Semi-volatile aerosols in Beijing (R.P. China): Characterization and influence on various PM 2.5 measurements

Transcription

1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112,, doi: /2006jd007448, 2007 Semi-volatile aerosols in Beijing (R.P. China): Characterization and influence on various PM 2.5 measurements J. Sciare, 1 H. Cachier, 1 R. Sarda-Estève, 1 T. Yu, 2 and X. Wang 2 Received 27 April 2006; revised 26 March 2007; accepted 16 May 2007; published 19 September [1] During summer, the Beijing urban area meets contrasting meteorological conditions including warm and humid monsoon winds from the southeast bringing high levels of pollution, with PM 2.5 mass concentrations often exceeding 100 mg/m 3. The specific weather conditions and aerosol chemical composition observed at that time offer a unique opportunity to address the question of the contribution of semi-volatile material (SVM) in the continuous PM records available for the south East Asian urban regions. Different PM 2.5 measurements were evaluated during a 3-week field campaign performed in Beijing downtown during the summer 2004, and consisting of a Rupprecht & Patashnik (R&P TEOM) (heating air sample at 50 C), R&P TEOM-FDMS (enabling SVM measurement), optical GRIMM counter, and filter weighing. A good agreement was found between the different TEOM measurements during the campaign with the exception of the periods of high Relative Humidity (RH), which exhibited SVM levels (derived from PM 2.5 loss in the TEOM heated at 50 C) as high as 140 mg/m 3. Continuous artefact-free PM 2.5 nitrate measurements were performed simultaneously and showed a close relationship with the TEOM-derived SVM, accounting for half of this SVM. To better document the role of RH on SVM, estimates of liquid water content (LWC) in aerosols were derived from light scattering coefficient and integrated aerosol volume measurements performed in the field at different RH. LWC is shown to be related in a quantitative way to the levels of SVM and nitrate in aerosols, and thus is believed to play a major role in the gas-particle partitioning of semi-volatile species in Beijing aerosols. Citation: Sciare, J., H. Cachier, R. Sarda-Estève, T. Yu, and X. Wang (2007), Semi-volatile aerosols in Beijing (R.P. China): Characterization and influence on various PM 2.5 measurements, J. Geophys. Res., 112,, doi: /2006jd Introduction [2] Semi-volatile aerosol components can reside largely in the condensed phase or in the gas phase depending on atmospheric conditions. In the current scientific literature, this semi-volatile material (SVM) is commonly partitioned into its organic fraction (Semi-Volatile Organic Compounds, SVOC) and its inorganic fraction (mainly ammonium nitrate, NH 4 NO 3 ). [3] In the recent years, many studies have reported that these two SVM components can represent a significant mass fraction of submicron particles in urban atmospheres and will play a subsequent important role on many urban aerosol properties such as hygroscopicity and light scattering [Malm et al., 2005b]. An exhaustive and representative picture of the chemical composition of urban aerosol (including its SVM fraction) is then clearly needed with a special attention in developing countries since, in the near future, urban population is expected to occur primarily in 1 Laboratoire des Sciences du Climat et de l Environnement (LSCE), Gif-sur-Yvette, France. 2 Beijing Municipal Environmental Monitoring Centre (BMEMC), Beijing, China. Copyright 2007 by the American Geophysical Union /07/2006JD these countries; one billion inhabitants increase for Asia, three hundred million in Africa by [4] The classical methods used for sampling of aerosols based on the use of filters or filter packs, can lead to artefacts such as loss of SVM. Many studies have reported these sampling artefacts [see for instance Slanina et al., 1992; Chow, 1995], which are caused by reactions on the surface of the filter or by evaporation of compounds such as ammonium nitrate. The combination of denuders, to strip nitric acid, and a filter pack (consisting of Teflon and impregnated filters) will in principle result in correct nitrate measurements. On the other hand, blank problems as well as the total amount of experimental work needed for such measurement will make it more difficult to run a sampling programme with sufficient time resolution to investigate factors controlling levels of ammonium nitrate. [5] Several studies performed in various urban sites of North America have also shown that continuous PM measurements [Rupprecht & Patashnik (R&P TEOM), Patashnik and Rupprecht, 1991] also fail to measure this SVM [Long et al., 2003; Eatough et al., 2003; Grover et al., 2005; Lee et al., 2005]. As a result, little is still known from field studies on the factors controlling the SVM levels in the aerosol phase. [6] SVOC enter the atmosphere by direct emission from biogenic or anthropogenic sources, such as vegetation and 1of14

