Opposite seasonality of the aerosol optical depth and the surface particulate matter concentration over the north China Plain

Accepted Manuscript Opposite seasonality of the aerosol optical depth and the surface particulate matter concentration over the North China Plain Wenjun Qu, Jun Wang, Xiaoye Zhang, Lifang Sheng, Wencai Wang PII:

S1352-2310(15)30568-9

DOI:

10.1016/j.atmosenv.2015.11.061

Reference:

AEA 14313

To appear in:

Atmospheric Environment

Received Date: 13 July 2015 Revised Date:

26 November 2015

Accepted Date: 28 November 2015

Please cite this article as: Qu, W., Wang, J., Zhang, X., Sheng, L., Wang, W., Opposite seasonality of the aerosol optical depth and the surface particulate matter concentration over the North China Plain, Atmospheric Environment (2015), doi: 10.1016/j.atmosenv.2015.11.061. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Opposite seasonality of the aerosol optical depth and the surface

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particulate matter concentration over the North China Plain

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Wenjun Qu1, Jun Wang2, Xiaoye Zhang3, Lifang Sheng1, Wencai Wang1

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Physical Oceanography Laboratory, Key Laboratory of Ocean-Atmosphere

Interaction and Climate in Universities of Shandong, Ocean University of China,

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Qingdao 266100, China

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Chinese Academy of Meteorological Sciences, China Meteorological Administration,

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Beijing 100081, China

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Department of Earth and Atmospheric Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska 68588-0340, USA

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Revision submitted to Atmospheric Environment, November 26, 2015

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*Corresponding to Wenjun Qu, Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China. Tel.: +86-532-66781309; fax: +86-532-66782790. e-mail: [email protected], [email protected]

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ACCEPTED MANUSCRIPT Abstract: Great difference exists in the aerosol optical depth (AOD) between summer

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and winter over the North China Plain (NCP). Monthly mean AOD at 550 nm derived

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from the MODIS (MODerate Resolution Imaging Spectroradiometer) products during

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2000 to 2014 over the area of 30–40° N and 110–125° E exhibits an annual maximum

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in June (0.855 ± 0.130) and a minimum in December (0.381 ± 0.032). This

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seasonality of AOD is in the opposite phase with the surface particulate matter (PM)

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concentration (higher in winter and lower in summer). The possible causes for the

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higher AOD in June (compared with December) include (a) a higher boundary layer

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height (BLH) that results in more efficient transport and mixing of aerosol particles to

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a higher altitude (corresponding to a lower particle concentration near surface) as

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revealed by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations

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profile, (b) a higher relative humidity (RH) due to the inshore monsoon circulation

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that leads to enhancement of aerosol extinction, (c) emission from the regional open

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stalk burning in the summer harvest season (as seen from MODIS fire products), and

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(d) the typical eastward open topographical basin over NCP. Under the assumption

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that the aerosol and water vapor are well mixed within the boundary layer, analysis on

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multi-year average shows that the differences in BLH, RH and surface PM

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concentration can explain up to 81% of the variance of monthly averaged AOD over

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NCP. A preliminarily hypothesis is also suggested to interpret the shift of AOD

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pattern from winter to summer with an abrupt increase of AOD from May to June, as

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well as an increase of surface PM2.5 concentration over NCP during the early phase of

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northward progress of the East Asia summer monsoon front.

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ACCEPTED MANUSCRIPT Keywords: Aerosol optical depth; Seasonality; Boundary layer height; North

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China Plain

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1. Introduction Satellite measurement has been applied to air quality monitoring worldwide

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including the North China Plain (NCP, Li et al, 2003); although a good relationship

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has been established between the MODerate Resolution Imaging Spectroradiometer

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(MODIS) aerosol optical depth (AOD) and surface PM2.5 (particulate matter (PM)

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with diameter ≤ 2.5 µm) concentration in eastern and Midwestern USA (Engel-Cox et

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al., 2004) and Alabama (Wang and Christopher, 2003), correlation between AOD and

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surface PM2.5 is quite poor in western USA (Engel-Cox et al., 2004). A critical review

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by Hoff and Christopher (2009) concluded that the derivation of surface PM2.5 from

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satellite measurement of AOD (with a precision of ±20%) has an uncertainty of ±30%

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(or larger), AOD should combine with ground-based measurement and model to

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improve PM estimation from space.

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Li et al. (2003) validated the MODIS aerosol products and identified three high

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AOD areas in eastern China (ECN). In north China, a discrepancy in the seasonal

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variations of AOD and surface particle concentration has been identified, which was

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partly attributed to the variation of atmospheric mixing layer height (Xia et al., 2006).

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Wang et al. (2012) reported the contrasting trends between PM10 and the aerosol

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optical extinction in China, USA, Canada and Europe from 1992 to 2011, and

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emphasized contribution from the increased fraction of anthropogenic aerosol

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emission (mostly fine particle). Besides the vertical profile and size distribution of the

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aerosol, are there any other factors also contribute to the seasonal variation of AOD in

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north China?

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ACCEPTED MANUSCRIPT While the wintertime air pollution (as well as haze and fog) is recognized as a

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major concern in ECN (Yang et al., 2013a; Zhao et al., 2013; Boynard et al., 2014),

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past studies also investigated the increasing trend of summertime air quality

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deterioration in the region from both the meteorology (Qu et al., 2013) and the

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emission (Li et al., 2010) perspectives. An overall comparatively better surface air

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quality in summer (than in winter) over ECN can be easily understood because of the

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greater boundary layer height (BLH) which is more favorable for dilution and

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diffusion of the pollutants as well as the more intensive precipitation which is more

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favorable for wet scavenging of the particle. For example, the surface fine particle

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concentration in Wuhan, China was found to be mainly depends on variation in the

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convective BLH (Kong and Yi, 2015). However, it is interesting that the better air

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quality and lower PM concentration near surface in summer is in contrast with the

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higher summertime AOD (will be discussed in section 3) over NCP (generally the

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area of 30–40° N and 110–125° E, Fig. 1). This study will examine the factors

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contributing to the higher AOD in June (compared with the lower AOD in December)

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over NCP.

