Molecular distributions of dicarboxylic acids , oxocarboxylic acids , and α-dicarbonyls in PM 2

20 Daytime and nighttime fine particulate matter (PM2.5) samples collected at Mt. Tai in the North China Plain (NCP) during summer 2014 were analyzed for dicarboxylic acids and related compounds (oxocarboxylic acids and α-dicarbonyls). The total concentrations of dicarboxylic acids and related compounds were 1050 ± 580 ng m -3 and 1040 ± 490 ng m -3 during the day and night time, respectively. Although these 25 concentrations were about 2 times lower than similar measurements in 2006, the 1 5 Yanhong Zhu 1 , Lingxiao Yang 1,6* , Jianmin Chen 1,5,6 , Kimitaka Kawamura 3,a , Mamiko Sato 3 , Andreas Tilgner 4 , Dominik van Pinxteren 4 , Ying Chen 4,b , Likun Xue 1 , Xinfeng Wang 1 , Hartmut Herrmann 4,2,1 , Wenxing Wang 1 Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1240 Manuscript under review for journal Atmos. Chem. Phys. Discussion started: 25 January 2018 c © Author(s) 2018. CC BY 4.0 License.


Introduction
Fine particulate matter (PM 2.5 ) is an atmospheric pollutant of particular concern due to its contribution to visibility degradation (Ghim et al., 2005;Watson, 2002), exacerbation of respiratory diseases (Davidson et al., 2005), and modification of 25 climate (Sloane et al., 1991).In recent years, haze frequently occurred in China and has received increasing attention due to its serious impact on air quality and human health (Mu and Zhang 2013;Guo et al., 2014;Huang et al., 2014;Wang et al., 2014).VOC samples were identified and quantified by gas chromatography equipped with electron capture detection (ECD), flame ionization detection (FID), and mass spectrometer detection (MSD).Detailed descriptions about the chemical analysis have been presented in Blake et al. (1994) and Simpson et al. (2010).

WRF Model
The boundary layer heights around Mt. Tai during the campaign were calculated using Weather Research and Forecasting Model (WRF V3.5.1) (Skamarock et al., 2005;Wang et al., 2007).In this study, the Yonsei University (YSU) boundary layer scheme (Hong et al., 2006) was used, which can reasonably represent the daytime 10 boundary layer structure (Hu et al., 2013).Although the model may have lower confidence about the nighttime boundary layer height estimation (Hu et al., 2013), this insignificantly influenced our analysis and conclusion because the nighttime boundary layer was always well below the measurement site.Previous studies also reported that the WRF model can capture the boundary layer structure and local circulation over the 15 NCP mountainous regions during summer (Chen et al., 2009).More details of the model configurations were given in Chen et al. (2016).

Analytical procedures
Aliquots of the aerosol filter samples were extracted by Milli Q water under ultrasonications.The extracts were concentrated by a rotary evaporator under vacuum.

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The concentrates were reacted with 14% BF 3 /n-butanol to convert to dibutyl esters and butoxy acetals.The derivatives were dissolved in n-hexane and analyzed by an Agilent 6890 gas chromatograph (GC) installed with a split/splitless injector (250 °C ), fused silica capillary column (HP-5, 0.2 mm × 25 m, film thickness 0.5 μm), and a flame ionization detector (FID).Identification of each compound was based on a 25 comparison of retention times of GC peaks with those of authentic standards and confirmed by GC/mass spectrometry.Recoveries were 77% for oxalic acid and > 86% for malonic, succinic, and adipic acids.Kawamura and Yasui (2005) reported of the trajectories.The mean transport pathway and corresponding total concentration of dicarboxylic acids and related compounds for every cluster are displayed in Figure 1.The total concentrations of dicarboxylic acids and related compounds were the greatest in clusters 2 and 4. The source regions of the air in clusters 2 and 4 were characterized by large emissions of VOCs, which are important precursors of 5 dicarboxylic acids and related compounds (Zhang et al., 2009).As a result, clusters 2 and 4 had higher concentration of dicarboxylic acids and related compounds.The two clusters contributed 73% of the total concentration of dicarboxylic acids and related compounds.Clusters 1 and 3 originated from cleaner areas (i.e., the ocean and Siberia, respectively), so the total concentration of dicarboxylic acids and related compounds 10 was lower compared with clusters 2 and 4. Using WRF modeling, the boundary layer heights (BLH) at Mt. Tai (Figure S1) were calculated.The results revealed that the daytime BLH were higher than the site elevation for only 7% of cluster 2 and 9% of cluster 4 trajectories, while nighttime BLH were all lower than the site elevation.Therefore, our measurements generally represent concentrations in the free 15 troposphere, which suggests that pollutant concentrations at Mt. Tai were largely controlled by long range transport.

