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Characterization of Natural and Affected Environments

Spatial distribution of secondary organic aerosol formation potential in China derived from speciated anthropogenic volatile organic compound emissions Rongrong Wu, and Shaodong Xie Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b01269 • Publication Date (Web): 28 Jun 2018 Downloaded from http://pubs.acs.org on June 30, 2018

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Environmental Science & Technology

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Spatial distribution of secondary organic aerosol formation

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potential in China derived from speciated anthropogenic

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volatile organic compound emissions

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Rongrong Wu, Shaodong Xie *

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College of Environmental Sciences and Engineering, State Key Joint Laboratory of

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Environmental Simulation and Pollution Control, Peking University, Beijing, 100871, China

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* Corresponding author phone: 86-010-62755852; fax: 86-010-62755852; e-mail:

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[email protected]

1 ACS Paragon Plus Environment


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TOC/ Abstract Art

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ABSTRACT

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Fine particulate matter (PM2.5), largely composed of secondary organic aerosol (SOA), is

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currently one of the most intractable environmental problems in China. As crucial precursors for

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SOA, understanding the formation propensity of various volatile organic compound (VOC)

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species and sources is useful for pollution control. In this work, we estimated the SOA formation

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potential (SOAP) of anthropogenic VOC emissions based on an improved speciated VOC

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emission inventory, and investigated its distribution in China. According to our estimates,

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toluene had the largest SOAP, followed by n-dodecane, m/p-xylene, styrene, n-decane, and n-

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undecane, while passenger cars, chemical fiber manufacturing, asphalt paving, and building

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coating were the top five SOAP–contributing sources nationwide. The spatial distribution of

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SOAP in China shows a distinct pattern of high values in the southeast and low values in the

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northwest. Beijing–Tianjin–Hebei and surroundings, the Yangtze River Delta, Pearl River Delta,

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and Sichuan–Chongqing District were found to have the highest SOAP, particularly in urban

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areas. The major SOAP–contributing species and sources differed among these regions, which

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was attributed to local industrial and energy structures. Our results suggest that to mitigate PM2.5

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pollution in China, more efficient SOAP–based control measures should be implemented instead

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of current emissions-based policies, and VOC control strategies should be adapted to local

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conditions.



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1. Introduction

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Particulate pollution, characterized by high mass concentrations of fine particles (PM2.5)

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accompanied by low visibility, is one of the most intractable environmental problems in China.1–

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5

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well as regional and global climate,5–9 the Chinese government has implemented a series of

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control strategies to mitigate it.10 Due to these stringent control measures, ambient PM2.5

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concentrations have been significantly reduced in most Chinese cities over the past several years

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(annual average PM2.5 concentrations in 2016 were reduced by 34.7% compared to 2013

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level).11-13 However, greater effort is needed to diminish PM2.5 to a non-threatening level (i.e., an

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annual average of 10 µg m-3, as proposed by the World Health Organization 14). Data from 338

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monitoring sites in China showed that 75.1% were in non-attainment status in 2016, and the

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annual average PM2.5 concentration still exceeded the secondary ambient air quality standard

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limit (35 µg m-3) by about 34%. The highest PM2.5 concentration levels are found in cities such

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as Beijing–Tianjin–Hebei and surroundings (BTHS), the Yangtze River Delta (YRD), and the

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Sichuan–Chongqing economic zone (SC), which are the most developed regions in China. In

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2016, annual average PM2.5 levels in these regions were 71, 46, and 56 µg m-3, respectively.15

Considering the detrimental effects of particulate pollution on air quality and human health, as

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Secondary organic aerosols (SOAs), which are primarily formed through photooxidation of

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volatile and semi–volatile organic compounds, comprise a major fraction of the fine particle

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mass.16-19 Meanwhile, recent studies have noted that the extremely high PM2.5 mass

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concentrations in China during the pollution episodes were driven largely by SOA formation.1,2

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As important precursors of SOAs, volatile organic compounds (VOCs) are estimated to

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contribute about 16–30% or more of PM2.5 by mass through SOA production.2 Therefore, we can

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conclude that reducing VOC emissions would help mitigate particulate pollution in China.


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Intermediate VOCs (IVOCs) were also recently recognized as an important source of SOAs,20-23

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but we did not consider them in this work due to a lack of available IVOC emission inventory.

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More work measuring emissions of IVOCs is needed to fill this gap.

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Although approximately 90% of global VOC emissions are from biogenic sources,

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anthropogenic emissions often dominate those from vegetation in urban areas, where they have a

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more significant impact on the local ecosystem and climate.24 In China, anthropogenic VOC

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emissions have been extraordinarily high (29.94 Tg in 2013), and continue to increase year after

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year.25 At present, VOCs in China are poorly constrained. Although some VOC control measures

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were recently implemented, they are all emissions-weighted and do not account for the different

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potentials of various species for SOA formation, and thus may not efficiently mitigate PM2.5

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pollution in China. Therefore, thorough knowledge of the propensity of different VOC species

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and sources for SOA formation is urgently needed. However, few previous studies have provided

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such information, and the detailed characteristics of SOA formation potential (SOAP) in China

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are yet to be reported.