2 combustion emissions. They are also the result of the oxidation of volatile organic compounds (VOC) mainly by O 3,NO 3 and OH. The oxidation process adds functional groups to the organic gas molecules and thus lowers their vapor pressure. Part of the reaction products will be semivolatile (SVOC) and will condense through physical adsorption and/or absorption mechanisms onto a pre-existing organic and/or water film on particulate matter [Pankow, 1987]. Particular attention has been paid to the importance of air temperature in the partitioning of SVOC between gas and particulate phase. Based on a model study, Strader et al. [1999] have suggested that there exists an ideal temperature for secondary organic aerosols formation, lying in the range C. Higher temperatures will induce an increase in the oxidation efficiency of reactive organic gases but also will induce a decrease in the partitioning coefficient of SVOC (e.g. higher volatilization). Based on field studies, Fan et al. [2004] have reported that this air temperature driven process controls the partitioning of SVOC; with higher concentrations of SVOC in the aerosols being observed during the night coincident with a decrease in temperature. Modey et al. [2004] have reported a secondary origin for SVOC in urban aerosols, with the highest values in the particulate observed at midday, coinciding with ozone maxima. Finally, it is worthwhile noting here that levels of SVOC should also depend on their source origin, significant amount of SVOC being expected, for instance, in biomass burning aerosols [Jeong et al., 2004]. [7] Partitioning of the inorganic fraction of SVM is much better constrained from thermodynamic models which have demonstrated fairly well prediction of nitrate aerosol concentrations observed in the field [Takahama et al., 2004]. The physical state of aerosols (liquid / solid) is an important input to these thermodynamic models, demonstrating that Relative Humidity (RH) is a major parameter controlling the partitioning of nitrate aerosol. This has been confirmed in field observations by Charron et al. [2004] who have reported that high RH promotes the levels of ammonium nitrate in the particulate phase, in agreement with thermodynamic models [see for instance Ansari and Pandis, 1999]. [8] Most of this work on SVM in aerosols were performed at urban/suburban sites of Northern America or Europe. In that way, they are representative of anthropogenic/biogenic aerosol sources as well as meteorological conditions that correspond to mid-latitude industrialized countries. To draw a more complete picture on the role of SVM in the urban particulate pollution, similar studies are clearly needed for other urban areas, with a special attention to Asian cities [Guttikunda et al., 2005]. The levels of SVM in aerosols are potentially very important considering the high PM concentrations recorded at these locations [Zhang and Eatough, 2000]. This has been already confirmed for Beijing (R.P. China) where high levels of ammonium nitrate have been monitored for the months of May-June 2000 [Zhang et al., 2004 and references therein], with PM 2.5 concentrations similar to sulfate and ranging from 8 to 55 mg/m 3. It should be noticed here, that these nitrate measurements, performed by means of a steam jet aerosol collector (SJAC), were artefact free and have also shown that classical filter-based measurements (e.g. with no denuders to remove HNO 3 and no back filter to correct for nitrate volatilization) were biased and could underestimate nitrate concentration by some 70%. [9] The major focus of the present work concerns first the mass contribution of SVM in PM 2.5 in Beijing for the summer period. Different real-time and integrated PM 2.5 measurements were then evaluated in the field to test their ability to properly determine both non-volatile and semivolatile material in aerosols. During this experiment, strong attention was paid on the role of RH, since Beijing experiences warm and humid air masses during summertime. Therefore, part of the aerosol setup was dedicated to the determination of liquid water content (LWC) in the particulate phase. Real-time artefact free measurements of nitrate aerosols in PM 2.5 were used here to complete our study on the factors controlling the levels of SVM in the particulate phase. For the purposes of this study, it needs to be clearly and unambiguously stated here that SVM is partitioned into organic fraction (SVOC) and its inorganic fraction (mainly ammonium nitrate), and thus does not include liquid water content. 2. Instrumentation 2.1. Sampling Site Description and Meteorological Overview [10] A 3-week experiment was performed during August 2004 in downtown Beijing. A detailed description of the sampling site is given in Guinot et al. [2007b]. Briefly the sampling site is located at 4 km West from Tiananmen Square, between the Second and the Third Ring Roads, and top of the Beijing Municipal Environmental Monitoring Centre (BMEMC) building, roughly about 30 m above ground level. Simultaneous aerosol measurements performed at a different location in downtown Beijing (Cachier et al., unpublished results) have shown that this site was not directly impacted by local traffic sources and could be considered as representative of the urban pollution of Beijing City. [11] Two periods of high RH (> 60%) were observed at the beginning and at the end of the experiment; respectively on the 6-12/08 (period H1) and the 25-27/08 (period H2). Air temperature (T) daily average was in the range of 26.7 to 30.3 C, and 23.1 to 25.5 C during these two periods, respectively. These wet and warm periods were characterized by air masses originating from regions south of Beijing and by low air ventilation, inducing high pollution concentration levels [Wehner et al., 2004; Cachier et al., unpublished data] and the highest levels of sulfate / nitrate and gaseous precursors (SO 2 and HNO 3 ) recorded at our sampling site (Guinot et al., unpublished data). As a matter of fact, a non-negligible change in atmospheric concentrations of sulfate and nitrate in aerosols is expected during the periods H1 and H2. The period D, between these two wet periods, is characterized by RH below 60% and T daily average in the range 20.6 to 27.6 C. Along the campaign, these two parameters show diurnal variations in the range of 15% for RH and 6 8 C fort. [12] Of particular interest for our SVM study are the high temperatures observed during the study which should induce a lowering of the gas-to-particle conversion of oxidized organic (SVOC). On the other hand, strong changes are observed in RH (from 20 to 90%) which would play a major role in the partitioning of SVM at least for nitrate aerosols. An important instrumental setup was then 2of14

