC in DJF, corresponding to the large variations in meteorological parameters over NC in this season. Process analyses were performed to identify the key meteorological parameters that determined the IAVs of different aerosol species in different regions. While the variations in temperature and specific humidity, which influenced the gas-phase formation of sulfate, jointly determined the IAVs of sulfate over NC in both DJF and JJA, wind (or convergence of wind) in DJF and precipitation in JJA were the dominant meteorological factors to influence IAVs of sulfate over SC and the SCB. The IAVs in temperature and specific humidity influenced gas-to-aerosol partitioning, which were the major factors that led to the IAVs of nitrate aerosol in China. The IAVs in wind and precipitation were found to drive the IAVs of organic carbon aerosol. We also compared the IAVs of aerosols simulated with variations in meteorological parameters alone with those simulated with variations in anthropogenic emissions alone; the variations in meteorological fields were found to dominate the IAVs of aerosols in northern and southern China over 2004–2012. Considering that the IAVs in meteorological fields are mainly associated with natural variability in the climate system, the IAVs in aerosol concentrations driven by meteorological parameters have important implications for the effectiveness of short-term air quality control strategies in China.
url http://www.atmos-chem-phys.net/14/9597/2014/acp-14-9597-2014.pdf
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