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This study is the second in a series of papers intended to develop a high-resolution speciated

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anthropogenic VOC emission inventory, and then to investigate the effects of VOC emissions on

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ozone (O3) and SOA formation. Here, we focus on the importance of VOCs to SOA formation.

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Based on the improved speciated anthropogenic VOC emission inventory developed for the year

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2013 in our previous study,26 we calculated the inventory-based SOAP using SOA yield method,

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and identified the major species and sources contributing to SOAP. We also investigated the

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spatial distribution of SOAP in China, and discuss the characteristics of SOAP in the most

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heavily polluted regions of China, i.e., BTHS, the YRD, Pearl River Delta (PRD) and SC. Our

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results provide useful insight for pollution control in China.



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2. Methods

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2.1 Speciated VOC emissions in 2013

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To obtain speciated VOC emissions, we should first determine bulk emissions. Using the bulk

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emission inventory and an integrated VOC source profile database, speciated VOC emissions

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were calculated by multiplying bulk emissions by the corresponding profiles, as formulated in Eq.

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(1). Details on the methodology used to establish the speciated inventory were provided in our

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previous study.26 Table S1 and Table S2 list the national and provincial speciated VOC

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emissions in 2013.

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Etotal, j = ∑i Ei ×fi, j

(1)

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where Etotal, j and Ei are the total emissions of species j from all source sectors and from source i,

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respectively, and fi, j is the weight percentage by mass of species j from source i.

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2.2 Calculation of SOAP

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The propensity of different VOC compounds to form SOA differs significantly, which can be

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scaled to the SOA yield. Thus, the SOAP of various species can be calculated using Eq. (2).

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SOAPi, j =Ei, j ×YSOA, j

(2)

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where SOAPi,j and Ei,j are the SOAP and emissions of species j from source i, respectively, and

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YSOA,j is the corresponding SOA yield of species j.

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In previous studies, the fractional aerosol coefficient (FAC) was generally used to calculate

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SOAP. FAC is a fixed value that cannot well represent real conditions. In this work, SOA yields

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were used instead, accounting for important parameters such as organic aerosol concentration,

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type of oxidant, and NOx concentration in the calculation.

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There are two parameterization approaches derived from the gas-particle partitioning theory,

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i.e., the two-product and volatility basis set (VBS) models. The two-product model can simulate 6 ACS Paragon Plus Environment

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most real atmospheric conditions, and has been widely used in previous experimental and

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modeling studies.27–31 Because of its simplicity, computational efficiency and good performance

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to a certain extent,32 the two-product approach was chosen to calculate the SOA yield of various

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VOC species, as formulated in Eq. (3). More information about this method can be found in Wu

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et al.32

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YSOA = ∆VOC =M0 1+Mi P,i + 1+M K ∆M

αK

αj KP,j

0 P,i

0 KP,j

(3)

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where ∆M is the mass of organic aerosol produced (µg m-3), ∆VOC is the amount of VOCs

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reacted (µg m-3), M0 is the mass concentration of organic aerosol, αi and αj are mass-based

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stoichiometric yields for semi-volatile species i and j, respectively, and KP,i and KP,j are their gas-

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particle partitioning coefficients.

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The values of αi, αj, KP,i and KP,j for various VOC species can be determined by fitting the

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smog chamber data reported in previous studies to Eq. (3).For species that lack experimental data,

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FAC values proposed by Grosjean and Seinfeld33 or SOA yields of species with similar

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structures were used instead.32 The value of M0 was estimated by multiplying the ambient PM2.5

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mass concentration in different provinces with the corresponding mass fraction of organic

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components. The annual average PM2.5 mass concentrations in 74 cities in China for the year

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2013 were collected from the website of the China National Environmental Monitoring Center,34

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and the average ratio of the organic fraction was determined to be 40% according to local

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measurements in four megacities in China.2 Notably, this ratio changes among seasons, regions,

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and pollution conditions.35 Therefore, setting it to a fixed value would certainly introduce

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uncertainties to the estimates. Further work is needed to improve its estimation. In addition, the

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NOx concentration can significantly affect SOA yields. VOCs have higher SOA yields under

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low-NOx conditions.36–40 In this work, we used the emissions ratios of VOCs/NOx to determine 7 ACS Paragon Plus Environment


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NOx concentration levels in Chinese cities, as described by Wu et al.32 Provincial NOx emissions

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were obtained from Zhao et al.41 The VOCs/NOx ratios varied from 0.5-1.8 in different provinces,

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considered high-NOx conditions.36,38,39

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Using this method, the SOA yields of 117 VOC species in China were determined. Table S1

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shows the nationally averaged SOA yields of different VOC species. It is obvious that aromatics

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and long-chain alkanes have greater propensity to form SOA than other species, which is

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consistent with existing knowledge.42-45 A comparison with the results derived from VBS

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approach is provided in Text S1 and Table S3 in the Supporting Information (SI).

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2.3 Spatial allocation

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Gridded SOAP were calculated first by distributing the provincial values to counties using

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source–specific spatial surrogates (including gross domestic product for transportation and

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solvent use, secondary industry output for industrial processes, population for stationary fossil

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fuel combustion, and sown area for biomass burning).25 County–level SOAP was further

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allocated to grids according to the grid–to–county area ratio and aggregated using Mapinfo.26

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Finally, the gridded SOAP was mapped at a resolution of 12 km × 12 km using ArcGIS.