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2. Data

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The data used in this study include MODIS Terra AOD products (1×1 degree grid)

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from

March

2000

to

December

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(http://giovanni.gsfc.nasa.gov/giovanni/) and the GOCART (Goddard Chemistry

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Aerosol Radiation and Transport, Mian et al., 2002) modeled CODs (column optical

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2014

from

Giovanni

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depth) for different aerosol components in 2000 – 2007 (formerly distributed by

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Giovanni, accessed by July 2015), as well as the AERONET AOD data at Beijing

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(116.381°

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(http://aeronet.gsfc.nasa.gov/cgi-bin/webtool_opera_v2_new). The aerosol extinction

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coefficient at 532 nm derived from the Cloud-Aerosol Lidar and Infrared Pathfinder

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Satellite

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(https://eosweb.larc.nasa.gov/project/calipso/cal_lid_l3_apro_allsky-beta-v1-30_table)

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is used to reflect vertical distribution of the aerosol. Relative humidity (RH) and wind

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(2.5×2.5 degree grid) from NCEP (United States National Centers for Environmental

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Prediction)

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(http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html)

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(0.125×0.125 degree grid) from ECMWF (European Center for Medium-Range

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Weather Forecasts) reanalysis data (http://apps.ecmwf.int/datasets/) are also used to

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make comparison of meteorology between summer and winter.

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(CALIPSO)

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In addition, the available PM10 (particles with diameter ≤ 10 µm) concentration in

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34 major Chinese cities over NCP from 2005 to 2012 is derived from the air pollution

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index

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from

the

Ministry of

Environment

Protection

of

China

(MEPC,

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http://datacenter.mep.gov.cn/) using the method in Qu et al. (2010). Similarly, the

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available PM2.5 concentration in 142 Chinese cities in 2014 is also derived from the

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air quality index from MEPC. These data are used to reflect the seasonal variation of

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surface PM concentration over NCP.

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Moreover, the surface visibility (Vis), wind speed and RH extracted from the

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354 stations in China are used to assess impact of the northward progress of East Asia

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summer monsoon. Detail of these data is described in Qu et al. (2013, 2015b).

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3. Contrast between AOD and surface PM seasonality over NCP

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The mean MODIS Terra AOD at 550 nm over China during 2000 to 2014

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demonstrates that the AOD seasonal contrast is most distinct over NCP; AOD in June

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is generally larger than 0.6 (> 0.9 over most of the area, Fig. 1a) and AOD in

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December generally ranges from 0.36 to 0.6 over NCP (Fig. 1b, also see

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supplementary material 1 for the yearly comparison), which reflects the greatest

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seasonal difference of monthly AOD in China. NCP is also the major high AOD area

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in China; the AOD hotspot area over NCP is generally constrained within the NCP

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topographical basin (supplementary material 1), which is expected because the basin

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is always most densely populated with intensive anthropogenic emission, consistent

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with Li et al. (2003) that human activities are the main source of aerosols in ECN. In

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addition, the obvious interannual variation in spatial coverage of the higher AOD area

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over ECN (supplementary material 1) is beyond the scope of this study.

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Fig. 2 shows the time series of AOD and surface PM concentration. The monthly

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averaged MODIS Terra AOD at 550 nm over NCP during 2000 to 2014 obviously

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illustrates an annual maximum in June (0.855 ± 0.130, Fig. 2a) and a minimum in

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December (0.381 ± 0.032). The AERONET monthly averaged AOD at Beijing (Fig.

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2b) generally shows a synchronous variation with the MODIS AOD over NCP, and

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significant correlations (R = 0.72 – 0.75, P < 0.0001 significance, n = 135) exist

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between the monthly averaged AERONET AODs at 440 nm, 675 nm, 870 nm and

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1020 nm at Beijing with the monthly averaged MODIS AOD over NCP. Fig. 2c shows monthly surface PM10 mass concentration in 34 major Chinese

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cities over NCP from 2005 to 2012. In discrepancy with the higher AOD in June

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(compared with the lower AOD in December), the surface PM10 concentration in June

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is generally lower than that in December; similarly, the PM2.5 concentration varies in

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a same way as PM10 (supplementary material 2). It must be noted here that the

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MODIS AOD is an ambient measurement, but the surface PM measurement is

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generally made by using of the Tapered Element Oscillating Microbalance analyzers

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(TEOMs, model 1400a, Rupprecht & Patashnick, USA) at an elevated temperature

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(50 °C), thus suffers loss of materials such as the semi-volatile and hygroscopic

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species (see detail in Qu et al., 2010). A discussion of the possible causes resulting in

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such contrast between the phase of monthly variation of AOD and PM will follow.

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4. Possible causes of the AOD seasonality over NCP

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4.1. Emission

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Over ECN, the presumably intensive and continuous anthropogenic emission (of

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the aerosol and its precursor gases) due to house heating is believed to be an important

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additional source in winter. Such an intensive anthropogenic emission in winter is

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supported by the high wintertime black carbon and brown carbon concentration

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reported in Beijing during 2002 to 2013 (Li et al., 2015). Meanwhile, the higher

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mineral dust concentration in Beijing in spring (Li et al., 2015) is consistent with the

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more intensive springtime dust emission.

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On the other hand, an inspection of global fire maps from the National Aeronautics

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(http://www.earthobservatory.nasa.gov/GlobalMaps/view.php?d1=MOD14A1_M_FI

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RE#) shows clear fire points from Shandong Peninsula to the north of Yangtze River

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in ECN (the major NCP area) in June every year, suggesting potential additional

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emission sources favorable for high AOD over this area in June. Such an additional

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June emission is most probably associated with the regional intensive open stalk

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burning in the summer harvest season. Individual particle study did identify evidence

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of the contribution from regional agricultural biomass burning to high AOD in Beijing

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and north China in June 2007 (Li et al., 2010). This regional open, out-of-order and

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uncontrolled stalk burning is a major emission source over NCP in the summer

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harvest season. For example, the agricultural biomass burning has been found to be

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associated with the AOD peak value in June over ECN (Yang et al., 2013b).

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Observation of a clearly increased black carbon concentration in June (comparable

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with those in December, January and February) at Beijing (Li et al., 2015) also

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supports this point.

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In addition to emission, BLH (associated with vertical distribution of the aerosol)

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and meteorology (including wind and RH) are the other important factors influencing

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AOD and PM concentration and will be discussed next.

