Diel variation of mercury stable isotope ratios record photoreduction of PM 2

4 Qiang Huang, Jiubin Chen, Weilin Huang, John R. Reinfelder, Pingqing Fu, Shengliu 5 Yuan, Zhongwei Wang, Wei Yuan, Hongming Cai, Hong Ren, Yele Sun and Li He 6 7 1 SKLEG, Institute of Geochemistry, CAS, Guiyang 550081, China 8 2 SKLOG, Guangzhou Institute of Geochemistry, CAS, Guangzhou 510640, China 9 3 Institute of Surface-Earth System Science, Tianjin University, 300072, China 10 4 Department of Environmental Sciences, Rutgers, The State University of New Jersey, New 11 Brunswick, NJ 08901, USA 12 5 LAPC, Institute of Atmospheric Physics, CAS, Beijing 100029, China 13 6 Laboratory of Hebei Institute of Regional Geology and Mineral Resources Survey, 14 Shijiazhuang 065000, China 15 16 *Corresponding author. 17 E-mail: jbchen@tju.edu.cn 18 19 Page S2 Materials and methods 20

For example, Rutter and Schauer (2007) and Amos et al. (2012) proposed gas-aerosol partitioning models, which suggest that more divalent gaseous Hg (GOM) may partition onto aerosols at lower temperature.If we assume that GOM could remain a constant level during daytime and night-time, relatively lower temperature at night-time should result in higher PBM in the night-time than in the daytime.However, the assumption of constant GOM over daynight time is likely untrue.According to several recent studies, the GOM measured in the field also exhibits significant diel variation, with higher GOM concentrations found during the daytime than at night (Poissant et al., 2005;Liu et al., 2007;Lan et al., 2012), likely due to the photo-oxidation of GEM.For example, the GOM measured during the spring season in Salt Lake city was equal to or lower than 4 pg m −3 at night-time and was as high as 20 pg m −3 during daytime (Lan et al., 2012).Another study reported that the GOM measured in the urban area of Detroit, Michigan was lower than 9 pg m −3 at night and as high as 13 pg m −3 during day-time (Liu et al., 2007).Apparently, the temperature effect on PBM concentration due to favored adsorption of GOM during night-time (lower temperature) may be partially (if not totally) offset by lower GOM levels during night-time.In other words, the net PBM may show less diel variation as predicted from the temperature-dependent partitioning model when GOM is also substantially lowered during the night-time.
To support the above argument, we used an inverse approach and a GOM partitioning model to compute hypothetic GOM levels corresponding to each of our PBM observations at ambient temperature.We used the GOM gas-aerosol partitioning model proposed by Amos et al., 2012, which has the following equation: log10(K −1 ) = (10±1) -(2500±300)/T, where K = (PBM/PM2.5)/GOMwith PBM and GOM in common volumetric units (pg m −3 ), PM2.5 in µg m −3 , and T in K.We used the measured PM2.5-Hg as PBM and assumed that the PM2.5-Hg measured for each sample is 100% in divalent and active mercury forms.The calculated GOM concentrations are presented in the following Table R1.In summary, the calculated GOM concentrations range from 1.5 to 31 pg m −3 , with average values of 11±5 pg m −3 during the daytime and 13±7 pg m − 3 during the nighttime.Overall, the calculated GOM exhibit insignificant (p = 0195, paired samples t-test) diel variation of GOM concentration, i.e., there would be little or no difference of GOM between day-and night-time.Close inspection of the data (Table R1) showed that half of the paired day-night samples have higher calculated GOM concentrations during the nighttime than in daytime.This is opposite to the prior findings cited above (Poissant et al., 2005;Liu et al., 2007;Lan et al., 2012) showing higher measured GOM in the daytime than in the nighttime and indicates that processes other than gas-aerosol partitioning control GOM concentrations in the environment.
Similarly, gas-aerosol partitioning of GOM does not likely account for the diel variation of PM2.5-Hg concentrations measured in this study.Meanwhile, our data showed that the average Δ 199 Hg value during the daytime (0.26‰ ± 0.40‰, 1SD, n = 26) is (statistically) significantly (p < 0.05, t-test) higher than during the nighttime (0.04‰ ± 0.22‰, 1SD, n = 30).This slight diel variation of odd-MIF of Hg isotopes was explained in terms of photoreduction of PBM during daytime.In addition we argue that the diel variations of odd-MIF of Hg isotopes does not result from GOM gas-aerosol partitioning.
In general, divalent Hg gas-aerosol partitioning is considered as chemisorption and desorption (Rutter and Schauer, 2007).Prior studies showed that the adsorption/desorption and precipitation of aqueous Hg 2+ had insignificant odd-MIF of Hg isotopes (Jiskra et al., 2012;Smith et al., 2015), suggesting that the GOM partitioning process may not result in the characteristics of odd-MIF of Hg isotopes we observed for the PM2.5 samples.
In conclusion, gas-particle partitioning may increase PBM during the night-time due to relatively lower temperature compared to the daytime.The actual increase of PBM during the nighttime may be off-set by lower GOM levels during nighttime when little or no production of GOM by the photo-oxidation of GEM may occur.It is shown that GOM is high during daytime likely due to stronger photo-oxidation.GOM can be adsorbed on to PM where the active Hg species are also photo-reduced to elemental mercury.Such a dynamic and complex adsorptionphotoreduction cycle yields lowered PBM levels, along with characteristic Hg isotope properties.
In other words, our thesis is that the photochemical reactions cause the concentration reduction of PM2.5-Hg as well as fractionation of the PM2.5-boundHg isotope compositions.