3 deployed in the field in order to investigate the levels of SVM and their potential RH-dependence. A full description of this aerosol setup is given below PM 2.5 Measurements From R&P TEOM 1400 [13] Continuous measurements of PM 2.5 were performed by a classical Tapered Element Oscillating Microbalance from Rupprecht & Patashnik (R&P TEOM, model 1400a). The monitor probe is heated at 50 C in order to avoid water condensation [Patashnik and Rupprecht, 1991]. However, this technique is likely to fail in measuring SVM in aerosols, which partly volatilize during the collection step. Then, uncertainties associated with the PM 2.5 measurements performed with this heated TEOM cannot be determined and largely depends on the concentration of SVM in aerosols. Non volatile PM measurements performed by this instrument will be referred as PM 2.5 (TEOM 50 C) later in the text PM 2.5 Measurements From R&P TEOM FDMS [14] A TEOM (model 1400a) equipped with a Sample Equilibration System (SES) and a Filter Dynamic Measurement System (FDMS, 8500 model series) was set up in parallel with the R&P TEOM 1400a. These additional devices are devoted to the evaluation of SVM (excluding liquid water content) in aerosols : the sample equilibration system (SES) of this second TEOM allows reduction of heating at the inlet from 50 C to30 C, maintaining sample RH below 25% by the mean of a multi-channel nafion permapure dryer. This SES thus decreases partly the loss of SVM in aerosols compared with a classical TEOM heated at 50 C. However, the complete collection of SVM on the filter deposit in the TEOM will be only resolved by use of the 8500 FDMS system, which provides a full determination of volatile mass through a self-referencing gas conditioning scheme. The TEOM FDMS will thus provide two different PM 2.5 measurements: a first one using only the SES device and referred later in the text as PM 2.5 (TEOM 30 C) ; a second one, using both SES and FDMS devices and referred as PM 2.5 (TEOM FDMS). Noteworthy, in previous studies real-time PM measurements provided by the TEOM FDMS have shown to compare very well with other real-time measurement obtained from other analyzers taking into account SVM [Grover et al., 2005]. Based on these results, PM 2.5 measurements performed with a TEOM-FDMS were given with an uncertainty of the order of 5%. In the following sections, measurements performed by the R&P TEOM FDMS will be considered as a reference for PM 2.5 as it will enable the evaluation of non volatile material (like the TEOM 50 C) as well as SVM. It will be also assumed later that any PM loss calculated as the difference between this PM 2.5 (TEOM FDMS) reference and the other PM 2.5 from heated TEOMs (30 C and 50 C) will refer to volatilization of SVM PM 2.5 and Ion Measurements From Filter Sampling [15] A total of 58 ambient aerosol samples were collected in the field, for a period of 18 consecutive days (09/08-27/ 08) with Stacked Filter Units (SFUs). The SFUs consist of an 8-mm pore size 47-mm diameter Nuclepore polycarbonate filter mounted in front of a 0.4-mm pore size 47-mm diameter Nuclepore polycarbonate filter. Similar devices have been successfully used in other studies [Maenhaut et al., 1994; Andreae et al., 2002; Sciare et al., 2005] and have shown to compare well with other PM measurements [Hitzenberger et al., 2004]. After 24 h equilibration at room temperature and RH below 20%, the Nuclepore filters from SFUs were weighed at LSCE by the mean of a Sartorius microbalance (Model MC21S) of 1 mg readability. The uncertainty in the gravimetric measurement is typically of the order of 10 mg, which represents for our experiment, an averaged error on the weighing mass of the order of 5%. At the flow rate of 17.7 ± 2.9 l/min (7.7 cm/s face velocity), the 50% cut-point diameter the 8-mm pore size filter is estimated here to be of the order of 2.5 ± 0.2 mm aerodynamic diameter (AD) following the calculation by John et al. [1983]. PM 2.5 measurements from our filter sampling presented later in the discussion will thus refer to the gravimetric measurements of the 0.4-mm pore size Nuclepore filter. Although sampling artifacts (adsorption/volatilization of SVM) are inherent to this filter method, it is interesting to note that it leads to a very satisfactory chemical mass balance as reported in detail by Guinot et al. [2007a]. [16] Calcium and sodium levels in PM 2.5 are of particular importance in our SVM study since they may affect the gasaerosol equilibrium by shifting the equilibrium balance to an anion-limited status, which benefits the uptake of nitrate, thus forming Ca(NO 3 ) or Na(NO 3 ). On the other hand, this formation will reduce the amount of semi-volatile nitrate (NH 4 NO 3 ). The averaged mass concentrations of calcium and sodium in PM 2.5 were respectively, 0.6 and 0.1 mg/m 3 for the duration of the campaign. These concentrations are not influenced by filter sampling artifacts and can be compared with the averaged concentration of 14.7 mg/m 3 of nitrate determined by our fast and artifact free measurements (see later on). The low levels of Ca and Na are consistent with those reported by He et al. [2001], Guinot et al. [2007b] and Zhang et al. [2004] for summertime, and thus do not contribute significantly to the neutralization of nitrate in PM 2.5. Finally, the filter based chemical mass balance has shown that PM 2.5 ammonium levels were sufficient to fully neutralize both sulfate and nitrate. Based on these results, we can assume that most of the nitrate found in PM 2.5 is semi-volatile PM 2.5 Measurements From an Optical GRIMM Counter [17] In the following sections, GRIMM measurements will be used to get (1) an estimate of PM 2.5 (which will be compared in a quantitative way with other PM 2.5 measurements), and (2) a semi-quantitative estimate of liquid water content (LWC) in aerosols. [18] Aerosol number size distribution was performed in the field by means of two optical counters (GRIMM, Model 1.108), which classify particles within 15 channels from 0.3 to 20 mm in diameter. These two counters were operating in parallel during the Beijing campaign: one at ambient RH, the second at low RH (below 20%). This low RH was achieved by the use of a TSI silica gel Diffusion Dryer (Model 3062) mounted upstream of the counter. These two counters were intercompared at RH < 20% at the beginning and at the end of the campaign without 3of14