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3. Results and Discussion

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3.1 SOAP at the national level

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3.1.1 By species

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According to our estimates, anthropogenic VOC emissions in China for 2013 had a potential to

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form 1471.1 Gg SOA. The uncertainty of this estimate is described in Text S2. As shown in

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Table 1, aromatics had the largest SOAP, with a contribution of 68.6%, followed by alkanes

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(27.1%). By contrast, the SOAP of alkenes and oxygenated VOCs (OVOCs) were relatively low,

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accounting for 2.4% and 1.9%, respectively, of the total SOAP.


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Table 1. SOAP of anthropogenic VOC emissions in China, 2013 Species

SOAP (Gg yr-1)

Percent (%)

Species

SOAP (Gg yr-1)

Percent (%)

Alkanes Alkenes Alkynes Aromatics

398.1 35.6 0.0 1008.5

27.1 2.4 0.0 68.6

Halocarbons OVOCs Others Total

1.0 27.9 0.0 1471.1

0.1 1.9 0.0 100

toluene n-dodecane m/p-xylene styrene n-decane n-undecane ethylbenzene o-xylene 1,3-butadiene methyl cyclohexane n-nonane n-heptane benzene m-ethyltolune n-octane 1,2,4-trimethylbenzene acetone hexanal o-ethyltoluene 3-methylheptane p-diethylbenzene 2,2,4-trimethylpentane 1,2,3-trimethylbenzene 2-methylheptane pentanal m-diethylbenzene

667.7 167.9 102.2 76.7 68.1 67.8 51.5 47.9 33.9 27.1 23.8 15.2 13.1 12.0 8.2 7.8 7.2 7.0 6.7 6.6 6.1 4.5 4.4 4.1 4.0 3.3

45.4 11.4 6.9 5.2 4.6 4.6 3.5 3.3 2.3 1.8 1.6 1.0 0.9 0.8 0.6 0.5 0.5 0.5 0.5 0.4 0.4 0.3 0.3 0.3 0.3 0.2

p-ethyltoluene isopropylbenzene 1,3,5-trimethylbenzene cyclopenane heptanal 2,3,4-trimethylpentane 4-methyl-2-pentanone octanal n-propylbenzene isovaleraldehyde 1-hexene nonanal methyl ethyl ketone decanal chrolobenzene cyclohexane isoprene o-diethylbenzene methylcylopentane methyl vinyl ketone 1,4-dichlorobenzene 1,3-dichlorobenzene 1,2-dichlorobenzene MTBE Others

2.7 2.5 2.4 2.3 2.1 1.7 1.7 1.5 1.3 1.3 1.2 1.1 1.0 0.8 0.6 0.6 0.5 0.3 0.2 0.1 0.1 0.1 0.1 0.1 0.0

0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.04 0.04 0.03 0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.0

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In terms of individual species, toluene was the largest SOAP contributor (45.4%), which

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was attributed to its large emissions and high SOA yield. n-Dodecane, m/p-xylene, styrene, n-

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decane and n-undecane also made significant contributions to SOA formation, accounting for 9 ACS Paragon Plus Environment


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11.4%, 6.9%, 5.2%, 4.6%, and 4.6%, respectively, of total SOAP. Ethylbenzene, o-xylene, 1,3-

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butadiene, methyl cyclohexane, n-nonane and n-heptane also had relatively high propensity to

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form SOA, as shown in Table 1. In total, these 12 species contributed 91.8% of total SOAP from

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28.3% of the national emissions. All of these compounds are aromatics and alkanes except 1,3-

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butadiene, which indicates that aromatics and long-chain alkanes are the major SOA precursors,

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in accordance with current knowledge.42–45

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It should be noted that species with large emissions do not necessarily have high SOAP,

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which is attributed to their propensity to form SOA, as scaled using the SOA yield in this work.

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For example, styrene had the largest emissions (7% of the total) but only contributed 5% of the

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total SOAP due to its low SOA yield (3.9%). By contrast, the emissions of n-dodecane (1.3%),

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n-decane (1.0%), and n-undecane (0.7) were relatively small, but due to their distinctly high

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SOA yields, (estimated to be 44%, 22%, and 33%, respectively), they constituted 11.4%, 4.6%,

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and 4.6% of the total SOAP.

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3.1.2 By source

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Industrial processes were the sector that contributed most to SOAP, constituting 40.1% of total

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SOAP, as shown in Figure 1(a), followed by transportation (23.6%) and solvent use (22.7%).

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The SOAPs of biomass burning (8.9%) and stationary fossil fuel combustion (4.6%) were

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relatively small. Among all subsectors, the petrochemical industry and on–road vehicles had the

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largest SOAP, accounting for 23.7% and 21.1% of the total, respectively. Other industrial

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processes, surface coating and asphalt paving also made significant contributions to SOA

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formation. Together, these sources constituted 37% of total SOAP.