To address these issues, we have included a discussion about the possible effects of gasaerosol partitioning on the diel variation of PBM.See the revised manuscript on line 358 to 370, it reads: "A possible explanation of the observed effects of diel variation of PM2.5-Hg would be the temperature-dependent gas-aerosol partitioning of GOM (Rutter and Schauer, 2007;Amos et al., 2012), which favors more adsorption of GOM on PM during nighttime when atmospheric temperature us relatively lower than daytime.However, the magnitude of such adsorption is also proportional to the GOM concentration in the atmosphere.An inverse calculation exercise (in SI) shows that the higher PM2.5-Hg measured for our samples would require higher GOM concentrations during the nighttime, which contradicts with prior findings that GOM concentrations are significantly lower during the nighttime than the daytime as GOM is a product of photo-oxidation processes (Poissant et al., 2005;Liu et al., 2007;Amos et al., 2012).In addition, GOM gas-aerosol partitioning is considered a chemisorption and desorption process (Rutter and Schauer, 2007), which unlikely result in appreciable odd-MIF of Hg isotopes (Jiskra et al., 2012;Smith et al., 2015).Therefore, GOM partitioning would have little or no effect on the observed diel variations of Δ 199 Hg values for PM2.5-Hg." I suggest the authors consider the influence of boundary layer dynamics and stratification: daytime turbulence could lead to mixing of above lying, cleaner free tropospheric air with high MIF, whereas nighttime stratification traps Hg emissions with low MIF." --Thank you for your suggestion.We agree that the boundary layer was higher during the daytime than at night, and daytime turbulence could help to mix the air between bottom and top of the layer.As your suggest, with constant Hg emission and PM2.5 deposition rates, Hg 2+ photoreduction on PM2.5 during the daytime may be enhanced at the top of the boundary layer (up to 1500 m) on a sunny day and produce much more positive odd-MIF of Hg isotopes on PM2.5, while at night, the lower boundary layer traps a portion of daytime PBM at much low altitudes (mean of about 300 m).The mixing of residual daytime PBM with newly emitted PBM in the thinner boundary layer at night may help to explain why nighttime PBM had odd-MIF values closer to source emissions.
Per your suggestions and comments, we have added a discussion about the possible effects of the difference of boundary layer thickness during daytime and nighttime on the diel variations of Hg isotope ratios in the PM2.5 samples we collected.See the revised manuscript on line 371 to 381, it reads: "Variation in atmosphere boundary layer height (ABLH) from 1000 to 1300 m during daytime to less than 200 to 300 m during nighttime may have contributed to the diel variation in Hg isotopic composition of PM2.5-Hg (Quan et al., 2013).With a high ABLH during daytime, relatively strong turbulence may help mixing the PM2.5-Hg from the surface to the upper free troposphere, where photoreactions may be favored due to higher intensities of ultraviolet radiation on clear days.In contrast, a lower ABLH at night may weaken the vertical transport of PM2.5-Hg, but enhance the contribution from newly produced PM2.5-Hg, possibly resulting in higher concentrations of PM2.5-Hg with negative or close to zero Δ 199 Hg values from emission sources and/or GOM.However, vertically-resolved, day-night measurements of Hg stable isotope ratios in PBM and GOM are needed to fully evaluate the effects of various physical processes on diel variation of the Hg isotopic compositions for the PM2.5".
In the current MS submitted to ACP I did not find discussion of gaseous Hg(0) -aerosol partitioning, nor discussion of boundary layer dynamics.The authors should discuss with atmospheric physicists, and see if proxies of boundary layer mixing can be used.For ex. PM2.5 itself seems higher during nighttime than daytime, which is likely due to nighttime boundary layer stratification which traps pollutant emissions.Daytime heating of land and ensuing turbulence will mix boundary layer air with overlying free tropospheric air.Such mixing may, or may not, generate all the trends observed.It should be discussed and counter-argumented.
--We agree that, although PM2.5 concentrations had insignificant diel variation (p = 0.887, paired samples t-test), the change of boundary layer thickness between daytime and nighttime could affect PBM transformations, and we now address the possibility of this effect as described in our comments above.
In summary, I am convinced that the dataset is novel and of strong interest to the atmospheric Hg community and ACP readers, but I suggest the authors to better think through alternative interpretations, and to respect the reviewing process.The editor and reviewers spend time to try and make your study better.
--Thank you for your suggestions and comments.Although the editor of ES&T did not give us a chance to response your comments, we truly appreciate the editor and reviewers for their comments on this manuscript.We are very glad to have this chance to respond to your comments at here, and we revised the manuscript accordingly.
Minor comments: L99. "It is intuitive that, while both D and N PM2.5 samples may have similar local or regional sources if the wind trajectory remains unchanged, D samples could have been exposed to more solar radiation than N samples, likely resulting in diel variations in the Hg isotope compositions that are indicative of differences in photochemical transformation of PM2.5-Hg."Not sure this makes sense: if PM-Hg was emitted 1 week ago and travelled across China, the particles went through 7 day/night periods, all receiving more or less the same amount of radiation.
--We have deleted this sentence.
L211.The statistics of diel variations are discussed here, with reference to Table S3.It appears to me that paired T-tests should be reported in the text, and not means and p values for the whole dataset.A key question is whether PM2.5 shows diel variation in the paired T-test?The p values in the text do not correspond to metrics in Table S3, so the discussion is hard to follow.
L171.Why 24h back trajectories and not more?What is known about PBM lifetime in the Chinese boundary layer?I think there is a discussion in Horowitz et al., ACP, 2017 on this.
--Per your suggestion, we changed to 72-h back trajectories in the revised manuscript.The results of such 72-h back trajectory frequencies are shown below in Figure R1, indicating that the dominant air masses (over 90%) of source directions estimated from 72-h approach were very similar to those estimated using the 24-h and 48-h approaches.--We have revised these sentences for clarity (see the revised manuscript on line 341 to 346): "Interestingly, negative D 199 Hg values in daytime PM2.5-Hg were only observed during a rainy day and an extreme smog event.Since the Hg emitted from local sources had close to zero and negative values of odd-MIF, higher humidity (such as during rainy days) and heavy pollution (the extreme smog) may enhance the effect of scavenging of locally produced gaseous or particulate Hg during rain or smog events, which may therefore have contributed to the reversal of the odd-MIF signature of Hg collected as PM2.5 at these times".

