Measurement report: Amino acids in fine and coarse atmospheric aerosol: concentrations, compositions, sources and possible bacterial degradation state

Abstract. The size distribution of amino acids (AAs) in atmospheric particles determines the atmospheric allergenicity, which may have deleterious effects on human health. This paper explores the use of compound-specific δ15N patterns of hydrolyzed amino acid (HAA), δ15N values of total hydrolyzed amino acid (THAA), degradation index (DI), and the variance within trophic AAs (ΣV) as markers to examine the sources and processing history of different sizes particle in the atmosphere. 2-weeks of daily aerosol samples from five sampling sites in the Nanchang area (Jiangxi Province, China) and samples of main emission sources of AAs in aerosols (biomass burning, soil and plants) were collected (Zhu et al., 2020). Here, we measured the concentrations and δ15N values of each HAA in two size segregated aerosol particles (> 2.5 μm and PM2.5). Our results showed that the average concentrations of THAA in fine particles was nearly 6 times higher than that in coarse particles (p 



Introduction
Recently, an increasing number of researchers highlight the importance of amino acids (AAs) in the 40 atmosphere because AA is considered to be one of the most important compound classes of organic nitrogen compounds in atmosphere (Samy et al., 2013;Wedyan and Preston, 2008;Song et al., 2017;Zhang et al., 2002). Moreover, AAs are bioavailable and can be directly utilized by plant and soil communities. Its key role in atmosphere-biosphere nutrient cycling and global nitrogen cycle has aroused greatly concern. Besides that, AAs and proteins are important constituents of allergenic bioaerosol. The

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distribution of AAs and proteins in different particle sizes will determine whether these compounds can reach the pulmonary alveoli and the allergy of aerosols. And the distribution of AAs associated with different particle sizes can help to trace the sources and transformation of atmospheric aerosols. However, detail information on the concentrations and mole composition profiles of AA distributed in different size particle is still limited.

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Compound-specific nitrogen isotope analysis of individual amino acids provide an opportunity to offer the key information on widely varied photochemical processes and origins of proteinaceous matter in the atmosphere. Nitrogen sources information and any possible nitrogen isotopic fractionation caused by transformation processes could be hold by the δ 15 N-AA pattern (Mccarthy et al., 2007;Bol et al., 2002).
At the same time, the δ 15 N value of total hydrolysable AA (δ 15 NAvg-THAA), calculated as the average molar-55 weighted δ 15 N value of individual AA, has been used as a proxy for total protein δ 15 N value . However, to our knowledge, no study has used the δ 15 N-AA pattern and δ 15 NAvg-THAA values to identify the sources of AAs distributed in different particle sizes.
It is generally accepted that AAs in aerosols are mainly controlled by abiotic photochemical aging processes. On the contrary, the biological degradation of AAs in aerosols are neglected. This can be 60 attributed to two factors. First, the sources and transformation pathways of protein matter and AAs in aerosols are highly complex (Wang et al., 2019;Zhu et al., 2020). Second, and the residence time of protein matter in aerosols is relatively short (Papastefanou, 2006). Admittedly, bacteria and fungi are ubiquitous and can be observed in all PM samples where people look for them, and this has been done routinely for many decades (Bauer et al., 2002;Bowers et al., 2013;Huffman et al., 2013;Wei et al., 65 2016;Wei et al., 2019). In-situ bacterial degradation processes occurred in the aerosols and the cloud water was also observed (Amato et al., 2007;Husá rová et al., 2011).Unfortunately, bacterial degradation of atmospheric AAs is rarely investigated, except for one study on marine aerosols by Wedyan and Preston (2008) and one study on precipitation by Yan et al. (2015). It is still unknown that whether bacterial degradation play a role in the levels and compositions of AAs in different particle sizes.

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In terrestrial, aquatic, and marine environment, the degradation state of organic materials (OM) is frequently characterized by DI based on the molar composition of amino acids (Dauwe and Middelburg, 1998;Wang et al., 2018;Dauwe et al., 1999). The higher DI values denote more "fresh" state of protein matter. Besides, a consensus has recently been reached on selective use of the 15 N depleted or enriched trophic AAs during bacterial heterotrophy processes can lead to large nitrogen isotopic fractionation in 75 trophic AAs (McCarthy et al., 2004). Thus, substantial δ 15 N pattern shifts of trophic AAs can index bacterial heterotrophy processes. ∑V, defined as the average deviation in the δ 15 N values of the Tr-AA, has therefore been established to track the degree of bacterial degradation of AAs in marine and terrestrial https://doi.org/10.5194/acp-2020-534 Preprint. Discussion started: 23 July 2020 c Author(s) 2020. CC BY 4.0 License. environment (Mccarthy et al., 2007;Philben et al., 2018;Yamaguchi et al., 2017).
In the present work, we sought to improve our understanding of AAs distributed in different sizes particle.