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4.2. BLH and vertical extinction profile

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ECMWF model, see section 2) between June and December during 2000 – 2013,

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shows that BLH in June is generally greater than BLH in December by at least 350

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meter over the AOD hotspots area from Shandong Peninsula to the north of Yangtze

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River in ECN (i.e., NCP, Fig. 3a); the higher BLH could result in more efficient

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transport and mixing of particles to a higher altitude (layer), leading to an increase of

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column AOD in June (compared to December) but possibly a decrease of surface PM

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concentration, consistent with Kong and Yi (2015).

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A comparison of the CALIPSO extinction profiles between June and December in

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2014 over NCP (Fig. 3b) does illustrate a higher extinction coefficient in June at a

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higher altitude, especially above ~600 meter where both the day and night extinction

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coefficients in June are much higher than those in December. The higher extinction

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coefficient above ~600 meter in the vertical profile in June (compared with that in

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December) is consistent with the higher BLH (favorable for more efficient transport

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and mixing of particles to a higher altitude) as well as the higher column integrated

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AOD. The peak extinction coefficient layers located aloft in the June profiles (relative

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to the December profiles) and the significant difference in extinction coefficient

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between higher altitude and near surface in Fig. 3b can interpret the higher AOD and

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lower surface PM concentration in June.

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Fig. 3e shows the monthly average BLH over the area of 30–40° N and 110–120°

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E during 2000 – 2013. As BLH is much different between land and ocean (Fig. 3a),

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120° E is chosen as the east boundary to plot the monthly BLH time series over the

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ACCEPTED MANUSCRIPT major land area within the study area. A comparably higher BLH is found in June

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(only slightly lower than that in May and April), consistent with the higher AOD then.

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On the contrary, a lower BLH in December (Fig. 3e) is consistent with the lowest

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AOD over NCP in December (Fig. 2a and 2b).

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4.3. Other meteorological and topographical factors

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NCP is an eastward open topographical basin surrounded by the Yanshan

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Mountains to the north, by the Taihang Mountains and the Qinling Mountains to the

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west, and by the Daba Mountains and the Dabie Mountains to the south (see

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supplementary material 1). The difference of wind vector between June and December

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illustrates a prevailing inshore (southeast and south) wind in June (Fig. 3c), which

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favors accumulation of the pollutants (originated from the intensive anthropogenic

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emission in this densely populated region) within the topographical basin of NCP and

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influx of the moisture from the ocean. Correspondingly, the RH profile (Fig. 3d) as

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well as the difference of RH between June and December at 850 hPa level (Fig. 3c)

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demonstrates a higher RH in June from 1000 hPa to 300 hPa levels over the AOD

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hotspots area of NCP. Meanwhile, a significant increase of RH from May to June is

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obvious at 1000 hPa, 925 hPa and 850 hPa levels over the area of 30–40° N and

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110–120° E (Fig. 3f). Here the 850 hPa pressure level, which is comparable to ~1900

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meter of the average BLH in June (Fig. 3e), is chosen to reflect RH at the upper level

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of the boundary layer (BL). Such an increase of RH in June at different levels is

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favorable for enhancement in new particle speciation (NPS) and secondary aerosol

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formation (such as sulfate and organic aerosol, Sun et al., 2013) as well as in

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hygroscopic growth of the aerosol (Qu et al., 2015a); all these processes can

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subsequently result in enhanced aerosol extinction as well as increase of the column

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AOD and impairment of visibility (Vis). Indeed, increase of AOD is found to be associated with increase of the total

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column water vapor content (CWV, Smirnov et al., 2002; Eck et al., 2008). Bi et al.

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(2014) identified a strong positive correlation between AOD and CWV at Beijing in

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January 2013. Aerosol water content was found to contribute significantly to the light

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extinction under Asian continental outflow (Jung and Kim, 2011), and its effect on

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light extinction and Vis impairment is mainly due to increases of the (NH4)2SO4 and

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NH4NO3 concentration (Jung et al., 2009).

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Along this line, a comparison of the GOCART (Mian et al., 2002) modeled CODs

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(column optical depth) of the aerosol components in 2000 – 2007 shows that sulfate

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has the greatest COD difference between June and December (supplementary material

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3). The higher sulfate COD over NCP in June is consistent with the initial significant

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increase of RH from May to June (Fig. 3f), which confirms that increase of RH and

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enhancement of hygroscopic growth of sulfate (a major aerosol component)

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contribute crucially to the maximal AOD in June over NCP. Moreover, the high

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sulfate COD center (> 0.1, shaded with blue to yellow) spans all over ECN in June but

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only limits within the more south part of ECN in December, consistent with the

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general spatial and temporal distribution of higher RH. Similarly, the high BC area

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also limits within the south part of ECN in December and shows a broadly northward

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extension in June, but with a weaker summer vs. winter contrast compared with

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sulfate (figures not shown). The June vs. December difference of CODs for other

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aerosol components is unobvious and not considered.

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Furthermore, according to the IMPROVE (Interagency Monitoring of Protected Visual

Environments)

reconstruction

method

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(http://vista.cira.colostate.edu/improve/Tools/ReconBext/reconBext.htm) for aerosol

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scattering (which is a major component of aerosol extinction), the scattering

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coefficient (Bscat) can be calculated using the following formula,

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Bscat (Mm-1) = 3fT(rh)[Sulfate] + 3 fT(rh) [Nitrate] + 4 forg(rh) [OMC]

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+ 1 [Soil] + 0.6 [CM]

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(1)

where [Sulfate] and [Nitrate] are mass concentrations calculated based on the forms of

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(NH4)2SO4 and NH4NO3, [OMC] is the organic mass by carbon, [Soil] is the mass of

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fine dust aerosol and [CM] is the coarse mass; while fT(rh) and forg(rh) are the relative

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humidity correction factors for converting dry scattering coefficient to ambient value.

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Three times of fT(rh) and four times of forg(rh) in formula (1) demonstrate that

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scattering of aerosol components such as sulfate, nitrate and organic matter can be

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strongly enhanced when RH increases, which supports the conjecture above that the

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higher RH and higher sulfate contribution to the aerosol profile over NCP in June are

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associated with an increase of AOD due to enhancement of the aerosol extinction

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efficiency.