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Figure 1(b) shows the SOAP-based source distribution at a more detailed level. It shows

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that passenger cars (PCs), chemical fiber manufacturing, coke production, asphalt paving,


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building coating, household liquefied petroleum gas (LPG) combustion, cement production,

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motorcycles (MCs), rubber products, and paint and ink manufacturing were 10 classes with the

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greatest SOAP. They contributed 62.2% of the national SOAP in total. More than 60 remaining

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sectors constituted only 37.8% of the total SOAP, which indicates that they had little effect on

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SOA formation. Thus, to mitigate the particulate pollution in China efficiently, these sources of

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VOC emissions should be preferentially controlled. 8.9%

4.6% 3.2% 2.5% 3.4%

7.1%

7.1%

7.4%

23.6%

4.9%

6.7% 21.1%

14.4% 4.7%

23.7%

4.6% 3.9% 3.5% 2.9% 2.5% 2.5% 2.3% 2.2%

13.4% 40.1%

22.7% 7.1%

16.5%

(a) major and subsectors

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28.3%

(b) sector branches

Transportation

Biomass burning

Fossil fuel

on-road fossil_power pesticides PCs chemical fiber coking

off-road biomass_open fossil_heat fossil_domestic printing asphalt paving asphalt paving cement building coating MCs LPG_domestic rubbers

Industiral processes biomass_domestic petrochemical surface coating paint and ink plastic biomass_domestic

Solvent use fossil_industry other industries other solvent refinning vehicle coating others

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Figure 1. Source distribution of SOAP in China, 2013. Sectors with contribution ratios less than

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2% are not labeled due to limited space.

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3.2 SOAP in typical regions

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Figure S1 shows the provincial SOAP and the corresponding source distribution in 2013. Both

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SOAP and its distribution varied significantly among regions. BTHS (including Beijing, Tianjin,

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Hebei, Shandong and Henan Province), the YRD (including Shanghai, Jiangsu and Zhejiang

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Province) and the PRD (referring to Guangdong Province in this study) had much larger SOAP 11 ACS Paragon Plus Environment


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values than other regions. In fact, BTHS, the YRD, the PRD, and the SC suffer from the most

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severe particulate pollution in China. To obtain useful information for pollution control, further

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investigation of the characteristics of SOAP in these regions is discussed in the following

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sections.

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3.2.1 SOAP in the BTHS

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In 2013, the BTHS region showed a propensity to form 354.4 Gg of SOA, accounting for 24% of

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the national SOAP, along with 26% of anthropogenic VOC emissions. As shown in Figure 2,

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aromatics were always the predominant contributors to SOAP in the four regions, followed by

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alkanes. These classes constituted 68–72% and 24–28%, respectively, of the regional SOAP.

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Figure 2 also illustrates the source distributions of SOAP. In the BTHS region,

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petrochemical industries (24.9%) and on-road vehicles (24.2%) made the largest contributions to

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SOA formation, followed by other industrial processes, surface coating and asphalt paving. More

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specifically, passenger cars (18.1%) represented the subsector with the largest SOAP, followed

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by coke production (8.4%), rubber product manufacturing (8.4%), asphalt paving (7.3%) and

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building coating (5.5%), as shown in Table S4.

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Figure 3 shows the top 5 species in terms of SOAP and the corresponding source

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distributions in various regions. In BTHS, toluene, n-dodecane, m/p-xylene, styrene and n-

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undecane were the top 5 species, accounting for 43.1%, 11.0%, 7.2%, 5.2%, and 4.7%,

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respectively, of the total SOAP. Toluene was sourced mainly from on-road vehicles (29.4%), as

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well as other industrial processes (21.3%), petrochemical industries (19.8%) and surface coating

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(12.0%). Emissions of n-dodecane was dominated by other industrial processes (46.7%) and

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asphalt paving (35.9%), followed by on-road vehicles with a contribution of 12.6%. For m/p-

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xylene, surface coating, petrochemical industries and on-road vehicles were the major


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contributors to emissions. As a commonly used chemical, nearly 70% of styrene was contributed

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from petrochemical industries. n-Undecane was mainly emitted from asphalt paving, other

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industrial processes, petrochemical industries and on–road vehicles.

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In conclusion, the BTHS region accounted for 24% of the SOAP in China in 2013. Toluene,

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n-dodecane, m/p-xylene, styrene and n-undecane were the key species contributing to SOAP,

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while passenger cars, coke production, rubber product manufacturing, asphalt paving and

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building coating were the major sources. Therefore, to efficiently reduce SOA formation in this

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region, we suggest listing these species and sources as control priorities.

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3.2.2 SOAP in the YRD

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The SOAP in the YRD was estimated to be 331.5 Gg in 2013, contributing 23% of the national

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SOAP with 18% of VOC emissions .Petrochemical industries (38.6%) were the greatest

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contributor to SOAP in this region, followed by surface coating (17.0%) and on–road vehicles

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(13.3%), as shown in Figure 2. In addition, other asphalt paving (8.6%) and industrial processes

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(6.9%) played important roles in SOA formation. Among all subsectors, chemical fiber

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manufacturing (22.6%) had the largest SOAP, followed by passenger cars (9.2%), asphalt paving

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(8.6%), building coating (8.0%) and household LPG combustion (4.1%) (see Table S4).

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Compared to BTHS, the petrochemical industry and surface coating made greater contributions

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to SOAP in the YRD, which is attributed to the well-developed organic synthesis industry (e.g.,

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chemical fiber, paint and ink manufacturing) and associated huge consumption of solvents.