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We measured the concentrations and δ 15 N values of each hydrolyzed amino acid in two size segregated aerosol particles (>2.5 μm and PM2.5) and main emission sources of AAs in aerosols collected in the Nanchang area (southeastern China). Furthermore, δ 15 N values of Gly and THAA in fine and coarse particle were compared with those in main emission sources to identify the potential sources of fine and coarse particles. In addition, the DI, ∑V values and δ 15 N values pattern of hydrolyzed AA in fine and 85 coarse particles were analyzed to explore the possible bacterial degradation of AAs in fine and coarse particles. Aerosols from straw burning were sampled by pumping into a high-volume air sampler (KC-1000, Qingdao Laoshan Electronic Instrument Company, China) from the funnel on the combustion furnace during July 2017. The combustion furnace is a domestic furnace widely used by local residents.

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For hydrolyzed AA analysis, samples were prepared using a modified version of Wang et al. (2019) and Ren et al. (2018). One-sixteenth of each fine aerosol filter (~80 m 3 of air) or Two-seventh of each coarse aerosol filter (~366 m 3 of air) was broken into small pieces and placed in a glass hydrolysis tube. Prior to the hydrolysis, 25 μL of ascorbic acid at a concentration of 20 μg μL -1 (500 μg absolute) was added to each filter sample. Then, 10mL and 6M Hydrochloric acid (HCl) was used to convert all of the combined

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AAs to free AAs. To avoid oxidation of AAs, the hydrolysis tube was flushed with nitrogen and tightly sealed before hydrolysis. The mixture was later placed in an oven at 110 °C for 24 h.
After cooling to room temperature, the hydrolyzed solution was dried with a stream of nitrogen and HCl was removed. The dried solution was then redissolved in 0. Butyldimethylsilyl (tBDMS) derivatives of HAAs were prepared following the method described by our previous study Zhu et al. (2018).
The concentrations of HAAs were analyzed using a gas chromatograph-mass spectrometer (GC-MS).
The GC-MS instrument was composed of a Thermo Trace GC (Thermo Scientific, Bremen, Germany) connected into a Thermo ISQ QD single quadrupole MS. The single quadrupole MS was operated in 120 electron impact ionization (70 eV electron energy) and full scan mode. The temperatures of the transfer line and ion source were 250°C and 200°C, respectively. More details on quality assurance and control (recoveries, linearity, detection limits, quantitation limits, and corresponding effective limits in the aerosol samples of AAs), are provided in Zhu et al. (2020) δ 15 N values of AA-tert-butyl dimethylsilyl (tBDMS) derivatives were analyzed using a Thermo Trace

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GC (Thermo Scientific, Bremen, Germany) and a conflo IV interface (Thermo Scientific, Bremen, Germany) interfaced with a Thermo Delta V IRMS (Thermo Scientific, Bremen, Germany). The analytical precision (SD, n=3) of δ 15 N was better than ±1.4‰. Moreover, AABA with known δ 15 N value (-8.17‰±0.03‰) was added in each sample to check the accuracy of the isotope measurements. The analytical run was accepted when the differences of δ 15 N values of AABA between GC-IRMS and EA-

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IRMS values were at most ±1.5‰. Each reported value is a mean of at least three δ 15 N determinations.
For more details of the analyses of HAA δ 15 N values refer to our previous publication (Zhu et al., 2018).
The concentrations and δ 15 N value of Cys, Trp, Asn and Gln in HAAs could not be determined using this method because, under strong acidic condition, Cys and Trp is destroyed, and Asn and Gln are converted to Asp and Glu, respectively. The concentration and δ 15 N value of hydrolysable Asp represents the sum 135 of Asp and Asn; the concentration and δ 15 N value of hydrolysable Glu represents the sum of Glu and Gln.