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In summary, the comparably higher BLH in June (Fig. 3e) is favorable for more

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efficient transport and mixing of particles to a higher elevation, which results in a

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higher AOD but a smaller surface PM concentration. On the contrary, in December

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but a lower extinction coefficient in the vertical profile (Fig. 3b) and subsequently a

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lower AOD. Moreover, accumulation of the pollutants within the eastward open

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topographical basin of NCP and influx of the moisture (as well as increase of RH)

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accompanied with the prevailing inshore wind in June (Fig. 3c) are also favorable for

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the enhancement of aerosol extinction and for the higher AOD over NCP. An

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integration of these factors is followed in section 5.

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5. A simple model to reconcile AOD and PM seasonality

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AOD is in proportion to the product of PM concentration, the shape of aerosol

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extinction profile (H) and RH correction factors (f(rh)) (Kessner et al., 2013). Here

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the PM10 concentration during 2005–2012 and PM2.5 concentration during 2014 in 34

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major Chinese cities within NCP are used to calculate the monthly PM concentration.

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The monthly averaged BLH over NCP during 2005–2012 is used to reflect variation

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of H. RH at the 1000 hPa, 925 hPa and 850 hPa levels are used to calculate the

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monthly averaged RH within BL, which is subsequently used to determine f(rh) value

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(http://vista.cira.colostate.edu/improve/Tools/humidity_correction.htm). Note BLH at

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14:00 local time is used, while RH and PM are derived from daily averages; these

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measurements are not coincident in time with the MODIS satellite overpass. Although

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monthly averages are compared here, disagreement is expected due to difference in

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the temporal coverage of measurements. Assuming the aerosol and water vapor are

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well mixed within BL, the PM concentration, f(rh) and BLH is used to establish a

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simple model, and PM*BLH*f(rh) can thus reflect the variation of AOD due to

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aerosol extinction in BL, which is subsequently compared with the monthly averaged

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MODIS AOD over NCP. There is generally a synchronous variation between the multi-year averaged

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monthly PM*BLH*f(rh) and AOD over NCP (with a June maximum and a December

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minimum, Fig. 4a and 4b); moreover, significant correlations also exist between

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PM*BLH*f(rh) and AOD (R2 = 0.81 and 0.74 for PM10 and PM2.5, respectively, P <

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0.0005, n = 12, Fig. 4d and 4e). Although individually PM, BLH and f(rh) can not

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well explain the AOD variation, BLH in collaboration with the surface PM

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concentration (PM) and the RH correction factor (f(rh)) can explain about 81% or

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74% of the variance of monthly averaged AOD over NCP. Consequently, the simple

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model supports our discussion in section 4 that the large values of BLH, RH and the

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corresponding emission and PM concentration are major possible causes of the

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maximal AOD in June over NCP. Note here only the available surface PM

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concentration is used in the comparison between PM*BLH*f(rh) and AOD.

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significant (P < 0.0001 significance level) correlation (R2 = 0.12 – 0.41, n = 103 – 151)

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between PM10*BLH*f(rh) and AOD for 22 of the 34 cities over NCP (for more detail

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see supplementary material 4); the unmatched AOD, BLH and RH (extracted from 1.0,

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0.125 and 2.5 degree grid data) and PM10 concentration (measured at a specific

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location) is an expected source of error, and averaging over space and time could

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result in better agreement between PM10*BLH*f(rh) and AOD (discussed above).

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– 2012 varied synchronously (Fig. 4c), and a stronger correlation (R2 = 0.53, P <

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0.0001 significance, n = 103, Fig. 4f) is found between them.

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6. Preliminary hypothesis about impact of EASM front

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It is well known that the shift of the winter and summer monsoon is a major

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characteristic of weather and climate over East Asia. Climatologically, the phasic

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northward progress of the summer monsoon front (SMF) experiences three times

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abrupt advance and four quiescent stages. SMF is located at the north part of south

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China during its first quiescent stage (May 16 to June 10, SMF1, Fig 5a), and then

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marches to the Yangtze River Basin, the Yellow River and Huai River Basin, and

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north China during its second (June 16 to July 5, SMF2), third (July 6 to July 20,

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SMF3) and fourth (July 21 to August 10, SMF4) quiescent stages, respectively (Wu et

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al., 2002). To facilitate the discussion, SMF0 (Apr 20 to May 15), a period with the

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same duration of but before SMF1, is defined to supply a background before the East

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Asia summer monsoon (EASM) developing.

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Monthly variation shows an abrupt increase of AOD over NCP from May to June

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(Fig. 4a). More specifically, there is an obvious AOD increase over NCP from SMF0

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(Fig. 6a) to SMF1 (Fig. 6b); meanwhile, the higher AOD (> 0.9, shaded with red) area

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over ECN experiences a further northward displacement from SMF1 (Fig. 6b) to

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SMF2 (Fig. 6c). Correspondingly, the PM10 concentration exhibits a comparably

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higher value from December to May (Fig. 2c, associated with additional emission

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ACCEPTED MANUSCRIPT from house heating in winter and contribution from dust in spring), followed by June

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with the highest PM10 concentration in summer (June, July and August). Similar

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variation for the one-year record of monthly PM2.5 concentration in 2014

324

(supplementary material 2) also indicated the highest June PM concentration in

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summer. More in detail, the difference between SMF1 and SMF0 shows a significant

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increase of PM2.5 concentration over the major south part of ECN (Fig. 7a), which is

327

consistent with the increase of multi-year averaged RH from SMF0 to SMF1 in this

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region (Fig. 7c). A comparison of the spatial distribution of PM2.5 and RH differences

329

shows that the area with a slight and initial RH increase (0 to 2%, shaded with green

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in Fig. 7c) seems like the area with a greater PM2.5 increase (generally > 15 µg m–3,

331

Fig. 7a). These AOD and PM variations could be interpreted by a preliminary

332

hypothesis of the possibly enhanced formation of the secondary aerosol (SOA)

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accompanied with the northward progress of EASM (as conceptually illustrated in Fig.

334

5b).