Anonymous Referee #2
Received and published: 19 October 2018 This manuscript quantified the diel variation of Hg isotope composition of particulate bound mercury (PBM) and revealed that daily photochemical reduction of divalent Hg is of critical importance to the fate of PM2.5-Hg in urban atmospheres.The topic is quite interesting and is important for understanding global mercury cycling.Publication is suggested after minor revision.
--Thank you for your comments.
Line 114 Is one air sampler enough?PBM concentration in the air is quite small.To obtain enough mercury for isotope analysis, especially when the sampling time was reduced, it seems that we need more samplers.
--We used one sampler for collecting the PM samples.Among the 61 PM2.5 samples we collected, 56 had sufficient Hg mass for Hg isotope analysis.It would be better if two or more samplers were used simultaneously for sampling so that (1) sufficient mass of PBM can be obtained for isotope analysis and (2) replicates could be used for isotope analysis.
Line 163 Why do you choose the height of 500 m?
--In our back trajectory modeling, we used 500 m as the average boundary layer height in Beijing according to a prior study by (Xiang et al., 2019).The estimated backward HYSPLIT trajectories of air masses should be acceptable.Alternatively, we also used different arrival heights (200, 500, 1000 m above ground level) for estimating the backward trajectories.The results (see below Figure R2) indicate that the transport pathways are not very sensitive to the selected heights within the studied area.
Per your comments, we have added detail information in the revised version of the Supporting Information.Figure 2(a) How to explain the negative value of Δ 199 Hg on Sep 28?
--The explanation had been described in Line 363 to 373."Interestingly, negative Δ 199 Hg values in daytime PM2.5-Hg were only observed during a rainy day and an extreme smog event.Since the Hg emitted from local sources had close to zero and negative values of odd-MIF, higher humidity (such as during rainy days) and heavy pollution (the extreme smog) may enhance the effect of scavenging of locally produced gaseous or particulate Hg during rain or smog events, which may therefore have contributed to the reversal of the odd-MIF signature of Hg collected as PM2.5 at these times.In addition, the negative Δ 199 Hg values in PM2.5 may have resulted from the contribution of biomass burning with limited photoreduction effect during periods of less sunshine (Fig. 2 and Table S1) since plant foliage has negative Δ 199 Hg values (Yu et al., 2016) and more negative Δ 199 Hg values (down to −0.53‰) of PM2.5-Hg in Beijing were related to biomass burning, a source of PM2.5-Hg south of Beijing in autumn (Huang et al., 2016)." Figure 2(f) all legends are suggested to be listed on the top of this figure.It is difficult to find "clear" "cloudy" "rain" in this figure.
--We have revised the legends in the revised Figure 2(d).
Line 356 "While our results cannot exclude the effects of other possible processes, such as oxidation, adsorption (and desorption), and precipitation, based on the limited previous studies (Jiskra et al., 2012;Smith et al., 2015;Sun et al., 2016), these processes are not likely to be important to the diel variation of odd-MIF of Hg isotopes in PM2.5-Hg we observed."The observed isotope fractionation is a phenomenon while the photochemical reduction is one process leading to this phenomenon.How can you exclude the impact from other processes?Evidences are required to prove this conclusion.
--We agree that these observations may be the result of multiple processes.We now address the possible contributions of two additional physical process, adsorption of GOM to PM and reduced boundary layer mixing of PBM at night (see responses to Referee 1).
Figure 5(a) What is the main reason that caused the variation of Δ199Hg during the night time?Is it possible caused by measurement error?If this is true, it is better to point out this in method part.
--Our data showed that the Δ 199 Hg values ranged from 0.01‰ to 0.30‰ for the nighttime samples in Figure 5(a) and ranged from -0.51‰ to 0.55‰ for all nighttime samples in this study.The method we used for quantifying Hg isotopes bears an uncertainty (2SD) of 0.06‰ for Δ 199 Hg for the samples.Statistically, differences between Δ 199 Hg values for daytime and nighttime samples were clearly significant and should not have been caused by uncertainty of the method.
To help readers understand this issue, we have added the measurement uncertainty in the caption of Figure 5.