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Because both the petrochemical industry and surface coating involve the use of numerous

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aromatic components, aromatics in this region accounted for a higher SOAP contribution

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proportion than in the BTHS.



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The top 5 species in terms of SOAP in this region were toluene (47.8%), n-dodecane

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(9.9%), m/p-xylene (7.3%), styrene (5.6%) and ethylbenzene (4.7%). As illustrated in Figure 3,

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the source distributions of these species were quite different from those in BTHS except for n-

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dodecane and styrene. For example, more than half of toluene was from the petrochemical

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industry in the YRD, while in BTHS industry accounted for only 19.8% of toluene emissions.

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Although surface coating was also the predominant contributor to m/p-xylene (57.3%) in this

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region, its contribution proportion was much larger than that in the BTHS (30.6%). These results

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were largely attributed to the booming organic synthesis industry and extensive solvent use in the

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YRD.

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In general, the YRD region contributed 18% of national SOAP in 2013. Toluene, n-

240

dodecane, m/p-xylene, styrene and ethylbenzene were the key species, while chemical fiber

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manufacturing, passenger cars, asphalt paving, building coating and household LPG combustion

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were the predominant sources of SOA formation in this region. Our results indicate that it would

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be more efficient to mitigate particulate pollution in the YRD by reducing the VOC emissions

244

associated with above sources and species.

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3.2.3 SOAP in the PRD

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The SOAP in the PRD region was estimated to be 156.8 Gg, constituting 10.7% of the national

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total, in a region with 9.3% of the total VOC emissions. Surface coating was the largest

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contributor to SOAP in this region, followed by petrochemical industries and on-road vehicles.

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These sources constituted 24.2%, 21.1%, and 16.5%, respectively, of the regional SOAP. The

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SOAP contribution of household fossil fuel combustion, mainly dominated by LPG combustion,

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was markedly increased in the PRD (11.2%) compared to other regions (less than 5%), probably

252

because LPG is the major residential energy source in this region. According to statistical data,


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LPG consumption in Guangdong Province is the highest in China, and source apportionment

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results showed that LPG was one of the major VOC sources in PRD cities.46,47 Among all

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subsectors, building coating (14.5%) and household LPG combustion (11.2%) were the largest

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SOAP contributors in this region, followed by motorcycles (7.2%), asphalt paving (6.9%) and

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passenger cars (6.2%), as shown in Table S4. Notably, surface coating made a much greater

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contribution to SOA formation in the PRD than in other regions, which is closely tied to the local

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industrial infrastructure and development. The high content of aromatics in solvents led to the

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increased contribution from aromatics in this region compared to other areas.

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In terms of key species, toluene was the greatest SOAP contributor (39.8%), followed by n-

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dodecane (10.1%), m/p-xylene (9.3%), styrene (9.1%), and n-decane (6.1%). However, in

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contrast with other regions, toluene in the PRD was sourced mainly from surface coating

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(30.1%), rather than on-road vehicles (20.3%) or petrochemical industries (20.2%). In addition,

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household fossil fuel combustion (11.3%) contributed a larger proportion than in other regions.

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Despite the similarity in the distributions of m/p-xylene and styrene in the PRD and YRD,

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household fossil fuel combustion made greater contributions to emissions in the PRD. These

268

findings are consistent with the source distribution of SOAP. The emissions of n-dodecane were

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also dominated by other industrial processes (37.1%) and asphalt paving (37.1%), similar to our

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results in the other two regions. Household fossil fuel combustion (33.4%) was the largest

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contributor to n-decane emissions, followed by asphalt paving (14.7%), industrial fossil fuel

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combustion (14.1%), and printing and dying (9.5%). It is apparent that household fossil fuel

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combustion, in particular LPG combustion, plays a more important role in SOA formation in the

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PRD.


2.7 1.5 1.4 3.1 3.9

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x10


24.2

27.1

0.1 2.3

24.9 10.7

2.5 1.7

67.5

25.2

50

100

150

200

250

300

350

400

3.8

450

0

0

4.1 2.2

BTHS: 354.4 Gg

18.4

12

7.3

1.9 2.2

x10

6.5

13.3

38.6

Chemical distribution(%) alkanes alkenes alkynes aromatics 1.0 0.0 OVOCs others

50

15.4

1.0 0.0

3.0

17.0

100

18.8 19.2

6.9

SC: 70.3 Gg

150

5.3

3.2 8.6

YRD: 331.5 Gg 2.6

200

1.3

1.4

300

0.1 2.5

24.2

250

28.2

11.2

67.9

4.9 1.6

PRD: 156.8 Gg

1.8

1.8

71.8 26.4

16.5 21.1

Source contribution(%) on-road vehicles off-road transportation biomass open burning biofuel combustion industrial combustion power generation heat supply residential combustion petroleum industry other industrial process pesticide use printing and dying asphalt paving surface coating other solvent use

1.3 5.7

24.2 5.2

275

70.5

6.9

276

Figure 2. Chemical and source distributions of SOAP in four typical regions of China. Sectors with contribution ratios less than 1%

277

are not labeled due to limited space. The graphics of spatial distribution of AOD in this figure was created using ArcGIS software by Esri. ArcGIS®

278

and ArcMap™ are the intellectual property of Esri and are used herein under license.