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The spatial displacement of SMF associated with EASM development can result

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in changes in the converging of precursor gases (of aerosol) with moisture introduced

337

by EASM into the region. The key point here is that during the drier period before

338

EASM prevailing (i.e., the winter and spring associated with presumably more

339

intensive anthropogenic emission), although the aerosol precursor gases is abundant in

340

the atmosphere, the water vapor is presumably in deficit over ECN and serves as an

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important rate control condition for SOA formation. In this context, northward

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introduction of the water vapor into ECN and increase of RH during the early phase of

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ACCEPTED MANUSCRIPT EASM development is crucial to SOA formation. When converging and mixing of the

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precursor gases of aerosol with the moisture from south occur, ECN becomes a good

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place with more efficient photochemical activity, leading to enhancement of NPS,

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SOA formation and hygroscopic growth. Indeed, the NPS events in urban Beijing

347

were usually associated with changes in wind directions (Zhang et al., 2011),

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implying that mixing of the precursor gases with moisture (occurred during

349

converging of different air masses) is favorable for photochemical activities and NPS,

350

which supports our hypothesis above. Such an enhanced SOA formation can

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potentially influence AOD and PM concentration. Here, PM2.5 concentration is used to

352

evaluate the PM variation associated with SOA formation because SOA should be

353

within the size range of fine particle.

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On the other hand, for the area of Guangdong Province (the most south of ECN,

355

nearby Hainan Island) with a significant RH increase from SMF0 to SMF1 (2% to 8%,

356

shaded with yellow to orange in Fig. 7c), the PM2.5 concentration decreases (Fig. 7a),

357

probably due to more efficient wet scavenging when RH increases further. This is

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confirmed by the shift from SMF1 to SMF2, accompanying with a general significant

359

increase of RH (> 10%, Fig. 7d) and a decrease of PM2.5 concentration (Fig. 7b) over

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the major area of ECN.

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Moreover, variation of Vis accompanied with the northward progress of EASM

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also supports our hypothesis. As Vis shows an interannual decreasing trend over ECN

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(Qu et al., 2013, 2015b), here the normalized Vis is calculated based on each station

364

during May 16 to August 10 (i.e., the period spans over the four quiescent stages of

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ACCEPTED MANUSCRIPT SMF) each year to assess the phasic variation of Vis due to the northward progress of

366

SMF. Our analysis finds that the south part of ECN experiences a Vis improvement

367

accompanied with the northward progress of SMF, while NCP (30–40° N and

368

110–125° E) experiences a Vis degradation during the same course (supplementary

369

material 5); the increase of RH and the decrease of surface wind speed

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(supplementary material 6, here wind speed is also normalized using the same method

371

for Vis) might be possible causes favorable for enhancement of NPS and SOA

372

formation as well as Vis degradation over NCP accompanied with the northward

373

progress of SMF.

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Based on these analyses, we can hypothesize the impact of EASM front on a

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possible enhancement of SOA formation, which contributes to the significant increase

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of PM2.5 concentration and the corresponding increase of AOD from SMF0 to SMF1

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over NCP.

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7. Conclusion

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In contrast to the lower surface PM concentration in summer, AOD shows an

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obvious increase in summer (June) compared with winter (December) over NCP.

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Several factors work in concert to result in this opposite seasonality of AOD and

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surface PM.

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(i) Increase of BLH, associated with more efficient transport and mixing of

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particles to a higher altitude, results in a higher extinction coefficient near

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and above the top of BLH and therefore, a higher AOD but a decrease of

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ACCEPTED MANUSCRIPT 386

surface PM concentration over NCP in June. (ii) Converging and mixing of the precursor gases of aerosol with the

388

moisture introduced by EASM, which subsequently results in an increase

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of RH and enhancement of NPS, SOA formation and hygroscopic growth

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(especially for sulfate as a major aerosol component).

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(iii) Emission from regional open stalk burning in the summer harvest season.

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(iv) The typical southeast and south wind and the mountains to the north and

394

west (generally ≥ 1500 meter above sea level) resulting in accumulation

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and restriction of pollutants within the NCP topographical "basin".

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BLH, RH in collaboration with PM concentration can well explain the multi-year

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averaged monthly variation of AOD. These factors need to be considered when

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investigating the climate effect of aerosol in the region.

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The increase of AOD and PM concentration over NCP in early summer can be

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attributed to possible enhanced new particle speciation and SOA formation during the

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early phase of EASM (section 6). The presumably intensive solar radiation, high RH

402

and high temperature over ECN in summer are all favorable for the enhancement of

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photochemical activity and SOA formation. However, the suggested hypothesis

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should be further investigated. Observation and study on the contribution of SOA to

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the total aerosol, on the possibly seasonal variation of aerosol components, as well as

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on influx and impact of the ocean originated materials (such as sea salt,

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dimethylsulfide (Ma et. al., 2005), etc.) accompanied with EASM should be helpful to

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ACCEPTED MANUSCRIPT improve our understanding in the future. Clarifying the variation of AOD and PM

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accompanied with the establishing and prevailing of EASM is potentially helpful to

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study the feedback and interaction between the increased aerosol loading and the

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variation of monsoon intensity in the region.

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Acknowledgments:

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Education’s 111 Project (B07036).

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This research is supported by NSFC 41276009 and Chinese Ministry of

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Boynard, A., Clerbaux, C., Clarisse, L., Safieddine, S., Pommier, M., Damme, M.V., Bauduin, S., Oudot, C., Hadji-Lazaro, J., Hurtmans, D., Coheur, P.-F., 2014. First simultaneous space measurements of atmospheric pollutants in the boundary layer from IASI: A case study in the North China Plain. Geophysical Research Letters 41, doi:10.1002/2013GL058333.

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Eck, T.F., Holben, B.N., Reid, J.S., Sinyuk, A., Dubovik, O., Smirnov, A., Giles, D., O’Neill, N.T., Tsay, S.-C., Ji, Q., Mandoos, A.A., Khan, M.R., Reid, E.A., Schafer, J.S., Sorokine, M., Newcomb, W., Slutsker, I., 2008. Spatial and temporal variability of column-integrated aerosol optical properties in the southern Arabian Gulf and United Arab Emirates in summer. Journal of Geophysical Research 113, D01204, doi:10.1029/2007JD008944.

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Engel-Cox, J.A., Holloman, C.H., Coutant, B.W., Hoff, R.M., 2004. Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality. Atmospheric Environment 38, 2495–2509.