DI index
The degradation index (DI) was calculated using the formula Eq. (1) originally proposed by Dauwe et al. (1999): where DI is the degradation index, Var is the mole% of the each individual HAA, Avgi, SDi and PCi are the average mole% and standard deviation of each HAA in our data set, respectively, and PC1 loading of the amino acid i obtained from principal component analysis (Table S1).

δ 15 N values
The natural abundance of 15 N was calculated as δ 15 N values in per mil (‰): where R is the ratio of mass 29/mass 28

∑V parameter
The ∑V parameter is defined as the average absolute deviation in the δ 15 N values of the Trophic AA (including: Ala, Asp, Glu, Ile, Leu, and Pro) (Mccarthy et al., 2007). This parameter has been used as a https://doi.org/10.5194/acp-2020-534 Preprint. Discussion started: 23 July 2020 c Author(s) 2020. CC BY 4.0 License.
where ꭓAA is defined as the deviation of the δ 15 N of each trophic amino acid from the δ 15 N of the mean of trophic amino acids (δ 15 N AA-average δ 15 N of Ala, Asp, Glu, Ile, Leu, and Pro), and n is the total number of trophic amino acids used in the calculation.
Where mol%HAA is the mole contribution of each HAA and δ 15 NTHAA is the δ 15 N value of individual 160 HAA.
We performed a Two-way ANOVA for the concentration of THAA, the DI index, δ 15 NTHAA values and

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∑V values, testing the effect of aerosol sizes, location, and their interaction. Tukey's Honestly Significant Differences (Tukey-HSD) test was used to evaluate which combinations of location and aerosol size were significantly different. Two-way ANOVA was also conducted for DI values, examining the effect of aerosol sizes, coefficients (obtained by using first principal component score or previous reported coefficients) and their interaction. The differences in δ 15 NGly values for fine particles between 5 sampling 170 locations were examined using the one-way analysis of variance (ANOVA) procedure, and compared using the Tukey-HSD test.
The exponential regression was analyzed to evaluate changes in DI index as a function of the concentration of THAA.
To test for changes in the concentration of THAA, DI index and ∑V values following the rain events, a 175 two-way ANOVA was performed, testing for effects of precipitation, aerosol sizes and their interactions.
Tukey-HSD test was conducted to compare the significant difference. Changes in mol% of each HAAs concentrations following precipitation were tested for significance by using ANOVA procedure followed by a Tukey-HSD test to compare significant differences. For all tests, statistically significant differences were considered at p<0.05. were found in fine and coarse aerosol samples collected in Nanchang areas during spring 2019 (Fig. 1).
434.0±722.6 pmol m -3 , respectively. The mean concentration of THAA for fine particles was nearly 6 times higher than that for coarse particles (p<0.01) (Fig. S1). However, for coarse particles, the difference in THAA concentrations between 5 sampling sites were not significant (p>0.05) (Fig. S1). The mean concentration of THAA in airport, urban, forest, town and

mol% composition profile of HAA in potential sources
The mol% composition of HAA were distinct in the biomass burning aerosols (straw burning), soil (road, paddy and forest soil), and plant sources (pine and straw) (Fig. 2

Difference in composition profiles of HAA between fine and coarse particles
The composition profiles of HAA in fine and coarse particles during the whole campaign are shown in accounting for an average of 25.0 ± 11.6%, 16.9 ± 8.0%, 11.8 ± 3.3% and 10.8 ± 5.7%, respectively, of https://doi.org/10.5194/acp-2020-534 Preprint. Discussion started: 23 July 2020 c Author(s) 2020. CC BY 4.0 License.
the THAA pool.
For coarse particles, Pro were the most abundant THAA specie, with an average contribution of 63.3± 31.1% to the THAA pool. Leu, Ala and Val were the next most abundant species, each accounting for 6.6

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-9.2% of the THAA pool, while other individual HAA was only minor component in coarse particles ( Fig. 2 and Fig. 3).

Difference in composition profiles of HAA among different sampling locations
The HAA distribution among the different sampling locations for both fine and coarse particles appeared similar ( Fig. 3).