Page 17 of 34


2.1% 4.1% 3.4% 3.8%

6.8%

4.1%

4.4% 16.5%

29.4%

46.7%

20.4%

12.6%

BTHS

20.0%

8.4%

19.6%

29.6% 19.8%

12.0% 21.3%

26.1%

n-dodecane

3.5%

e n e l y h t e

4.6%

toluene

2.3%

styrene

m/p-xylene

7.3%

2.8%

2.1%

8.5%

17.0%

31.5%

YRD

n-undecane

3.5%

15.2% 14.4%

3.2%

23.0%

69.0%

30.6%

35.9%

42.6%

7.5%

11.0%

8.0%

5.1%

51.7% 15.6%

72.2%

57.3%

46.7%

47.7%

4.7% 3.1%

toluene

n-dodecane

5.2% 2.5%

m/p-xylene

PRD

6.4%

6.2%

15.6% 20.3%

37.1%

13.6%

a

14.1%

28.7%

11.4%

8.5%

11.3%

10.2%

33.4%

30.1%

6.0% 52.8%

37.1%

14.7%

56.9% 3.5% 3.5%

e n e l y h t e

6.1%

n-dodecane

toluene

m/p-xylene

8.9%

3.2%

29.6%

SC

64.2% 16.8%

19.5%

6.9%

6.3%

9.3%

13.3%

19.7%

20.5%

13.6%

10.1% 5.1% 20.9%

18.3%

42.8%

off-road transportation heat supply printing and dying

m/p-xylene

1284 0

biomass open burning residential combustion asphalt paving

3

3

1284 0

n-undecane biofuel combustion petroleum industry surface coating

x10

n-dodecane

x10

3

x10

3

x10

3

x10

279

on-road vehicles power generation pesticide use

1284 0

27.3%

5.6%

37.7%

53.6%

14.0%

toluene

9.5%

n-decane

styrene

2.6% 2.1%

2.6%

1284 0

a

2.1%

20.2%

3.2%

ethylbenzene

4.6% 3.6%

11.3%

styrene

1284 0

o-xylene industrial combustion other industrial process other solvent use

280

Figure 3. Source distribution of top 5 species in terms of SOAP in four regions. Sectors with

281

contribution ratios less than 2% are not labeled due to limited space.



282

In summary, the PRD region made up 10.7% of the national SOAP in 2013. Toluene, n-

283

dodecane, m/p-xylene, styrene and n-decane were the crucial species and building coating,

284

household LPG combustion, motorcycles, asphalt paving, and passenger cars were the crucial

285

sources of SOAP in this region. Hence, to mitigate particulate pollution, VOC emissions controls

286

in the PRD region should be targeted to these key species and sources.

287

3.2.4 SOAP in the SC

288

The SC region was estimated to have a potential to form 70.3 Gg of SOA, responsible for 4.8%

289

of total SOAP in China, with 5% of national VOC emissions. As shown in Figure 2, on–road

290

vehicles (25.2%) had the largest SOAP in this region, followed by other industrial processes

291

(19.2%), surface coating (18.8%), and petrochemical industries (15.4%). Interestingly, household

292

biomass combustion made a much larger contribution to SOAP (6.5%) in the SC region than in

293

other three regions (1.0–2.7%). Among all subsectors, passenger cars were the largest SOAP

294

contributor (with a contribution of 17.6%). In addition, building coating (9.4%), cement

295

production (8.0%), coke production (5.5%), vehicle manufacturing (5.4%), asphalt paving

296

(5.3%), motorcycles (4.4%), and household crop residue combustion (4.2%) also made important

297

contributions to SOA formation in this region, as shown in Table S4. .We found that the key

298

sources of SOAP in SC differed somewhat from those in other regions, with the most obvious

299

discrepancy being that other industrial processes (mainly cement production and coke production)

300

and household biomass combustion made larger contributions to SOA formation, which is

301

related to the local industries and energy sources.

302

Toluene was also the largest SOAP contributor in the SC region, followed by n-dodecane,

303

m/p-xylene, n-undecane and o-xylene. They constituted 44.6%, 13.6%, 7.6%, 4.9%, and 3.9% of

304

the total SOAP. As depicted in Figure 3, the source distributions of toluene, n-dodecane, and


Page 18 of 34

Page 19 of 34


305

m/p-xylene in this region were similar to those in other regions, with the exception of higher

306

contribution from other industrial processes. About 38% of n-undecane emissions were from

307

other industrial processes, followed by on-road vehicles (19.7%) and asphalt paving (18.3%).

308

Surface coating was the predominant source of o-xylene, contributing 42.8% of its emissions.

309

In general, the SC region constituted 4.8% of SOAP in China in 2013. Toluene, n-dodecane,

310

m/p-xylene, n-undecane and o-xylene, and passenger cars were the key species to SOAP, and

311

building coating, cement production, coke production and vehicle manufacturing were the main

312

sources. Based on these results, we believe that it would be more efficient to mitigate particulate

313

pollution in the SC region by reducing the emissions of these key species and sources.