4 Figure 1. Field mass calibration of the GRIMM optical counter. PM measurements on the Y-axis are obtained from the GRIMM back-filter weighing. PM measurements on the X-axis are obtained by summing the volume integrated aerosol distribution for each of the filter sampling intervals. showing any significant difference (below 5%) for all channels. [19] Following recommendations of the constructor, the GRIMM counter measurements can be converted into PM 1 / PM 2.5 /PM 10 real-time measurements through field mass calibration ; all the particles measured by the GRIMM counter being collected on pre-weighed PTFE filters to allow gravimetric determinations of the aerosol mass. Such field mass calibration of the GRIMM counter is based on a conversion factor (CF) which can be expressed as the ratio between aerosol mass (obtained from the gravimetric measurements) and integrated aerosol volume measurements obtained from the GRIMM and calculated for the duration of the filter sampling (typically several hours to several days). [20] For the Beijing campaign, gravimetric measurements of Teflon filters were performed at LSCE as for the filter sampling (previous section). Results of the field mass calibration for the GRIMM counter running at low RH are reported in Figure 1. This calibration was performed from filters sampled for the whole duration of the campaign and shows a good agreement for the two datasets for the duration of this study. The slope of (2.26) corresponds to the CF that will be used to calculate PM 2.5 from the GRIMM counter running at low RH. This CF is not only related to the aerosol density but also accounts for the mass that is not measured by the GRIMM below 0.3 mm. It is also important to note here that the use of CF involves many uncertainties that can induce significant deviations in PM measurements: [21] (1) PM 1 /PM 2.5 /PM 10 real-time GRIMM measurements are obtained from the same correction factor (CF), and thus assume that this CF does not depend on the aerosol size. This is probably the most critical approximation of this method since CF is calculated from a mass calibration performed on bulk aerosols and thus accounts for (i) the aerosol density of bulk aerosols and (ii) the mass contribution of missing submicron mass (below 0.3 mm) relative to TSP. If these assumptions are acceptable for TSP and PM 10 GRIMM measurements, they are more questionable for PM 1 and PM 2.5. [22] (2) The filter-based mass calibration will induce also some positive/negative artifacts, which should not affect significantly PM 10 or TSP data but much more the PM 1 and PM 2.5 data which are known to contain the whole faction of SVM responsible for these positive/negative artifacts. [23] Finally, water uptake onto particles will represent another calibration issue for GRIMM counter running at ambient RH as it will change the index of refraction of particles and thus will affect the size distribution calculated by the optical counter Scattering Coefficient Measurements From Nephelometer [24] In the following sections, nephelometer measurements will be used at different RH to obtain, in a qualitative way, an indication of the aerosol wet/dry state. Two monowavelength (525 nm) integrating nephelometers (ECO- TECH, Model M9003) were operating in parallel during the Beijing campaign: one at ambient RH, the second at low RH (below 20%). As for the GRIMM counters, this low RH was achieved by the use of a TSI silica gel Diffusion Dryer (Model 3062) mounted upstream of the nephelometer. Light scattering coefficient (s sp ) measurements from these nephelometers were performed with a 50% cut-off diameter of 2.5 mm. Fully automatic zero check was configured in the instrument setup on a daily basis without showing any significant shift (below 1 Mm 1 ). Light scattering measurements are reported in the following with a 5% uncertainty which accounts for the error in the calibration performed prior to the campaign by the manufacturer and the aerosol loss in the sampling line. Intercomparison exercises (at RH below 20%) were performed between the two nephelometers at the beginning and the end of the campaign showing a deviation within the uncertainty of 5% given for s sp measurements. RH measurements performed by the nephelometer at ambient conditions showed a good correlation with RH measurements performed by the R&P TEOM FDMS (r 2 = 0.94, N = 374) and an averaged RH difference of 6.0 ± 4.2% due, most probably, to the heating of the nephelometer cell. 4of14