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In Table 2 the concentrations of dicarboxylic acids and related compounds at Mt.
Tai in 2014 and from other previous measurements are presented.Using the ratio of PM 2.5 /TSP = 0.91 (Deng et al., 2011) and concentrations of dicarboxylic acids and related compounds in TSP at Mt. Tai in 2006 (Kawamura et al., 2013), we estimated the corresponding concentrations of dicarboxylic acids and related compounds in  (Zhu et al., 2017), which is substantially lower than the 2006 estimated value of 387 ng m -3 (Fu et al., 2008;Deng et al., 2011).Therefore, from 2006 to 2014, biomass burning decreased by about 80%.Compared with the Chinese megacities, such as Guangzhou (Ho et al., 2011) and Beijing (Ho et al., 2010), the dicarboxylic acids and related compounds 2014 Mt.Tai concentrations were about 1-2 times higher.The concentrations of dicarboxylic acids at Mt. Tai in 2014 were similar to the concentrations reported in the 14 Chinese cities study (Ho et al., 2007), while oxocarboxylic acids and α-dicarbonyls were more than 5 three times higher.Compared with other Asian urban sites, the results reported here were about 1-2 times higher than those reported in Chennai, India (Pavuluri et al., 2010b), Tokyo, Japan (Kawamura and Yasui, 2005), and Sapporo, Japan (Aggarwal and Kawamura, 2008), but lower than those reported in Raipur, India in PM 2.1 (Deshmukh et al., 2016).Furthermore, the Mt.Tai dicarboxylic acids and related 10 compounds concentrations were approximately 5-13 times higher compared with those in Europe and USA urban aerosols, such as in Leipzig, Germany (van Pinxteren et al., 2014), Zurich, Switzerland (Fisseha et al., 2006), and Houston, USA (Yue and Fraser, 2004).The high concentrations of dicarboxylic acids and related compounds at Mt. Tai likely resulted from the substantial emissions of VOCs in Mt.Tai's 15 surrounding areas, which are some of the most heavily polluted regions in China.
C 2 was found to be the most abundant species at Mt. Tai in 2014, and the concentration of C 4 was larger than C 3 .This trend was consistent with measurements at several urban sites, where local anthropogenic emissions were significant sources, such as in the 14 Chinese cities study (Ho et al., 2007) and Tokyo, Japan (Kawamura 20 and Yasui, 2005).Ph which can be utilized as a tracer for anthropogenic source (Kawamura and Ikushima, 1993;Kawamura and Yasui, 2005), was the fourth most abundant species at Mt. Tai in 2014.The trend was dissimilar to Beijing, Guangzhou, and to the 14 Chinese cities studies, where Ph was the second most abundant species.This is likely due to photochemical aging during long range transport from source