314

3.3 Spatial distribution of SOAP

315

3.3.1 At the national level

316

The spatial distribution of SOAP at a resolution of 12 km × 12 km is illustrated in Figure 4(a),

317

which shows that southeastern China had much higher SOAP than northwestern area. The

318

coastal regions had the greatest SOAP intensity (~139 kg km-2 or more). By contrast, except for

319

some parts of Xinjiang and Gansu, the SOAP intensity in west China was generally lower than

320

6.9 kg km-2. The BTHS, YRD, PRD, SC, as well as the Wuhan and Changzhou–Zhuzhou–

321

Xiangtan metropolitan zones, had higher SOAP than other regions of China. There regions are

322

more likely to suffer from severe particulate pollution due to their high propensity to form SOA,

323

which is consistent with the high PM2.5 concentrations in these areas, as shown in Figure 4(b).

324

3.3.2 At the regional level

325

To better understand the spatial distributions of SOAP in the four typical regions, we conducted

326

in-depth analyses, described in this section.



327

(1) The BTHS region. As shown in Figure 4(A), the gridded SOAP values of cities in the

328

BTHS region were greater than 50 Mg, except for Chengde, Zhangjiakou, Baoding, Sanmenxia,

329

Zhumadian, Xinyang, Luoyang, and Nanyang. In south Beijing, south Tianjin, central Hebei,

330

north Henan, and most parts of Shandong Province, the gridded SOAPs were greater than 100

331

Mg, particularly in urban areas, such as Beijing, Tianjin, Shijiazhuang, Jinan, and Zibo. The

332

gridded SOAP values in these cities exceeded 200 Mg, which was largely attributed to high local

333

VOC emissions intensities. The grid with the largest SOAP was found in Qingdao City, which

334

reached 5.33 Gg.

335

(2) The YRD region. The gridded SOAP values of most cities in this region were greater

336

than 50 Mg, as shown in Figure 4(B). The central area had higher SOAP than other parts of the

337

YRD, particularly in Shanghai, Nanjing, Yangzhou, Zhenjiang, Changzhou, Suzhou, Wuxi,

338

Jiaxing, Huzhou, Hangzhou, Ningbo, Shaoxing, Taizhou and Wenzhou, where the gridded

339

SOAP exceeded 200 Mg. The most developed district, Pudong New Area, contributed more than

340

50% of Shanghai’s anthropogenic VOC emissions, with the highest gridded SOAP (7.92 Gg) in

341

the YRD region.

342

(3) The PRD region. As shown in Figure 4(C), the gridded SOAP values in most cities in

343

this region were less than 100 Mg except in the central region, including mainly Guangzhou,

344

Foshan, Dongguan, Shenzhen and Zhongshan. These cities had the highest propensity to form

345

SOA in the PRD. Their gridded SOAP exceeded 200 Mg. Jieyang, Shantou and south Maoming

346

also had high SOAP, with gridded values in the range of 100-200 Mg. In addition, some high

347

points were observed in the urban areas of Huizhou, Maoming, Zhaoqing, and Shaoguan City.

348

Within this region, the largest gridded SOAP value was found in urban Guangzhou, reaching

349

3.65 Gg.


Page 20 of 34

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350

(4) The SC region. It is evident that the SOAP of SC district was about half to one order of

351

magnitude smaller than those of the other three regions, which can be attributed to the less

352

developed economy of this region (thus less VOC emissions). As shown in Figure 4(D), the

353

gridded SOAPs of the western Sichuan Basin, including Ngawa, Garze, Liangshan and

354

Panzhihua, were less than 5 Mg. By contrast, SOAP increased to 20 Mg grid-1 or more in the

355

eastern part of the basin. This is because the western SC region is a mountainous and relatively

356

undeveloped area, while the eastern part, including two metropolises of Chengdu and

357

Chongqing, is the political and economic center of this region, with a dense population and high

358

rate of vehicle ownership. Consequently, Chengdu and Chongqing had the largest SOAP in this

359

region, particularly among urban areas (with gridded SOAP exceeding 100 Mg). In addition,

360

high points were found in Deyang, Mianyang, Zigong, Changshou County and Fuling.

361

According to our estimates, the largest gridded SOAP value was found in urban Chengdu, at 712

362

Mg.

363

In conclusion, urban areas had greater SOAP than other parts, and thus a higher risk for

364

particulate pollution. Therefore, it is more critical to implement pollution control measures in the

365

urban areas.



366


Page 22 of 34

Page 23 of 34


367

Figure 4. Spatial distributions of (a) SOAP and (b) satellite–derived PM2.5 mass concentrations

368

(dust and sea-salt removed) in China, 2013. The satellite–derived PM2.5 data were provided by

369

van Donkelaar et al. on the website at http://fizz.phys.dal.ca/~atmos/martin/?page_id=140. The

370

graphics in each section were created using ArcGIS software by Esri. ArcGIS® and ArcMap™

371

are the intellectual property of Esri and are used herein under license.