Introduction
Atmospheric mercury (Hg) consists of three operationally-defined forms including particlebound Hg (PBM), gaseous oxidized Hg (GOM), and gaseous elemental Hg (GEM) (Selin, 2009).GEM is the most abundant (about 90%) and chemically stable form (Selin, 2009), and is transported at regional and global scales.GOM has short residence times as it can readily be dissolved in rain droplets, adsorbed on particulate matter (PM), and it reacts rapidly within both gaseous and aqueous phases with or without PM.PBM contains mainly reactive Hg species such as Hg 2+ and perhaps trace quantities of Hg 0 , and is transported at regional or local scales thereby reflecting Hg pollution and cycling within short distances from emission source (Selin, 2009;Subir et al., 2012).PBM has multiple sources and undergoes complex transport and transformation processes in the atmosphere (Subir et al., 2012).
Prior studies have shown relatively constant Hg isotope compositions for GEM and very large variations of Hg isotope ratios for dissolved Hg 2+ in wet precipitation (Gratz et al., 2010;Chen et al., 2012;Rolison et al., 2013;Wang et al., 2015;Yuan et al., 2015).A few studies reported that the Hg isotope compositions of PBM also show large variations (Rolison et al., 2013;Das et al., 2016;Huang et al., 2016;Yu et al., 2016;Xu et al., 2017).Among these limited studies, Rolison et al. (2013)  isotope compositions for PM2.5 samples taken from Beijing, China, and attributed their observed seasonal variations in both MDF ( 202 to 0.51 to 0.57 ) to varied contributions from multiple sources of PM2.5-Hg, while the more positive 199 Hg values were likely produced by extensive photochemical reduction during long-range-transported.These prior results show that the Hg isotope approach can be employed for tracking sources and identifying possible transformation processes for airborne PM-Hg, and that PBM may undergo photochemical reactions that obscure its initial isotopic signature.
The goal of this study was to quantify short-term (diel) variations in the isotope composition of PM2.5-Hg in an effort to elucidate if photochemical processes could impact overall contents and isotope compositions of PM-bound Hg in an urban environment.Unlike prior studies in which PM samples were collected continuously over 24 hrs or longer, we collected two PM2.5 samples per 24 hrs with a daytime (D) sample between 8:00 a.m. and 6:30 p.m. and a nighttime (N) sample between 7:00 p.m. and 7:30 a.m..It is intuitive that, while both D and N PM2.5 samples may have similar local or regional sources if the wind trajectory remains unchanged, D could have been exposed to more solar radiation than N samples, likely resulting in diel variations in the Hg isotope compositions that are indicative of differences in photochemical transformation of PM2.5-Hg.The specific objectives of this study were to verify and quantify whether Hg isotope compositions of PM2.5 exhibit diel variations, and to elucidate whether photochemical transformation is the dominant process for such diel variations.
2 Experimental section 2.1 Field site, sampling method, and preconcentration of PM2.5-Hg Beijing was selected as the area of study because of its well-known air pollution issue (Zhang et al., 2007).Detailed information on the study site and PM2.5 sampling procedures were given elsewhere (Huang et al., 2016).During the sampling period between Sept. 15 th and Oct. 16 th , 2015, the average outdoor temperatures were 22.1 , and the average relative humidity were 45 20% and 59 19%, for D and N, respectively.The PM2.5 samples were collected using a Tisch Environmental PM2.5 high volume air sampler, which collects particles at a flow rate of 1.0 m 3 min -1 through a PM2.5 size selective inlet on a pre-combusted (450 quartz fiber filter (Pallflex 2500 QAT-, Pallflex Product Co., USA).Quartz fiber filters were wildely used to collect operationally defined PBM (Schleicher et al., 2015;Zhang et al., 2015;Xu et al., 2017).A total of 61 samples including 30 D samples and 31 N samples were collected between 8:00 a.m. and 6:30 p.m. and 7:00 p.m. to 7:30 a.m., respectively, along with 2 field blanks.They were wrapped with aluminum film, packed Meteorological data, including temperature (T), relative humidity (RH), sunshine duration, daily average wind speed (WS), were acquired from China Meteorological Administration (http://data.cma.cn), and the atmospheric ozone content (PO3) was measured concurrently.These data are summarized in Table S1.