5 Figure 2. Temporal variations of sulfate and nitrate concentration in fine aerosols derived from SJAC- IC measurements. Grey rectangles represent the periods of high RH (H1 & H2) Fast Real-Time Anion Measurements [25] The anion composition of the fine particles (A.D. < 2.5 mm) was determined on-line in the field for a period of 17 consecutive days (08/08-27/08) by Steam Jet Aerosol Collection with subsequent Ion Chromatography analysis (SJAC-IC). This SJAC uses basically the same approach as the one reported by Khlystov et al. [1995] and has been successfully tested against classical filter sampling methods to derive the atmospheric concentration of submicron sulfate and nitrate aerosols [Sciare et al., 2007]. Briefly, annular denuders are mounted upstream of the SJAC in order to remove acidic and basic gases. The air stream is then rapidly mixed with a steam of milli-q water inside a mixing reservoir. The resulting high supersaturation causes aerosol particles to grow rapidly into droplets of several micrometers. These droplets, containing dissolved aerosol species, are collected by a cyclone. The aerosol solution collected in the cyclone is constantly pumped out with a peristaltic pump to a DIONEX Reagent Free Ion Chromatograph (IC, Model ICS 2000), equipped with a 2-mm ASRS, 2-mm pre-column and AS-11 column, and a 100-ml injection loop. Analysis was performed in isocratic mode at 12 mm of KOH, for quantitative determination of the 3 major anions, Cl, NO 3, and SO 4 2, every 5 min. A total of 5500 determinations of these 3 ions were then available for the duration of the campaign. [26] Based on these settings, IC sensitivity for these 3 anions is typically of the order of 1 ppb, which represents for the Beijing campaign an atmospheric concentration of 0.08 mg/m 3. This is two orders of magnitude smaller than the atmospheric concentrations of NO 3, and SO 4 2 recorded during the campaign. Field calibrations of IC with standards were regularly performed during the campaign without showing any significant drift. The denuder efficiency was checked every 2 3 days by placing a total filter in front of the annular denuders and analyzing the levels of ions. Recorded nitrate and sulfate levels were on average 2.5 and 2.8% of their atmospheric concentrations, respectively during the campaign. An overall uncertainty of 10% is given for nitrate and sulfate measurements and takes into account the errors in liquids flowrate, air flowrate, IC calibration and blank correction. [27] Temporal variations of these species are reported in Figure 2 together with the periods of high RH (H1 & H2) observed at the beginning and at the end of the campaign. Average concentrations of 14.6 ± 9.3 mg/m 3 and 18.0 ± 11.4 mg/m 3 were calculated for nitrate and sulfate, respectively for the whole duration of the campaign. These values compare well with those reported in literature for Beijing fine aerosols [Zhang et al., 2004]. The wet periods were characterized by high nitrate and (to a less extent) high sulfate levels with average concentrations of 24.3 ± 9.4 mg/m 3 (nitrate) and 26.8 ± 12.6 mg/m 3 (sulfate), bringing these two species at similar levels despite the semi-volatile behavior of nitrate aerosols. [28] A ph meter (RADIOMETER, Model CDC749) and a conductivity meter (RADIOMETER, Model CDM230) were set downstream of the SJAC, in parallel to IC, in order to measure (every 10s) the ph and the conductivity (l) of the aerosol solution collected by the SJAC. These measurements were regularly calibrated and were used to better constrain our IC measurements through reconstruction of the conductivity. The conductivity of the aerosol solution collected by the SJAC can be expressed as: l calculated ¼ Sl x ¼ S ðz *l x * ½XŠÞ ð1þ 5of14

6 Figure 3. Reconstruction of the conductivity of the SJAC solution from in situ ph and IC measurements, and comparison with in situ conductivity measurements. where z stands for the ion charge, l x the molar conductivity of the species X and [X] its concentration. Assuming that SO 4 2,NO 3,NH 4 + are the major ions in the fine mode (see Section 2.4), and that [H + ] and [HCO 3 - ] are the major ions controlling the conductivity of ultra-pure water, equation (1) can be reduced to: l calculated ¼ l SO4 ½SO2 4 Šþl NO3 ½NO 3 Šþl NH4 ½NHþ 4 Š þl H ½Hþ Šþl HCO3 ½HCO 3 Š [29] The concentrations of [SO 4 2 ], [NO 3 ] and [H + ] were determined by IC and a ph meter. The neutral charge of the solution leads to: [NH 4 + ]=2[SO 4 2 ] + [NO 3 ] [H + ]. [30] Carbonates can be calculated as: ½HCO 3 Š¼ðK a1 *k H *P CO2 Þ=½H þ Š where K a1 stands for the equilibrium constant of the reaction (HCO 3 +H + $ H 2 CO 3 ), k H is the Henry law constant of the CO 2 dissolution and P CO2 is the CO 2 partial pressure. [31] The comparison between 30-min averaged l calculated and l measured is reported in Figure 3. The very good agreement [r 2 = 0.90; N = 307, the slope close to one (0.99) and the intercept close to zero ( )], demonstrates the robustness of the assumptions, in particular the neutralization of SO 2 4 and NO 3 by NH + 4. It also points out the reliability of our SJAC-IC measurements, in particular ð2þ ð3þ [NO 3 ] concentrations which cannot be correctly assessed through classical filter based methods. 3. Results and Discussion 3.1. Comparison Between the Different TEOM PM 2.5 Measurements [32] Three different TEOM datasets are available for this comparison: PM 2.5 (TEOM 50 C), PM 2.5 (TEOM 30 C), and PM 2.5 (TEOM FDMS). Hourly averaged measurements from these instruments are reported in Figure 4a together with an indication of the two periods of high RH (H1, H2) and low RH (D) depicted previously. Interestingly, the H1 and H2 periods coincide with the highest PM 2.5 concentration recorded during the campaign (up to 327 mg/m 3 for TEOM-FDMS measurements) but also coincide with the highest discrepancies between the three TEOM measurements. During the dry period (D), the three TEOM measurements compare well, with PM 2.5 concentrations ranging from 10 to 130 mg/m 3. [33] To better understand these discrepancies, the dataset was first divided in two parts corresponding to periods of high RH (H1, H2) and low RH (D). Then, our dataset was processed following the statistical method described by Eatough et al. [2001] and widely used to compare the precision of various PM measurements [Grover et al., 2005; Lewtas et al., 2001]. Results are reported in Table 1 for the periods (H1, H2) and (D). A good agreement between the three TEOM measurements is observed for the period D, with slopes close to 1 (ranging from 0.93 to 0.96), similar closely average concentrations (52.4 and 54.0 mg/m 3 ), and 6of14