Comparisons of day and night measurements of dicarboxylic acids and related compounds
As shown in Table 1, the daytime total concentrations of dicarboxylic acids, oxocarboxylic acids and α-dicarbonyls were similar to the nighttime total 5 concentrations.79% of the day-night concentration ratios ranged between 0.9 and 1.1.The boundary layer height was higher during the daytime, peaking near noontime.
The boundary layer occasionally extended high enough during the daytime to approach the sampling site (Figure S1).However, the maximum of boundary layer height was only ~ 600 m during the nighttime, which was much lower than the 10 sampling site height.This suggests that mountain/valley breezes may bring ground level pollutants to the summit of Mt.Tai during the daytime when the boundary layer height was above the sampling site height.A similar transport process was observed over the Taihang Mountains in the Beijing region (Chen et al., 2009).However, this transport mechanism did not occur during the night.Therefore, the similar day and 15 night average concentrations of dicarboxylic acids and related compounds cannot be explained by the changes in the boundary layer heights.As shown in Figure 2, dicarboxylic acids and related compounds exhibited correlations with their gas phase precursors-VOCs (Zhu et al., 2017).These result suggests that the difference in the day and night measurements was possibly dependent on the amount of precursor 20 emissions.
In addition, the daytime concentrations might have been enhanced by photochemical reactions, and the nighttime concentration might have been enhanced by effective aqueous oxidation and less effective loss.The RH was generally high during the nighttime (86.8% ± 15.2% on average, up to 100 %), indicating that dicarboxylic acids and related compounds may have been produced through aqueous phase oxidation.Correlations between C 2 and SO 4 2-and the corresponding linear regression slopes were used to evaluate whether C 2 might have been related to aqueous phase oxidation (Yu et al., 2005;Sullivan and Prather, 2007).As shown in Figure 3, C 2 and SO 4 2-exhibited a significantly higher correlation during the nighttime (R 2 = 0.64) than that during the daytime (R 2 = 0.28), and the linear regression slope during the nighttime (0.028) was also higher than that during the daytime (0.016).Assuming aqueous phase formation of sulfate was the dominant process (Yu et al., 2005), these results indicate that a considerable amount of C 2 may 5 have been produced via aqueous-phase oxidation during the nighttime.In addition, photolysis of iron-oxalate complexes is an important sink of C 2 in the aqueous phase; therefore, the removal of C 2 was lower during the nighttime than during the daytime (Ervens et al., 2003;Tilgner and Herrmann 2010;Pavuluri and Kawamura, 2012).
Details of the multiphase formation pathways, removal mechanisms, and major exhibited a strong correlation during the first half, while during the second half, dicarboxylic acids and K + exhibited no correlations (Figure 5).The peaks of dicarboxylic acids and K + appeared almost simultaneously (Figure 4).It was also clear that when the K + concentrations increased, dicarboxylic acids correspondingly increased during the first half (Figure 5).These results indicate that biomass burning Concentrations of C 2 declined from the first half to the second half (Figure S2).C 3 , C 4 and longer-chain dicarboxylic acids (C 5 -C 9 ) also exhibited similar trends, with much higher concentrations during the first half.However, iC 4 and iC 6 were generally constant throughout the whole period.This result suggests that biomass burning was an insignificant source for these two species.M, F, mM, Ph, iPh, tPh, kC 3 , and kC 7 5 had higher concentrations during the first half, suggesting that the anthropogenic components, such as vehicle emissions, fossil combustion, and plastic burning (Kawamura and Sakaguchi, 1999;Kawamura and Kaplan, 1987;Simoneit et al., 2005), were probably transported to the Mt.Tai site concurrently with biomass burning plumes. 10 Oxocarboxylic acids and α-dicarbonyls exhibited similar temporal trends when compared to dicarboxylic acids.On average, oxocarboxylic acids and α-dicarbonyls were more abundant during the first half (158 ± 101 ng m -3 and 32.9 ± 25.5 ng m -3 , respectively) than during the second half (89.2 ± 25.1 ng m -3 and 16.8 ± 8.82 ng m -3 , respectively).ωC 2 , ωC 3 , ωC 4 , ωC 5 , ωC 9 , Pyr, Gly, and MGly also displayed similar 15 trends as C 2 , with higher concentrations during the first half.
Ph is a photo-degradation product of anthropogenic aromatic hydrocarbons, and C 9 is a photo-oxidation product of biogenic unsaturated fatty acids (Schauer et al., 2002;Kawamura and Ikushima, 1993).As a result, the Ph/C 9 ratio can be used to evaluate the source strength of anthropogenic versus biogenic emissions (Kawamura and Yasui, 20 2005).In this study, the Ph/C 9 ratios ranged between 0.32 and 8.64 (average: 3.20) and were mostly higher than 1 (Figure 6), which is comparable to those from the 14 Chinese cities study (average in the summer: 3.37) (Ho et al., 2007) but much higher than in Nanjing, China (average in summer: 1.98) (Wang et al., 2002) and Chennai, India (average in summer: 0.69) (Pavuluri et al. 2010b).These comparisons suggest 25 that anthropogenic sources contributed more significantly than biogenic sources at Mt.
Tai.Moreover, the Ph/C 9 ratios were higher during the daytime (range: 0.32-8.64,average: 3.75) compared to those during the nighttime (range: 0.54-7.09,average: 2.53).In addition, the Ph/C 9 ratios were higher during the second half when almost no biomass burning was observed.