Hg content and stable isotope measurements
The mass of each PM2.5 sample was gravimetrically quantified.Hg bound on each PM2.5 sample was extracted and concentrated for analysis of Hg content and stable Hg isotopes using the method reported previously (Huang et al., 2015).The details of the procedures are also given in supplementary material (SI).
Among the PM2.5 samples, 56 (including 26 D-and 30 N-samples) had sufficient Hg mass (> 10 ng) and were further analyzed for Hg isotope compositions using a multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS, Nu Instruments Ltd., UK) equipped with a continuous flow cold vapor generation system.Detailed protocols for the Hg isotope analysis can be found in Huang et al. (2015) and also in SI. 196 Hg and 204 Hg were not measured due to their very low abundance.Instrumental mass bias was corrected using an internal standard (NIST SRM 997 Tl) and strict sample-standard bracketing with NIST SRM as defined by the following equation (Blum and Bergquist, 2007): Hg/ 198 Hg)sample/( x Hg/ 198 Hg)NIST3133 1000 (1) where x = 199, 200, 201, and 202.MIF is reported as the deviation of a measured delta value from the theoretically predicted MDF value according to the equation: where the mass-dependent scaling factor is 0.252, 0.5024, and 0.752 for 199 Hg, 200 Hg and 201 Hg, respectively (Blum and Bergquist, 2007).
For quality assurance and control, we used NIST SRM 3177 Hg as a secondary standard and analyzed repeatedly during sample analysis session.), These values were consistent with previous results (Blum and Bergquist, 2007;Chen et al., 2010;Huang et al., 2015;Huang et al., 2016).The uncertainties of PM2.5-Hg isotope ratios listed in Table S2 were calculated based on repetitive measurements.However, if uncertainty of the isotopic compositions for a given sample was smaller than the uncertainty of CRM GBW07405, the uncertainty associated with that sample was assigned 2SD uncertainties (0.14 , 0.06 , 0.04 and 0.07 for 202 199 Hg, 200 Hg 201 Hg) obtained for longterm measurement of the CRM GBW07405.