Influence of precipitation on the composition profiles of HAA
It is worth noting that the influence of precipitation on the mole composition profile of HAA is different for the coarse and fine particles (Fig. 3). According to our previous study (Zhu et al., 2020) and the mol% composition of HAA observed in this study, hydrophobic (Ala, Val, Leu, and Ile), neutral (Pro) and hydrophilic (Glu, Lys, and Asp) species are the major HAA components in natural sources (plant and soil 235 sources). For fine particles, the contributions of HAAs species with high abundance in natural sources (including: Ala, Val, Leu, Ile, Pro, Glu, Lys, and Asp), increased from dry periods (65%) to rainfall periods (69%) (Fig. S2). Among these AAs, the percentage of Pro significantly increased from 14.1±6.2% on dry days to 19.7±8.8% on rainfall days (p<0.05). There was no apparent trend in the percentage of other individual HAAs for fine particles following the precipitation.

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For coarse aerosol, the percentage of HAAs with high abundance in natural sources exhibited little changes from dry periods (averaged 94%) to rainfall periods (averaged 93%) (Fig. S2). However, the percentage composition of HAA in dry periods is quite different from that in rainy periods for coarse particles (Fig. 3). From dry periods to rainfall periods, the percentage of Pro in coarse particles significantly decreased from 73.6±24.7% to 52.7±33.6% (p<0.05), meanwhile the percentage of Ala, Val,

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Leu, Ile and Glu in coarse particles significantly increased (p<0.05). These HAA species together accounted for 38.5% of the total THAA pool during dry periods, while during rainfall events this proportion was only 19.8%.
Besides that, compared to fine particles, the large variation in mole composition of THAA for coarse particles was observed following rain events (Fig. 3). From dry periods to rainfall periods, the percentage 250 changes of Pro for coarse particles (20.9%) was roughly 4 times greater than that for fine particles (5.6%).
Similarly, from dry periods to rain periods, the increase in the percentage of Ala, Val, Leu, Ile and Glu in coarse particles is significantly greater than that in fine particles. For example, following the precipitation, Val in coarse particles increased by 3.5%, whereas Val in fine particles only increased by 0.3%.
Particularly, this steep decrease in the percentage of Pro and increase of other HAAs in coarse particles 255 mainly occurred in the first day of rainfall events ( Fig. 3).

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The first principal component explained 38.3% of the variability, and the second principal component explained 20.9% (Table S1). Fig. 4a shows plots of the scores of the first and second principal components of fine and coarse particles in 5 sites. Components of fine and coarse particles could be roughly separated. The plots of the fine particles tended to cluster in the upper middle and right areas (approximately -1.7 to +2.0, and -0.4 to 1.4 at first and second principal component scores, respectively).

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In contrast, the plots of the coarse particles tended to locate in the lower and left areas (approximately -1.9 to 1.4, and -2.8 to +0.5 at first and second principal component scores, respectively). Fine and coarse particles were roughly distinguished by first and second principal component scores, suggesting that the first principal component score may also be designed as a degradation index of THAA in aerosols.
A plot of factor coefficients of each individual amino acid in the first and second principal components 275 was examined to clarify the reasons for variation of the scores of fine and coarse particles (Fig. 4b).
Based on this cross plot, 14 HAA species were divided into four groups. In were affected by the relative abundance and the factor coefficient of each individual amino acid. The relative high principal component scores of fine particles in PC1 and PC2 were more affected by the high relative abundances of amino acids which has high factor coefficient (Group 1 and Group 2). In contrast, the relative low principal component scores of coarse particles in PC1 and PC2 were more affected by the low relative abundances of amino acids which has low factor coefficient (Group 1 and Group 4).

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Furthermore, DI values for fine particles showed positive correlation with percentage of HAA species in Group1 (e.g., Lys, Glu, Asp, Phe, Thr, Ser), but DI values for coarse particles were positively correlated to percentage of HAA species in Group 2 (e.g., Ala, Val, Leu and Ile) (Fig. 5), indicating the difference in composition profiles of HAA between fine and coarse particles may affected by the degradation process.

Compared our calculating method with other works
This is the first report of the DI values for aerosol particles. We compared DI values obtained by our calculating method with those calculated by using the coefficients given in previous references (Dauwe et al., 1999;Yamashita and Tanoue, 2003). There is no significant difference between the DI values calculated using the first principal component score and the DI values calculated using the coefficients 295 given in the previous reference (Dauwe et al., 1999;Yamashita and Tanoue, 2003) (p>0.05) (Fig. S3), confirming our calculation method is reliable.