Source identification of dicarboxylic acids and related compounds
Principal component analysis (PCA) is a multivariate analytical tool and that can be employed to reduce the dimensionality of original variables and extract the principal components (PCs) in order to study the relationships among the observed variables.
Only factors with eigenvalues greater than 1 were extracted based on 5 Kaiser-Meyer-Olkin (KMO) and the Bartlett's test of sphericity.Then the factors were rotated by the Varimax method (Malinowski, 1991).In this study, PCA was used with particulate concentrations of 25 variables for daytime and nighttime samples by using IBM SPSS Statistics 21.0.If the compound concentrations were below the detection limit, the data was replaced by a value half of the corresponding detection limit.The 10 factor-loading matrix after Varimax rotation is shown in Table 3 and Table 4.
Weighting factors |x| < 0.2 were considered insignificant and not listed, while |x| > 0.6 were considered high loading and are depicted in bold.

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As shown in Table 3, PC1 was dominated by high loadings of C 2 -C 6 , iC 5 , F, hC 4 , Ph, kC 3 , Pyr, ωC 2 , ωC 4 , Gly, MGly, OC, and K + , which was most associated with anthropogenic activities such as fossil fuel and biomass/fuel combustion, followed by photochemical aging during long range transport.NH 4 + , NO 3 -, and SO 4 2-were positively related with PC2, indicating they were derived from secondary sources, 20 including gas and aqueous phase chemistry.Fine mode SO 4 2-is formed through aqueous-phase oxidation of SO 2 on aerosols and cloud droplets (Seinfeld and Pandis, 1998).PC3 was enriched in M, F, and EC and was assumed to represent fuel combustion (Puxbaum et al., 2007;Zhang et al., 2008;Jung et al., 2010).In PC4, C 9 and Na + were dominant, suggesting that the photooxidation of unsaturated fatty acids explained 56, 14, 13, and 6%, respectively, of the total variance (89% in total).
Nighttime sources for dicarboxylic acids and related compounds were similar to the daytime, but there were distinctions between the contribution orders.As shown in , and SO 4 2-dominated, suggesting that gas and aqueous phase secondary processing was a significant factor.Moreover, the variance of the sources was higher during the nighttime (13%) than that during the daytime 10 (9%), suggesting that secondary processes were more important during the nighttime.
PC4 was characterized by high loadings of C 9 , tPh, OC, and Na + suggesting a mixed aerosol related to the photooxidation of unsaturated fatty acids emitted from sea surfaces and anthropogenic emissions from burning of solid wastes/plastic polymers.