7 Figure 4. Comparison of PM 2.5 measurements from: (a) the three TEOM datasets; (b) TEOM-FDMS and GRIMM optical counter; (c) TEOM-FDMS and filter method. The blue rectangles represent the periods of high RH (H1 & H2). bias of only 4.4 and 2.4 mg/m 3. For the wet periods (H1 & H2), comparison between TEOM FDMS and TEOM(30 C) is remaining very good (r 2 = 0.99) but leads to a slight underestimation of PM 2.5 done by the TEOM(30 C); typically of the order of 10%. Comparison between TEOM- FDMS and the classical TEOM(50 C) is less satisfactory (r 2 = 0.93) and leads to an even higher underestimation of PM 2.5 from the TEOM(50 C) of about 23%. [34] From these results, it can be reasonably assumed that the major discrepancies between the different TEOM datasets are originating from SVM volatilization, and that this artifact has been found to be more important in the TEOM(50 C) than in the TEOM(30 C). More interesting, these results also suggest that RH is a key factor of the PM loss in heated TEOMs, high RH being concomitant with high levels of SVM in aerosols Comparison Between TEOM-FDMS Results and Other PM 2.5 Measurements [35] Comparison of TEOM-FDMS with two other PM 2.5 measurements (GRIMM at RH < 20% in Figure 4b, and SFUs in Figure 4c) leads to more of a contrast in results. Discrepancies evident in this figure are not only related to SVM volatilization and are discussed below Comparison With the SFU Measurements [36] When our TEOM FDMS data are restricted to the SFU sampling period (Figure 4c), the averaged TEOM FDMS and SFUs PM 2.5 concentrations are respectively 93.6 and 56.2 mg/m 3. This comparison performed for the (H1, H2) periods is unsatisfactory (r 2 = 0.80) and shows an underestimation of filter sampling by roughly 40 to 50% compared to TEOM-FDMS (Table 1). This result is 7of14

8 Table 1. Results of the Statistical Analysis of PM 2.5 Measurements for the Periods of High (>60%) and Low (<60%) RH Comparison X versus Y n r 2 Slope PM 2.5 (H1 & H2) Periods of High RH PM 2.5 D Period of Low RH Intercept mg/m 3 X Average, mg/m 3 X-Y Bias, mg/m 3 s, mg/m 3 s,% TEOM-FDMS vs. TEOM(30 C) a ± ± TEOM-FDMS vs. TEOM (50 C) a ± ± TEOM-FDMS vs. GRIMM a ± ± TEOM-FDMS vs. Filters a,b ± ± TEOM-FDMS vs. TEOM 30 C a ± ± TEOM-FDMS vs. TEOM 50 C a ± ± TEOM-FDMS vs. GRIMM a ± ± TEOM-FDMS vs. Filters a,b ± ± a Based on 1-h average results. b Based on the duration of each filter sampling. somewhat expected for these periods considering that SVM is not collected in a quantitative way on the filters. The comparison for the D period is less comprehensive with no obvious correlation between TEOM-FDMS and filter sampling measurements (r 2 = 0.23) and a PM 2.5 underestimation of the order of 40% for filter sampling measurements. These artifacts from filter sampling are not fully understood yet and could possibly originate from a partial clogging of SFUs. Although these SFUs lead to a very satisfactory chemical mass balance, they appear to be inaccurate for PM 2.5 measurements in Beijing during summertime Comparison With GRIMM Measurements [37] During the (H1, H2) periods, TEOM-FDMS vs. GRIMM PM 2.5 measurements do agree, with an even better correlation coefficient (r 2 = 0.95) than found in the TEOM- FDMS vs. TEOM(50 C) comparison (Table 1). This very good correlation could originate from the fact that sizeresolved number measurements provided by the GRIMM counters are performed without heating the sampled air and thus account in a quantitative way for SVM in aerosols (which is not the case for TEOM(50 C)). On the other hand, the use of CF to derive PM 2.5 GRIMM measurements appears to be questionable and results in an underestimate of PM 2.5 of around 25%, compared to TEOM-FDMS measurements Factors Controlling the Levels of SVM in Aerosols [38] To better characterize the relationship between SVM volatilization in heated TEOMs and RH reported previously, we have reported in Figure 5, PM 2.5 losses defined as: PM 2:5 loss ð30 CÞ¼PM 2:5 ðteom 30 CÞ PM 2:5 ðteom FDMSÞ PM 2:5 loss ð50 CÞ¼PM 2:5 ðteom 50 CÞ PM 2:5 ðteom FDMSÞ [39] We have reported in this figure the two periods of high RH (H1, H2) and the period of low RH (D). As a ð4þ ð5þ general statement, we can observe that the most important PM discrepancies do coincide roughly with H1 and H2 periods (RH > 60%), which is in agreement with our previous findings (Table 1). However, a detailed analysis reveals that some periods of RH > 60% show no significant discrepancies (11-12/08), whereas some periods of RH < 60% show significant discrepancies (24&26/08). These periods have been reported in Figure 5 (T1 & T2) and do correspond to transition periods between high and low RH. They also correspond to a gradual change in wind speed and air mass origin. [40] The liquid water content (LWC) could be proposed as an alternate parameter to better delineate the periods with/without SVM since RH values of the order of 60% generally correspond to a significant change in the physical aerosol state (liquid/solid). This change is partly driven by (NH 4 )NO 3 which has a relative humidity deliquescence point of the order of 62% [Lightstone et al., 2000]. Recalling that RH could not explain entirely PM losses, in particular for the RH transition periods of 11-12/08 and 24&26/08, if we assume that LWC in aerosols is playing a major role in controlling the partitioning of SVM, then it should better explain the PM loss pattern during the abrupt RH transitions periods (T1 and T2). In other words, high LWC in aerosols should be expected for the period (11-12/08); conversely, low LWC in aerosols should be expected for the period (24&26/08). These assumptions will be addressed in the next sections from semi-quantitative estimates of LWC in aerosols measured in the field, as well as from measurements of semi-volatile nitrate aerosols in PM 2.5 obtained from the SJAC-IC instrument Liquid Water Content [LWC] in Aerosols and Its Influence on SVM Levels in PM LWC Derived From GRIMM Measurements [41] An estimate of LWC in PM 2.5 can be obtained from the comparison of integrated dried (RH < 20%) and ambient aerosol volume obtained from our two GRIMM counters. Assuming that error due to volume additivity is negligible [Dick et al., 2001], the difference between our two inte- 8of14