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Hoff, R.M., Christopher, S.A., 2009. Remote sensing of particulate pollution from space: Have we reached the promised land? Journal of the Air & Waste Management Association 59, 645–675.Jung, J., Lee, H., Kim, Y.J., Liu, X., Zhang, Y., Gu, J., Fan, S., 2009. Aerosol chemistry and the effect of aerosol water content on visibility impairment and radiative forcing in Guangzhou during the 2006 Pearl River Delta campaign. Journal of Environmental Management 90, 3231–3244.

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Jung, J., Kim, Y.J., 2011. Tracking sources of severe haze episodes and their physicochemical and hygroscopic properties under Asian continental outflow: Long-range transport pollution, postharvest biomass burning, and Asian dust. Journal of Geophysical Research 116, D02206, doi:10.1029/2010JD014555.

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Kessner, A.L., Wang, J., Levy, R.C., Colarco, P.R., 2013. Remote sensing of surface visibility from space: A look at the United States East Coast. Atmospheric Environment 81, 136–147.

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Kong, W., Yi, F., 2015. Convective boundary layer evolution from lidar backscatter and its relationship with surface aerosol concentration at a location of a central China megacity. Journal of Geophysical Research 120, 7928–7940.

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Li, C., Mao, J., Lau, K.A., Chen, J., Yuan, Z., Liu, X., Zhu, A., Liu, G., 2003. Characteristics of distribution and seasonal variation of aerosol optical depth in eastern China with MODIS products. Chinese Science Bulletin 48, 2488–2495.

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Li, W.J., Shao, L.Y., Buseck, P.R., 2010. Haze types in Beijing and the influence of agricultural biomass burning. Atmospheric Chemistry and Physics 10, 8119–8130.

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Li, Z., Li, L., Zhang, F., Li, D., Xie, Y., Xu, H., 2015. Comparison of aerosol properties over Beijing and Kanpur: Optical, physical properties and aerosol component composition

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ACCEPTED MANUSCRIPT retrieved from 12 years ground-based Sun-sky radiometer remote sensing data. Journal of Geophysical Research 120, 1520–1535.

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Ma, Q., Hu, M., Zhu, T., Liu, L., Dai, M., 2005. Seawater, atmospheric dimethylsulfide and aerosol ions in the Pearl River Estuary and the adjacent northern South China Sea. Journal of Sea Research 53, 131–145.

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Mian, C., Paul, G., Stefan, K., Omar, T., Brent, N.H., Bryan, N.D., Randall, V.M., Jennifer, A.L., Akiko, H., Teruyuki, N., 2002. Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements. Journal of the Atmospheric Science, 59, 461–483.

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Qu, W.J., Arimoto, R., Zhang, X.Y., Zhao, C.H., Wang, Y.Q., Sheng, L.F., Fu, G., 2010. Spatial distribution and interannual variation of surface PM10 concentrations over eighty-six Chinese cities. Atmospheric Chemistry and Physics 10, 5641–5662.

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Qu, W., Wang, J., Gao, S., Wu, T., 2013. Effect of the strengthened western Pacific subtropical high on summer visibility decrease over eastern China since 1973. Journal of Geophysical Research 118, 7142–7156.

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Qu, W.J., Wang, J., Zhang, X.Y., Wang, D., Sheng, L.F., 2015a. Influence of relative humidity on aerosol composition: Impacts on light extinction and visibility impairment at two sites in coastal area of China. Atmospheric Research 153, 500–511.

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Qu, W., Wang, J., Zhang, X., Yang, Z., Gao, S., 2015b. Effect of cold wave on winter visibility over eastern China. Journal of Geophysical Research 120, doi:10.1002/2014JD021958.

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Smirnov, A., Holben, B.N., Dubovik, O., O'Neill, N.T., Eck, T.F., Westphal, D.L., Goroch, A.K., Pietras, C., Slutsker, I., 2002. Atmospheric aerosol optical properties in the Persian Gulf. Journal of Atmospheric Science 59 (3), 620–634.

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Sun, Y.L., Wang, Z.F., Fu, P.Q., Jiang, Q., Yang, T., Li, J., Ge, X.L., 2013. The impact of relative humidity on aerosol composition and evolution processes during wintertime in Beijing, China. Atmospheric Environment 77, 927–934.

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Wang, J., Christopher, S.A., 2003. Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies. Geophysical Research Letters 30(21), 2095, doi:10.1029/2003GL018174.

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Wang, K.C., Dickinson, R.E., Su, L., Trenberth, K.E., 2012. Contrasting trends of mass and optical properties of aerosols over the Northern Hemisphere from 1992 to 2011. Atmospheric Chemistry and Physics 12, 9387–9398.

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Wu, R.S., 2002. Principles of modern synoptic meteorology (in Chinese), 319 pp., Higher Education Press, Beijing.

487 488 489

Xia, X.A., Chen, H.B., Wang, P.C., Zhang, W.X., Goloub, P., Chatenet, B., Eck, T.F., Holben B.N., 2006. Variation of column-integrated aerosol properties in a Chinese urban region. Journal of Geophysical Research 111, D05204.

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Yang, K., Dickerson, R.R., Carn, S.A., Ge, C., Wang J., 2013a. First observations of SO2 from the

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Yang, Y.J., Fu, Y.F., Wu, B.W., Shi, C.E, Deng, X.L., Zhang, H., Zhang, Y., 2013b. Impacts of agricultural fire on aerosol distribution over East China during summer harvest time. Journal of Atmospheric and Environmental Optics 8(4), 241–252.

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Zhang, Y.M., Zhang, X.Y., Sun, J.Y., Lin, W.L., Gong, S.L., Shen, X.J., Yang, S., 2011. Characterization of new particle and secondary aerosol formation during summertime in Beijing, China. Tellus 63B, 382–394.

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Zhao, X.J., Zhao, P.S., Xu, J., Meng, W., Pu, W.W., Dong, F., He, D., Shi, Q.F., 2013. Analysis of a winter regional haze event and its formation mechanism in the North China Plain. Atmospheric Chemistry and Physics 13, 5685–5696.

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Figure captions:

503

Fig. 1.

The mean MODIS Terra AOD at 550 nm over China in (a) June and (b) December during 2000 to 2014. The AOD contrast is significant over NCP

505

(the area of 30–40° N and 110–125° E, indicated by a black box with the

506

North China Plain as a principal part).