Air mass backward trajectories
To identify possible pathways of PM2.5-Hg transport, backward HYSPLIT trajectories of air masses at a height of 500 m above ground level and arriving at the sampling site were simulated.
Backward trajectories for each D or N sample were calculated every 1 hrs using the Internet-Based HYSPLIT Trajectory Model and gridded meteorological data (Global Data Assimilation System, GDAS1) from the U.S. National Oceanic and Atmospheric Administration (NOAA) (Fig. S1).The obtained average directions of arriving air masses for each sample were summarized in Table S1.The frequencies of backward trajectories were calculated for all the samples taken during Sept. 15 th to Oct. 16 th 2015 using the Internet-Based HYSPLIT Trajectory Model and the archived GDAS0p5, with an interval of 3 hrs.Each trajectory had a total run time of 24 72 hrs and a grid resolution of 0.5 0.5 degree trajectory frequency.The simulation results showed the dominant air mass was arriving from southwest of the sampling site during the sampling period (see Fig. 1).Hg, and their results were summarized in Table S3.

Diel variation of PM2.5-Hg
The chronological sequence of Hg stable isotope ratios, along with PM2.5 sample properties and weather conditions for the 56 PM2.5 samples are presented in Figure 2 (see also Tables S1 and   201 Hg values).The major features of this dataset include: i) large variations in both MDF and odd-MIF of Hg isotopes, ii) significant diel differences in Hg isotope ratios, iii) correlations of weather conditions and air mass backward trajectories with Hg isotope signals, and iv) detectable even-MIF. .The overall variations of Hg isotope ratios for these 12-hr D/N PM2.5 samples are generally consistent with several prior reports for the 24-hr PBM samples (Rolison et al., 2013;Das et al., 2016;Huang et al., 2016).
T-test results (Table S3) showed that diel variation was statistically significant (p < 0.05) for