9 Figure 5. Influence of RH on (1) the PM loss [TEOM (50 C) - TEOM (30 C)], and (2) the PM loss [TEOM (50 C) - TEOM-FDMS]. grated volume measurements (in the size range 0.3 to 2.5 mm) is roughly proportional to the mass of adsorbed water and will be noted later as LWC GRIMM. Although such calculations lead to substantial approximations (see Section 2.6) and does not cover the whole aerosol size range, it fulfills our requirements to determine in a semi-quantitative way the LWC in the particulate phase. It remains interesting to note that a similar protocol (based on number size measurements performed at ambient/dry RH) has been successfully used in a quantitative way to calculate the LWC of ambient particles [Khlystov et al., 2005]. [42] Figure 6 shows LWC GRIMM and [SVM] which (SVM) is defined as the opposite of PM 2.5 loss (50 C) (equation (5)) and which is used here and later as a surrogate for SVM in aerosols. For comparison purposes, (H1, T1, D, H2, T2) periods are reported in this figure. It can be noticed that LWC GRIMM rarely shows values close to zero, suggesting that a small amount of water still does exist in the particulate phase even for RH below 40% (averaged concentration of the order of 5 mg/m 3 for the period of low RH lying in the middle of the campaign). This finding is consistent with results reported by Khlystov et al. [2005] who noticed that, during summer months, ambient aerosols in Pittsburg (Pennsylvania, USA) practically always contained water even when RH was as low as 30%. [43] As a consequence, distinction between wet and dry particles might not be straightforward in this study. Alternatively, an arbitrary threshold can be set in the measurements in order to distinguish more-hydrated from less-hydrated particles. For the D period, LWC GRIMM is remaining almost systematically below 10 mg/m 3 whereas it is systematically above 20 mg/m 3 for the periods of high RH. Then, these two values can be used to delineate less to more-hydrated particles. The first period corresponds to a sharp drop which occurred on 11/08 (from values up to 20 mg/m 3 to values down to 5 mg/m 3 ). This drop coincides exactly with the beginning of the transition period T1 which is characterized by a similar drop in the concentration of SVM in aerosols. On the other hand, this drop in LWC cannot be explained by a similar change in RH which ranged between 60 and 70% during the period T1. The second time LWC GRIMM crossed the mg/m 3 threshold is observed later in the campaign (24/08), with a regular increase during this day from values below 10 mg/m 3 on 24/08 midnight to values up to 40 mg/m 3 on 25/08 midnight and this increase in LWC coincides exactly with the beginning of the transition T2 period which is characterized by a similar increase in the SVM concentration in aerosols. Here again, this increase in LWC cannot be explained by a similar change in RH which ranged between 43 and 58% during the T2 period. [44] All these results point out the importance of LWC to delineate the periods which correspond to important SVM levels. They do support the proposed mechanism of the existence of SVM in highly hydrated particles. Further evidence on the key role of aerosol water content in delineating the periods with/without SVM levels is presented in the next section regarding the optical properties of aerosols. 9of14

10 Figure 6. Temporal variations of LWC (derived from GRIMM measurements), water uptake influence on the light scattering coefficient (derived from nephelometer measurements), and SVM (derived from TEOM-FDMS and TEOM (50 C) measurements). The blue rectangles represent the periods of high RH (H1 & H2); the dashed rectangles represent the transition periods T1&T LWC Derived From Light Scattering Coefficient Measurements [45] A similar approach to estimate LWC has been performed from the two nephelometer datasets, one working at ambient RH, the second working at RH < 20%. The highest s sp values do correspond to the periods of high PM 2.5 (data not shown here) and exhibit, at that time, ambient values above 500 Mm -1 ; being responsible for a drastic reduction of ground visibility (below 2 km). The difference (Ds sp ) between these two nephelometer measurements is potentially very important in this study since it will take into account the light scattering coefficient due to water uptake onto particles. In other words, (Ds sp ) could be used here as an indicator for the levels of liquid water in the aerosol phase and thus could help us to validate our previous findings on SVM. However, (Ds sp ) is not only related to the water content in the particulate phase and a careful examination on the factors controlling (Ds sp ) is then firstly required. A simple model assuming external mixing assumptions with constant dry mass scattering efficiencies and constant aerosol types [Malm et al., 2000] can be used to reconstruct the light scattering coefficient, which can be expressed as: s sp ¼ Sa X ½XŠ ð6þ where a X is the specific mass scattering or absorption coefficient (or mass efficiency) and [X] is the mass concentration of the individual species. The water uptake can be taken into account by multiplying the concentration of the hygroscopic species by a humidity-dependent scattering enhancement factor, f(rh). In a first approximation, it can be assumed that the ionic species are the only 10 of 14