Fig. 2.

(a) MODIS Terra monthly averaged AOD at 550 nm over NCP from January

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507

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2005 to December 2012. The red and green arrows indicate AOD in June

509

and December, respectively. (b) AERONET monthly averaged AOD

510

(interpolating using values at 440 nm and 675 nm) at Beijing (116.381° N,

511

39.977° E) from January 2005 to December 2012. The red and green arrows

512

indicate AOD in June and December, respectively. (c) Monthly PM10 mass

513

concentration in 34 major Chinese cities over NCP from 2005 to 2012. The

514

box-and-stem plots depict the minimum, the 1th, 5th, 25th, 50th (median),

515

75th, 95th, 99th percentile and the maximum for the PM10 concentration; the

516

square in the box depicts the arithmetic mean. The geometric mean of the

518 519

520

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monthly PM10 concentration for the 34 cities in June and December also presented. Those in June and December are shown in red and green, respectively.

Fig. 3.

(a) The difference of average boundary layer height (BLH, meter) at 14:00

521

local time between June and December (∆BLH = BLHJune – BLHDecember)

522

during 2000 – 2013. BLH in June is generally greater than BLH in

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ACCEPTED MANUSCRIPT 523

December by at least 350 meter over the AOD hotspots area from Shandong

524

Peninsula to the north of Yangtze River in eastern China. The black box

525

indicates NCP. (b) Vertical profile of the aerosol extinction coefficient at 532

526

nm (km

527

30–40° N and 110–120° E in June and December 2014. (c) The difference of

528

mean wind vector and relative humidity (RH) between June and December

529

(June minus December, ∆RH = RHJune – RHDecember) during 2000 – 2013 at

530

850 hPa (1475 gpm, geopotential height in meters) level, the white line

531

illustrates the zero line of ∆RH (i.e., the mean RH in June is equal to that in

532

December), the black box indicates NCP; the results at surface, 1000 hPa

533

(110 gpm), 925 hPa (762 gpm) and 700 hPa (3012 gpm) levels are similar

534

and not shown. The difference of RH generally shows a higher RH over the

535

AOD hotspots area in June compared with December. (d) The RH profile in

536

June and December over NCP during 2000 – 2013, a higher RH in June is

537

obvious from 1000 hPa to 300 hPa levels. (e) The monthly average BLH

538

over the area of 30–40° N and 110–120° E during 2000 – 2013. (f) same as

540

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, derived from CALIPSO level 3 allsky product) over the area of

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–1

(e) but for relative humidity (RH, %) at 1000 hPa, 925 hPa and 850 hPa levels.

Fig. 4.

(a) MODIS Terra monthly averaged AOD at 550 nm over NCP during

542

2001–2013. (b) Monthly product of PM concentration, boundary layer height

543

(BLH, at 14:00 local time) and RH correction factors (f(rh)) (PM*BLH*f(rh))

544

over NCP. (c) Time series of the monthly area averaged PM10*BLH*f(rh)

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ACCEPTED MANUSCRIPT and AOD over NCP during 2004 – 2012. (d) Linear fitting between the

546

monthly averaged AOD and PM10*BLH*f(rh) over NCP. (e) same as (d) but

547

for PM2.5. (f) same as (d) but for the monthly area averaged PM10*BLH*f(rh)

548

and AOD over NCP during 2004 – 2012.

549

Fig. 5.

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(a) Change of the summer monsoon front (SMF) illustrated by the average position of the 850 hPa level pseudoequivalent potential temperature θse =

551

340 K contour during 1971 – 1980 (follow Wu et al., 2002). Here SMF1,

552

SMF2, SMF3 and SMF4 are corresponding to May 16 to June 10, June 16 to

553

July 5, July 6 to July 20 and July 21 to August 10, respectively; the average

554

positions of SMF during these four quiescent stages are demonstrated (detail

555

in section 6 of the main text). (b) A conceptual illustration of the enhanced

556

formation of the secondary aerosol due to northward transport of the

557

moisture (as well as initial increase of relative humidity, RH) and subsequent

558

converging and mixing with the precursor gases of aerosol over eastern

559

China (ECN) during the early stage of the East Asia summer monsoon

560

(EASM), which results in more efficient photochemical activity. Further

562

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550

northward progress of EASM is associated with increased precipitation and more efficient wet scavenging, which result in decrease of the surface particulate matter (PM) concentration.

563

564 565

Fig. 6.

The mean MODIS Terra AOD at 550 nm over China during (a) Apr 20 to May 15 (SMF0), (b) the first quiescent stage of the summer monsoon front

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ACCEPTED MANUSCRIPT 566

(SMF1, May 16 to June 10), and (c) the second quiescent stage of the

567

summer monsoon front (SMF2, June 16 to July 5) in 2014. The black box

568

indicates NCP.

Fig. 7.

Difference of the surface PM2.5 concentration (µg/m3) in 142 Chinese cities

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569

(a) between the first quiescent stage of the summer monsoon front (SMF1,

571

May 16 to June 10) and Apr 20 to May 15 (SMF0); (b) between the second

572

quiescent stage of the summer monsoon front (SMF2, June 16 to July 5) and

573

SMF1. The magenta box indicates NCP. (c) and (d), same as (a) and (b) but

574

for the difference of NCEP RH at 1000 hPa level during 2000 – 2013, black

575

line illustrates the zero line of ∆RH, white box indicates NCP, values over

576

topography higher than 1500m (mostly the Tibetan Plateau) are masked out.