Diel variation in odd-MIF of PM2.5-Hg independent of air mass source
Many consecutive D-N sampling intervals had similar air mass back trajectories (Table S1 and The uncertainty for measurement of 199 Hg and Hg of PM2.5 samples were 0.06 and 0.12 in 2SD, respectively.D  200 Hg signatures was also observed in PM2.5-Hg.Prior studies reported contribution may be very limited. 200Hg values are weakly, but significantly 199 Hg (r 2 = 0.13, p < 0.01) (Fig. S6) and 202 Hg (r 2 = 0.27, p < 0.01) (Fig. S7).

Even isotope MIF
No mechanistic explanation is available yet for such observations, however.

Conclusions
This study showed significant diel variations of Hg isotopic compositions for ambient PM2.Although the specific reactions and mechanisms that control Hg isotope fractionation (MDF and MIF) in Beijing PM2.5 could not be explicitly determined from this field study, our result illustrated that, in addition to variation in sources, photochemical reduction appears to be an important process that affects both the content and isotopic composition of PM2.5-Hg.Further systematic study is thus needed to better quantify the photoreduction of PM2.5-Hg to estimate the percentage of reduced Hg it produces and its impact on the global biogeochemical cycling of Hg.

Figure R1 .
Figure R1.The frequencies of backward trajectories were calculated for all the samples using the 24h, 48h and 72h Backward Trajectory Model.

Figure R2 .
Figure R2.The frequencies of backward trajectories were calculated for all the samples using the 24h Backward Trajectory Model at three deferent heights of 200, 500 and 1000 m above ground level.

Figure 2 Figure R3 .
Figure 2 This figure is too busy.Instead listing all data according to time series, is it possible to classify the figure into several subgroup according to the topic you wants to discussed?This figure can be moved to supporting information.

Figure 1 .
Figure 1.Geographic location of the PM2.5 collection site in Beijing, China (Baidu Map image) and average air mass back trajectories during sampling from Sept. 15 th to Oct. 16 th , 2015 (left), and characteristics of North-West vs. South-East arriving air masses.2.4 Statistical analysis Figure 2. Chronological

FigFigure 5 .
Fig. S1), suggesting that the dominant sources of PM2.5-Hg did not vary over each such 24 hr sampling period.For example, pairs Sept-16-D and Sept-16-N, Sept-17-D and Sept-17-N, Sept-20-D and Sept-20-N, Sept-21-D and Sept-21-N, Oct-1-D and Oct-1-N, Oct-2-D and Oct-2-N, Oct-4-D and Oct-4-N have similar air mass trajectories from the southwest, and pairs Oct-8-D and Oct-8-N, Oct-9-D and Oct-9-N, Oct-10-D and Oct-10-N, Oct-11-D and Oct-11-N, Oct-12-D and Oct-12-N have similar air mass trajectories from the northwest and north (Fig. S1).It is reasonable to assume, therefore, that each of these D-N PM2.5 sample pairs had identical 5-Hg collected in the city of Beijing.The Hg isotope signatures featured a large range of MDF ( 202 to 0.55 ) and significant (p < 0.05) 199 Hg values in daytime samples (0.26 ) than at night (0.04 ).The results clearly indicated that the Hg isotope compositions of PM2.5-Hg are impacted variously by both weather conditions (such as sunlight duration), which may promote the photochemical reaction, and directions of air mass trajectories, which are related to possible sources of PM2.5.D-N paired samples having similar air mass backward trajectories and hence similar sources exhibited strong positive correlations between 199 Hg and 201 Hg with a slope 199 Hg and 202 Hg with a slope of 1.15, and a decrease in the content of Hg in PM2.5199 Hg increased.These results provide isotopic evidence that local, daytime photochemical reduction of divalent Hg is of critical importance to the fate of PM2.5-Hg in urban atmosphere.

Table R1 .
Calculated GOM concentrations of day and night samples.The value of GOM concentrations higher at night than the consecutively days are in bold text.