Correlation between DI and THAA
Plots of DI as a function of THAA concentration in both fine and coarse particles showed an exponential relationship (y=1067.4e -1.0x ; r=0.6, p<0.01); that was, that at higher values of DI, concentrations of THAA 300 were higher, and vice versa (Fig. 6), indicating THAA for both fine and coarse aerosols probably undergone bacterial degradation. in Seoul, which were proved to be more degraded materials (Fig. 8).

DI values of aerosol particles at different locations
However, the differences in DI values were not significant among 5 sampling sites for both fine and

Influence of precipitation on the DI values of aerosol particles
As exhibited in Fig. 7a, DI values of coarse aerosol particles were influenced by precipitation. For coarse aerosol particles, a significant increase was found from dry (average=-1.0±0.8) to rain periods (average=- It is interesting to note that a substantial δ 15 N-AA shifts in trophic AA group was observed between fine and coarse particles. Ala, Leu, Ile and Asp was 15 N-enriched in coarse particles compared to fine particles,

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whereas Pro in coarse particles was 15 N-depleted than those in fine particles (Fig. 10). Clearly, there is no uni-directional 15 N depletion or enrichment of Trophic-AA was observed between fine and coarse https://doi.org/10.5194/acp-2020-534 Preprint. Discussion started: 23 July 2020 c Author(s) 2020. CC BY 4.0 License.
particle samples. The δ 15 N -AA distribution in the Trophic-AA group is more ''scattered'' in coarse particles than that in fine particles (Fig. 10). However, the difference in δ 15 N values of Source-AA between coarse particles and fine particles was relatively small except for Val. δ 15 N values of Gly, Ser,

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Phe and Lys measured in coarse particles are close to those measured in fine particles.

δ 15 NGly and δ 15 NTHAA values of local natural sources
Our previous study found that the δ 15 N value of Gly in PM2.5 can be used to trace the potential emission sources for aerosol AAs because the N isotope fractionation associated with Gly transformation in aerosol is relatively small (Zhu et al., 2020). The δ 15 N of protein AA (δ 15 NTHAA) has been served as a proxy for

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indicating the nutrient N in marine sediments (Batista et al., 2014). To trace the sources of fine and coarse particles, we measured the nitrogen isotopic compositions of hydrolyzed Gly and THAA sampled from main emission sources in the study areas, including biomass burning, soil and local plants (Fig. 10). The average δ 15 N value for hydrolyzed Gly from the biomass burning, soil, and plant sources was +15.6 ± 4.3‰, +3.0 ± 4.4‰, and −11.9±1.4‰, respectively, and the mean δ 15 NTHAA value was +15.8 ± 4.5‰,

δ 15 NGly and δ 15 NTHAA values in different size particles
In this study, to test δ 15 NTHAA values of aerosol particles could also be used to trace the sources of aerosol particles, δ 15 NTHAA values were compared with the δ 15 NGly values. Since the concentration of hydrolyzed Gly is very low in coarse particles, a few the δ 15 NGly values could be measured in coarse aerosol samples.  Similarly, both fine (+0.7‰ to +13.3‰) and coarse particles (−2.3‰ to +10.0‰) had the δ 15 NTHAA value also typically in the range of these three main emission sources (Fig. 10). Therefore, it is likely that the main sources of atmospheric AAs for both fine and coarse particles were mainly biomass burning, soil, and plants.
In addition, the difference in δ 15 NTHAA values were not significant for fine and coarse particles (p>0.05)

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( Fig. 11c) and the average offset of δ 15 NTHAA value between fine and coarse particles was lower than 1.5 ± 1.7‰ in 5 sampling sites (Fig. 11a), further supporting the sources of AAs for fine and coarse aerosol particles may be similar.
The δ 15 NGly values of fine particles was significantly different at 5 sampling sites (p<0.05). The average 370 δ 15 NGly value of fine particles in urban (average=14.3 ± 8.5‰) and town (average=9.4 ± 4.2‰) were more positive than that in suburban (average=6.7 ± 4.3‰), airport (average= 6.9 ± 5.3‰) and forest site (average=6.5 ± 5.0‰) (Fig. 11b). The significantly higher δ 15 NGly values observed in the urban and town locations suggested an increased contribution from biomass burning sources to Gly in fine particles at these two locations.
The more positive δ 15 NTHAA values occurred in urban and town compared to other sampling sites for both fine and coarse particles (p<0.05), indicating that atmospheric AAs for both fine and coarse particles in urban and town were more influenced by biomass burning.