372

3.4 Implications for SOAP-based VOC control strategies in China

373

Table S5 lists the top 20 VOC species in terms of emissions and SOAP. The order of species in

374

terms of SOAP differed significantly from that of emissions, which is attributable to differences

375

in SOA yield among species. Therefore, VOC control strategies based on SOAP differ

376

significantly from those based on emissions. From the perspective of emissions, styrene, toluene,

377

m/p-xylene, benzene, ethylene and the other 15 high–emissions species should be targeted. If

378

emissions of these compounds were reduced to zero without any offset, it would lead to a VOC

379

emissions reduction of 60.4% and a SOAP reduction of 65.7%. The efficiency of an emissions-

380

based strategy for SOAP reduction is 0.053 g SOAP/g. From the perspective of SOAP, toluene,

381

n-dodecane, m/p-xylene, styrene, n-decane and other 15 major SOAP contributors should be

382

controlled preferentially. If releases of these compounds were reduced to zero without any offset,

383

it would reduce total SOAP by 96.3% with a VOC emissions reduction of 39.7%. Thus, when

384

implementing SOAP-based control measurements, a 1g VOC reduction would lead to a 0.12g

385

SOAP reduction. Note that this comparison was made under the assumption that emissions

386

would be reduced completely. Accounting for many other factors, such as technological

387

feasibility and economic costs, reducing emissions of any VOC compounds will not necessarily

388

lead to a proportional reduction of SOAP. It is nonetheless obvious that SOAP-based control

389

strategies are more efficient than emissions-based policies in terms of reducing SOA formation. 23 ACS Paragon Plus Environment


Page 24 of 34

390

Considering its efficiency in mitigating secondary particulate pollution, we suggest that

391

SOAP-based VOC control strategies should be implemented instead of the current emissions-

392

based regulatory policies. Due to the different industrial and energy structures among regions in

393

China, control targets also differ, as noted above. Table 2 summarizes the VOC species and

394

sources that should be controlled preferentially at the national and regional levels based on our

395

results. Some control measures that play a role in mitigating particulate pollution may be

396

ineffective at reducing O3 pollution.48,49 Therefore, we conducted a comparison of control

397

suggestions for O3 and SOA formation, and propose O3/PM2.5 synergistic control strategies based

398

on our results (see Text S3, Table S6, and Figure S2). In addition, SOAP varies seasonally due to

399

temporal variation in anthropogenic VOC emissions, as shown in Figure S3 and Figure S4.

400

However, the discrepancies among seasons were very small because of little monthly variation in

401

emissions from industrial processes, transportation and solvent use, which were the major

402

contributors to SOAP (see Text S4 for details).

403

Table 2. Suggested VOC emission control targets in different regions of China No.

Nationwide

BTHS

YRD

PRD

SC

Species 1

toluene

toluene

toluene

toluene

toluene

2

n-dodecane

n-dodecane

n-dodecane

n-dodecane

n-dodecane

3

m/p-xylene

m/p-xylene

m/p-xylene

m/p-xylene

m/p-xylene

4

styrene

styrene

styrene

Styrene

n-undecane

5

n-decane

n-undecane

ethylbenzene

n-decane

o-xylene

Source sectors 1

passenger cars

passenger cars

chemical fiber manufacturing

building coating

passenger cars

2

chemical fiber manufacturing

coke production

passenger cars

household LPG combustion

building coating


Page 25 of 34


3

coke production

rubber product manufacturing

asphalt paving

motorcycles

cement production

4

asphalt paving

asphalt paving

building coating

asphalt paving

coke production

5

building coating

building coating

household LPG combustion

passenger cars

vehicle manufacturing

404

Lastly, we note that SOAP is used in this work to quantify the importance of different VOC

405

species and sources to SOA formation. It cannot be used as a metric for measuring actual SOA

406

production under real atmospheric conditions. We used SOAP here to identify the major VOC

407

contributors to SOA formation in China, which might provide useful insights for particulate

408

pollution control in China.



409

Supporting Information

410

The Supporting Information is available free of charge on the ACS Publications website.

411

Additional information on VBS approach and its comparison with two-product model,

412

uncertainty analysis, comparison of SOAP– and OFP–based control strategies, and temporal

413

characteristics of SOAP; Tables showing speciated VOC emissions at the national and province

414

level, comparison of SOA yields calculated by two-product and VBS models, source

415

distributions of SOAP in four typical regions, top 20 species in terms of emissions and SOAP,

416

and top 20 species in terms of SOAP and OFP; Figures showing SOAP and the corresponding

417

source distribution in different provinces of China, source distributions in terms of SOAP and

418

OFP, monthly variation profiles and Monthly SOAP in China.

419

Author Information

420

Corresponding Authors: Shaodong Xie

421

Phone: 86-010-62755852; fax: 86-010-62755852; e-mail: [email protected]

422

Present Address: Room 402, Environmental Building, College of Environmental Sciences and

423

Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control,

424

Peking University, No.5 Yiheyuan Road, Haidian District, Beijing, 100871, China

425

Notes: The authors declare no competing financial interest.

426

Acknowledgements

427

This work received funding from the National Natural Science Foundation as part of the key

428

project entitled “The development and validation of emission inventories of anthropogenic

429

volatile organic compounds in the Beijing–Tianjin–Hebei region, China” (No. 91544106), and

430

from the National Air Pollution Prevention Joint Research Center as part of the Premier Fund 26 ACS Paragon Plus Environment

Page 26 of 34

Page 27 of 34


431

Project named “The research of characteristics, emission reduction and regulatory system of

432

volatile organic compounds (VOCs) in key sectors” (No. DQGG0204).



433

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