Conclusions 15
Dicarboxylic acids, oxocarboxylic acids, and α-dicarbonyls were quantified in PM 2.5 filter samples collected between 04 June and 04 July 2014 at Mt. Tai in the North China Plain.Concentrations of dicarboxylic acids and related compounds were higher than those reported in urban sites in the world but lower than previous measurements at Mt. Tai.WRF modeling and backward trajectory analyses suggested 20 that long range transport of pollutants was a major factor governing the distributions of dicarboxylic acids and related compounds at Mt. Tai.PCA results revealed that anthropogenic activities were the major sources for dicarboxylic acids and related compounds at Mt. Tai.However, biomass burning only had a significant impact during the first half of the sampling period (4-19 June).between dicarboxylic acids and related compounds and their gas precursors-VOCs and the correlations between C 2 and sulfate, the day-night ratios were probably dependent on precursor emissions and aqueous oxidation.Further interpretations of the complex Mt.Tai dataset using a detailed multiphase chemistry air parcel model, including chemical source and sink analyses, will be completed in a follow-up study.g Kawamura and Yasui (2005).l did not include all dicarboxylic acid species.Extraction method: Principal component analysis.
Rotation method: varimax with Kaiser normalization.

20 PM 2
.5 at Mt. Tai in 2006 (dicarboxylic acids: 1550 ng m -3 , oxocarboxylic acids: 220 ng m -3 , α-dicarbonyls: 62 ng m -3 ).Compared with the results with this study, the levels of dicarboxylic acids and related compounds in 2014 at Mt. Tai were about two times lower.Different meteorology conditions in 2006 and 2014 may partially explain the decreased concentrations, as well as the implementation of regulatory controls of 25 biomass burning by the Chinese government.In 2014, the levoglucosan concentration was 70.4 ng m -3 in PM 2.5

25 regions
to Mt. Tai.Although concentration of dicarboxylic acids, oxocarboxylic acids, and α-dicarbonyls notably decreased from 2006 to 2014, they were still greater when compared to other urban sites in the world.Due to photochemical aging during long-range transport, the compositional trends of dicarboxylic acids and related 30 9 Atmos.Chem.Phys.Discuss., https://doi.org/10.5194/acp-2017-1240Manuscript under review for journal Atmos.Chem.Phys.Discussion started: 25 January 2018 c Author(s) 2018.CC BY 4.0 License.compounds was distinct from previously studied Chinese sites.

10 precursor3. 5
contributions will be further investigated using the SPectral Aerosol Cloud Chemistry Interaction Model (SPACCIM, Wolke et al. 2005) together with chemical aqueous-phase radical mechanism (CAPRAM, Tilgner et al. 2013) in an upcoming study.Impact of biomass burning on the temporal variations of dicarboxylic acids 15 and related compounds The temporal variations of dicarboxylic acids, oxocarboxylic acids, α-dicarbonyls, and K + are presented in Figure 4. Concentration maxima of dicarboxylic acids were observed during the first half of the observational period (4-19 June), and then they decreased during the second half (20 June-4 July).Dicarboxylic acids and K + 20

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was a significant contributor to dicarboxylic acids, oxocarboxylic acids, and α-dicarbonyls during the first half of the measurement period.Emission hotspots reported by the Ministry of Environment Protection of the People's Republic of China further supported this conclusion.Atmos.Chem.Phys.Discuss., https://doi.org/10.5194/acp-2017-1240Manuscript under review for journal Atmos.Chem.Phys.Discussion started: 25 January 2018 c Author(s) 2018.CC BY 4.0 License.

Figure 1 . 5 Figure 2 . 10 29
Figure 1.Three-day backward trajectories for Mt.Tai during the study period.(Since cluster 2 was covered by cluster 3, the width of the cluster 2 trajectory has been increased.)

Figure 5 . 5 Figure 6 .
Figure 5. Scatter plots of K + and the total dicarboxylic acids concentration during the first half and second half of the campaign.
a Minimum.b

Table 2 .
Concentrations of dicarboxylic acids and related compounds reported in this study and literature data from the previous measurements at Mt. Tai in 2006 and other urban sites in the world (unit: ng m -3 ).

5 Table 3 .
PCA analysis result for daytime dicarboxylic acids and related compounds in PM 2.5 aerosols collected at Mt. Tai in 2014.