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∑V is defined as the average deviation in six Trophic-AA and has been proposed to reflect protein resynthesis during microbial degradation processes (Mccarthy et al., 2007). Fig. 12 shows the ∑V values measured in fine particles, coarse particles, and local natural sources, as well as ∑V values reported in previous references.

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∑V values for main natural sources collected around the sampling sites were calculated. ∑V values for local plants (needles of Pinus massoniana (Lamb.) and leaves of Camphora officinarum) ranged from 1.0‰ to 2.1‰, with a mean of 1.7±0.4‰ (Fig. 12). ∑V values in local soil (paddy soil, road soil and forest soil) ranged from 1.4‰ to 2.1‰, with a mean of 1.7±0.3‰.

∑V value in aerosol particles at different locations
The ∑V values of both fine and coarse particles were not significantly different among the 5 sampling 405 https://doi.org/10.5194/acp-2020-534 Preprint.  (Fig. 12).

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With the development of stable N isotope technology, δ 15 N values and δ 15 N pattern has become effective tools to trace the sources of nitrogen compounds. Our previous study found that the δ 15 NGly value in aerosol particles can be used to identify the potential emission sources for aerosol AAs. In this study, the δ 15 N values of hydrolyzed Gly for both fine and coarse particles exhibited wide ranges but were typically in the ranges of hydrolyzed Gly from biomass burning, soil and plant sources (Fig. 10). Therefore, it is 430 likely that the main sources of atmospheric AAs for both fine and coarse particles were mainly biomass burning, soil, and plants.
Similarly, according to the δ 15 N inventories of THAA in potential emission sources of atmospheric protein AA, δ 15 NTHAA values for fine and coarse particles were also in the range of δ 15 NTHAA values from the three main contributing sources, which further demonstrated that AAs in both fine and coarse particle 435 were affected by biomass burning, soil, and plants sources.
Moreover, the δ 15 N-HAA pattern of fine and coarse particles was remarkably consistent ( Fig. 9 and 10).
There is no significant difference in the δ 15 NTHAA value between fine and coarse particles in each sampling sites (p>0.05) (Fig. 11c) and the average offset of δ 15 NTHAA value between fine and coarse particles was lower than 1.5‰ (Fig. 11a).Thus, it is suggested that the main sources of AAs in fine and 440 coarse particles might be similar, all of which were influenced by biomass burning, soil, and plant sources.

Difference in degradation state of protein AA between fine and coarse aerosol particles
In this study, a huge difference was observed in the concentrations and mol% compositions of THAAs between fine and coarse particles ( Fig. 1 and 3). As we discussed above, the sources of AAs in fine and coarse particles are similar, therefore this lager difference may be attributed to protein matter in fine and 445 coarse undergoing different degrees of oxidation, nitration and oligomerization in the atmosphere Wang et al., 2019;Song et al., 2017;Haan et al., 2009). Another possibility is that, bacterial degradation of AAs may contribute to this variation observed between fine and coarse particles.
Interestingly, by using bacterial markers (DI, δ 15 N-AA distribution and ∑V), we found that AAs in fine and coarse particles may be degraded by bacteria to different degrees.

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The degradation index (DI) value has been developed to assess degradation state of atmospheric matter solely derived from amino acids (e.g., protein materials) (Yan et al., 2015). Relatively high DI values denote a relatively "fresh" matter. In this study, the positive correlation between the concentrations of THAA and DI values for both fine and coarse particles in the atmosphere is established in this study (Fig.   6). Furthermore, for fine particles, DI exhibited positive correlation with the percentage of Lys, Glu, Asp,