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ACCEPTED MANUSCRIPT 80°E

100°E

120°E

(a) 50°N 0.9 0.82 0.74

40°N

0.66 0.58 0.5

RI PT

0.42 0.34

30°N

0.26 0.18

20°N

80°E

100°E

120°E

M AN U

50°N

SC

0.1

40°N

30°N

(b) 0.9 0.82 0.74 0.66 0.58 0.5 0.42 0.34 0.26

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20°N

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0.18 0.1

ACCEPTED MANUSCRIPT

(a)

1.0 0.9 0.8 0.7 0.6 0.5 0.4

RI PT

MODIS AOD at 550 nm over NCP (unitless)

1.1

0.3

(b)

SC

1.4 1.2 1.0 0.8

M AN U

AERONET AOD at Beijing (unitless)

Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 1.6

0.6 0.4 0.2

0.0 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12

127

110

250

119

123

113

120

3

PM10 concentration (g/m )

(c)

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94.4

0 Jan-05

88.5

Jan-06

81.5

Jan-07

89.0

Jan-08

93.2

Jan-09

85.8

Jan-10

81.5

Jan-11

81.6

Jan-12

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(b)

Altitude (km)

5 4

Jun Day Jun Night

3

Dec Day Dec Night Jun Day

2 Jun Night

1

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Dec Day

Dec Night 0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 -1 Mean extinction coefficient at 532 nm (km )

–1100 –700 –350

50

450

800

1200 1550 1950 2350 2700 3100

ΔRH (%)

(c)

SC

ΔBLH (km)

Jun

60 50 40

M AN U

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P (hPa)

30

(d)

10

0

– 10 – 20 – 30

Dec

– 40

7.5 m/s

JUN

RH (%)

(f)

JUN DEC RH (%)

BLH (meter)

TE D

(e)

1000 hPa

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DEC

MAR

MAY

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JAN

JUL

SEP

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925 hPa 850 hPa JAN

MAR

MAY

JUL

SEP

NOV

0.8

ACCEPTED MANUSCRIPT 1.0

(a)

0.9

0.9

2

(d)

R = 0.90, R = 0.81, P < 0.0001, n = 12

AOD at 550 nm (unitless)

0.7 0.6 0.5

0.7 0.6 0.5 0.4

0.4 0.3 Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

0.3 160

Dec

180

200

RI PT

AOD at 550 nm (unitless)

0.8

0.8

220

240

260

280

300

3

PM10, BLH and f(rh) product ((g/m ) km)

(b)

0.9

2

R = 0.86, R = 0.74, P < 0.0005, n = 12

0.8

200

PM10, BLH and f(rh) product

150

PM2.5, BLH and f(rh) prodcut

Feb

Mar

Apr

May

Jun

Jul

0.7 0.6 0.5 0.4

Aug

Sep

Oct

Nov

SC

AOD at 550 nm (unitless)

250

100 Jan

(e)

M AN U

3

PM, BLH and f(rh) product ((g/m ) km)

300

0.3 140

Dec

160

180

200

220

240

260

3

PM2.5, BLH and f(rh) product ((g/m ) km)

1.6

300

1.4

250

1.2

150 100 50

1.0

1.2

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200

1.4

0.8 0.6 0.4 0.2

(f)

2

R = 0.73, R = 0.53, P < 0.0001, n = 103

1.0 0.8 0.6 0.4 0.2

0.0 100

150

200

250

300

350

3

PM10, BLH and f(rh) product ((g/m ) km)

EP

0 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12

AOD at 550 nm over NCP (unitless)

(C)

MODIS AOD at 550 nm over NCP (unitless)

350

1.8

AOD

PM10*BLH*f(rh)

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PM10, BLH and f(rh) product ((g/m ) km)

400

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Fig. 4

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SMF4

SMF2

SMF1

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SMF3

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(a)

→

→

→ → →

II. Further northward progress of EASM significant RH increase and more intensive precipitation more efficient wet scavenging decrease of surface PM concentration.

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→

→

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(b)

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I. Early stage of EASM moisture transported northward Converging with the precursor gases of aerosol over ECN initial increase of RH more efficient photochemical activity enhanced formation of the secondary aerosol.

Precursor gases of aerosol

Moisture associated with EASM

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(a)

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(b)

(c)

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100°E

120°E

(a) SMF1 – SMF0 May 16 to June 10 – Apr 20 to May 15

50°N

(c) SMF1 – SMF0 May 16 to June 10 – Apr 20 to May 15

# S S# # S

S # S# # S

30°N

20°N

80°E

100°E (b) SMF2 – SMF1 June 16 to July 5 – May 16 to June

40°N

S # S# # S # S S # S # S S# # S# S# S # S # # S S # # S SS # S# S# S# S# # S # S # S# # S # S S # S # S # S # # S # # S # # S # S # SS # S # S# # S S S S# S# S # S SS# # S# S # # S# S S# # SS # S# S# # S# S# # S # S S# S# # S S# S S# # S S# # Diff_PM2.5 S# S # S# # S S # S # S# # S S # S # S# # S # S # S # S S# concentration S # S # SS # S# # S # S S # S # S# # S S# # (μg/m3) S # S# S # S # S # 45 to 280 S # S # S # 30 to 45 S S # S# # S S# S # S # S # # 15 to 30 S # # S S # S # S # S # S # S # 0 to 15 S # S# # S# S S# # S S# – 15 to 0 S # S # S# # S – 30 to – 15 S # – 45 to – 30 S # – 230 to – 45

–10

–8

–6

–4

–2

0

2

ΔRH (%)

4

6

8

10

6

8

10

(d) SMF2 – SMF1 June 16 to July 5 – May 16 to June

20°N

AC C

EP

S #

# S S# # S

(μg/m3) 45 to 280 30 to 45 15 to 30 0 to 15 – 15 to 0 – 30 to – 15 – 45 to – 30 – 230 to – 45

TE D

50°N

30°N

120°E

Diff_PM2.5 concentration

SC

40°N

M AN U

# S S # S SS# # S# S # S# S # # S # S S# S# # S # S # S # S # S # S# # S # S SS# # S S # S # # S # # S # S# # S# S # S# # S S S S# S# S # S SS# # S# S # # S# S S# # SS # S# S# # S # S # S S# # S# # S S# S S# # S S# # S# S # S# # S S # S# # S # S S # S # S# # S # S # S # # SS S # S # S# # S # S # S # S S # S# S # S S# S # # S # S # S # S # S # S # S S # S# # S S# S # S # # S # S # S # S # S # S # SS S# # S# S # S # S # S# S# # S # S S# # S# # S S # S #

RI PT

S #

–10

–8

–6

–4

–2

0

2

ΔRH (%)

4

ACCEPTED MANUSCRIPT Highlights:

The AOD seasonality is distinct over NCP (maximum in June and minimum in

RI PT

December).  BLH, RH collaborate with PM concentration can well explain monthly AOD

variation.

SC

 June AOD increase over NCP relates to prevailing of the East Asia summer

AC C

EP

TE D

M AN U

monsoon.