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Phe, Thr, Ser, but for coarse particles, DI showed positive correlation with the percentage of different HAA species (e.g., Ala, Val, Leu and Ile) (Fig. 5). Clearly, concentrations of THAAs and composition profiles of HAA in aerosols may be related to microorganism-induced degradation processes. In compared to fine particles, the coarse particles had significantly lower THAA concentrations (Fig. S1) and DI values (Fig. 7). Moreover, compared with the DI values reported by previous studies, the DI 460 values of coarse particles were comparable to those of more degraded materials (e.g., soil and POM in hemi pelagic sediments), while the DI values of fine particles were close to those of "fresh" material (e.g., plankton, bacteria and sediment trap material) (Fig. 8), implying that AAs in coarse particles may undergo more bacterial degradation than fine particles. Our result is also comparable to that observed in precipitation at Uljin and Seoul (Yan et al., 2015). The DI values measured in coarse particles are closer 465 to those observed in Seoul, where is believed to have more advanced bacterial degradation than Uljin.
Previous studies proposed that a substantial δ 15 N-AA shifts in trophic AA group may indicate bacterial heterotrophy has occurred and those new resynthesized protein has become an important part of protein material measured (Mccarthy et al., 2007;Calleja et al., 2013). In this study, Ala and Ile were 15 N-enriched in coarse particles compared to fine particles. Similarly, recent study also observed the strong δ 15 N shift

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of Ala and Ile is accompanied by the processes of bacterial heterotrophy (Calleja et al., 2013;Mccarthy et al., 2007). Moreover, there is no uni-directional depletion or enrichment of δ 15 N -AA distribution in the Trophic-AA group between fine and coarse particle samples. The δ 15 N -AA distribution in the Trophic-AA group is more ''scattered'' in coarse particles than that in fine particles. Specifically, in coarse particles, Ala and Leu were 15 N-enriched and Pro was 15 N-depleted than those in fine particles 475 (Fig. 10). This ''scattered'' characteristic of δ 15 N-AA distribution in Tr-AA group of coarse particles may be due to the nitrogen fractionation occurred in microbial consumers selectively using Trophic-AA.
∑V could reflect the increasing trend of "scatting" δ 15 N-Trophic AA pattern related to bacterial resynthesis (Calleja et al., 2013;Yamaguchi et al., 2017). Significantly increasing ∑V values indicate organic material are more degraded by heterotrophic bacteria (Batista et al., 2014). In this study, the mean 480 ∑V value of fine particles was similar to or slightly higher than that measured in "fresh" materials https://doi.org/10.5194/acp-2020-534 Preprint. Discussion started: 23 July 2020 c Author(s) 2020. CC BY 4.0 License. (Mccarthy et al., 2007;Philben et al., 2018;Batista et al., 2014), while ∑V values of coarse particles were equal to or even higher than those of more degraded materials (Fig. 12). Accordingly, the significant higher values of ∑V measured in coarse particles than that in fine particles (p<0.05) (Fig. 5) may also imply more bacterial heterotrophic resynthesis occurred in coarse particles.

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Despite the uncertainties surrounding oxidation, nitration and oligomerization of AAs in the atmosphere, main observations remain that the difference in δ 15 N values of Source-AA (Gly, Ser, Phe and Lys) and total hydrolysable amino acids (δ 15 NTHAA) between coarse particles and fine particles was relatively small (Fig. 10). The average offset of δ 15 NTHAA value between fine and coarse particles was lower than 1.5‰ (Fig. 11a). These results appear to contrast with what one might expect for AAs in either sizes particles 490 undergo particularly more photochemical transformation than the other. Therefore, significantly lower DI values, ''scattered'' characteristic of δ 15 N distribution in Tr-AA and higher ∑V values observed in coarse particles in this study provide evidence that the difference in the THAA concentration and mol% composition distribution between fine and coarse particles may be related to AAs in coarse particles have stronger bacterial degradation state than those in fine particles.

Release of coarse "Fresh" bioparticles at the onset of the rainfall
A tight relationship between atmospheric bioaerosols and precipitation has been found by previous studies (Huffman et al., 2013;Yue et al., 2016). Since biological sources contain a large abundance of AAs (Ren et al., 2018), HAAs in aerosols can be used as tracer compounds to indicate the release of biological sources during precipitation. However, detailed size-resolved and time-resolved observation 500 for the release of bioparticles initiated by precipitation are spare and the degradation state of different sizes bioparticles has never been examined.
It is expected that the concentrations of individual AAs in aerosol were assumed to decrease during rainfall events because of the high scavenging ratio of AAs in aerosol (Gorzelska and Galloway, 1990).
In this study, form rain to dry periods, the concentrations of THAA for fine particles decreased (p<0.05)

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( Fig. S1), but the concentration of THAAs for coarse particles displayed not significant change (p>0.05) (Fig. S1). Similar variation trends of different size particles following the precipitation were also observed by (Huffman et al., 2013). They also found the steep increase of coarse particles while low concentrations of fluorescent bioparticles and total aerosol particles were found in fine particles during the precipitation, suggesting the new released AAs during the precipitation are mainly distributed in 510 coarse particles.
In addition, the large variations in the percentage of some HAA species (e.g., Pro, Ala, Val, Leu, Ile and Glu) were observed in coarse particles following the rainfall events, which imply the states of coarse particles measured during rain periods were different from the ones measured during dry periods (Fig.   3). This conclusion also supported by the variation of DI and ∑V values for coarse particles following 515 rain events. From dry to rain periods, DI values in coarse aerosol particles were significant increased (p<0.05) but the ∑V value was significantly decreased (p < 0.05) (Fig. 7), suggesting more fresh AAs in coarse particles were released during rain events, whereas, on dry days AAs in coarse particles were more degraded.
of HAA for coarse particles during the precipitation. At the onset of every rainfall events, the highest concentration of THAAs in coarse particles was observed. However, as the rainfall continued, the concentration of THAAs decreased rapidly. This temporal variation trend can attributed to the active release of these fresh biological aerosols caused by droplets splashing on porous medium are much stronger at the onset of rainfall events but with the rainfall continued, bioparticles in coarse particles were 525 suppressed by rain scavenging (Joung and Buie, 2015;Huffman et al., 2013;Yue et al., 2016). Moreover, the mol% composition of HAA in coarse particles measured at the onset of every rainfall events were significantly different from that observed in the continued stage of rainfall events. The mol% composition of HAA in the continued stage of rainfall events were similar to that observed on dry days (Fig. 2). As we discussed above, AAs in coarse particles on dry days were more degraded. Therefore, we can 530 conclude that those "fresh" protein matters are prone to release at the onset of the rainfall events and decayed swiftly with the precipitation continued.

Conclusions
2-weeks of daily aerosol samples in two size (>2.5μm and PM2.5) were measured. The significant difference was observed in the characteristics and distributions of AAs between fine and coarse particles.

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The concentrations of THAA in fine particles were significantly higher than that in coarse particles. A huge difference was also observed in the mol% compositions of THAAs between fine and coarse particle.
For fine particles, Gly, Pro, Leu and Glu were the four most abundant compounds of the THAA pool, whereas for coarse particles, Pro were the most abundant THAA specie and Leu, Ala and Val were the next most abundant species.

540
Similar δ 15 N-HAA pattern, closer δ 15 NTHAA values and small offset of δ 15 NTHAA value observed between fine and coarse particles indicates that AAs in fine and coarse particles might have the same sources.
Moreover, the δ 15 N values of hydrolyzed Gly and THAA for both fine and coarse fall within the ranges of those measured in biomass burning, soil and plant sources suggested that atmospheric AAs for both fine and coarse particles were affected by these three emission sources.

545
The difference in δ 15 N values of Source-AA and THAA between coarse particles and fine particles were small, implying AAs in fine and coarse particles may undergo the same degree of photochemical transformation. Using bacterial marker, we found that AAs in coarse particles may undergo more bacterial degradation than fine particles, which is supported by lower DI values, ''scattered'' δ 15 N distribution in the Trophic-AA group and higher ∑V values observed in coarse particles compared to fine 550 particles.
By comparing the variation of DI and ∑V values for coarse particles following the precipitation, we propose that "fresh" protein matters distributed in coarse fraction are prone to release at the onset of the rainfall events.

555
Author contributions. Ren-guo, Zhu., Zequn Wen and Yuwen Zhu designed the experiments, performed analyses, and analyzed the data. Hua-Yun Xiao were the principal investigators of the project that supported this work. All the authors have helped in the discussion of the results and collaborated in writing this article.      Figure 7. DI values (a) and (b) ∑V for fine (red box) and coarse (blue box) particles. The box encloses 50% of the data, the whisker is standard deviation of the data, the horizontal bar is the median, solid circles are outliers. The differences in means were statistically significant (two-way ANOVA, p < 0.05). Different uppercase letters denote means found to be statistically different (Tukey-HSD test) between fine and coarse particles. Different lower case letters denote means found to be statistically different (Tukey-HSD test) between rainy and dry days.