11 Figure 7. Temporal variations of LWC (derived from GRIMM measurement), water uptake influence on the light scattering coefficient (derived from nephelometer measurements), and semi-volatile nitrate derived from SJAC-IC. The blue rectangles represent the periods of high RH (H1 & H2); the dashed rectangles represent the transition periods T1&T2. species that are sensitive to RH changes, and thus it can be assumed that f(rh) = 1 for BC and POM. This hypothesis has been tested and validated by Malm et al. [2003, 2005a]. Following the hypothesis used by these authors, (Ds sp ) can be expressed as: Ds sp ¼ aðfðrhþ 1Þð½ðNH 4 Þ 2 SO 4 Šþ½ðNH 4 ÞNO 3 Š where a stands for the dry specific scattering coefficient of (NH 4 ) 2 SO 4 (supposed to be the same as the one of (NH 4 )NO 3 ). Note that, under high RH, the size distribution of the ionic species is likely to change and thus their dry specific scattering coefficient (a) too. On the other hand, this change is not as important as the one induced by f(rh) and assumed here to be constant. The equation (7) shows that any variations in (Ds sp ) will then have to be carefully scrutinized as it can originate either by a change in RH or by a change in the concentration of sulfate or nitrate aerosols. [46] Figure 6 reports (Ds sp ) together with [SVM] and LWC GRIMM (defined in the previous section) and confirms the general good agreement found between the periods of ð7þ high levels of SVM and the periods impacted by high levels of water in the aerosol phase. Interestingly, the drop in (Ds sp ) observed on 11/08 (from 200 to 50 Mm 1 )is almost exclusively due to a decrease in atmospheric concentration of sulfate aerosols (results not shown here). Such decrease in sulfate concentrations will directly decrease the levels of LWC, as it is shown in Figure 6 with LWC GRIMM measurements Semi-Volatile Nitrate Aerosols in PM 2.5 and Contribution to SVM Levels [47] Measurements of nitrate performed by the SJAC-IC instrument are particularly relevant in this study since they entirely relate on the inorganic fraction of SVM in aerosols (e.g. (NH 4 )NO 3 ). Figure 7 shows the temporal variations of [NO 3 ] together with LWC GRIMM and Ds sp. A good agreement is found in the three datasets especially during the periods with high levels of LWC GRIMM. A closer look on high temporal resolution variations of [NO 3 ], LWC GRIMM and [SVM] still exhibits good agreement as reported in Figures 8a and 8b, for selected days at the beginning and the 11 of 14

12 Figure 8. (a) Co-variations of water content (LWC GRIMM ) and semi-volatile nitrate during the first period of high RH (H1), (b) Co-variations of water content (LWC GRIMM ), SVM and semi-volatile nitrate during the second period of high RH (H2). 12 of 14

13 end of the campaign, respectively. These results are somewhat expected considering that LWC is closely related to the concentrations of the major ionic species in aerosols (NO 3 and SO 2 4 ). [48] Interestingly, very similar findings have been reported by Bergin et al. [2001] who have noticed that their - filter-based highest concentration of NO 3 in Beijing coincided with periods of very high RH (rain/fog events). Based on complementary light scattering and TEOM PM 10 measurements, these authors reached the conclusions that during these periods of high RH, 1) significant TEOM artifact were observed suggesting significant amount of SVM, 2) aerosol mass production were particularly high; condensation of 2 ammonium nitrate as well as oxidation of SO 2 into SO 4 being favored on fog/cloud droplets. [49] A more quantitative comparison can be drawn between SVM and its inorganic fraction, ((NH 4 )NO 3 ), for hourly-averaged positive data and for the whole duration of the campaign. The good correlation coefficient (r 2 = 0.80; N = 243), found between these two dataset, suggests very similar behaviors; both components existing mainly on highly hydrated particles. Another striking result arises from the slope of 0.52 calculated from this comparison between SVM and (NH 4 )NO 3. A strong caution should be given when interpreting these results which might suggest, from a brief look, that 1) half of SVM is made of SVOC, 2) this SVOC behaves as (NH 4 )NO 3 and thus is captured on the particulate phase for periods of high RH only. Alternatively, it could be also proposed that TEOM-FDMS measurements (from which SVM data are calculated) are affected by significant particle bound water that TEOM-FDMS partly fails to remove during periods of high RH. Note that this hypothesis was already reported for heated TEOMs during the dry period D. This could explain why we have a systematic good agreement between SVM and (NH 4 )NO 3. Considering the very good agreement obtained between TEOM-FDMS and GRIMM measurements for the periods of high RH, it would also suggest that GRIMM measurements (performed at RH < 20%) are also affected by this influence of strong particle bound water associated with the inorganic salts. [50] As a conclusion, there is a strong evidence supporting that TEOM artifacts and (NH 4 )NO 3 are closely related in a quantitative way in Beijing fine aerosols during summertime, both becoming significant when particles are highly hydrated. On the other hand, it cannot be firmly concluded that SVM is entirely related to (NH 4 )NO 3 or that SVOC is another significant component of SVM contributing as much as half of SVM particulate mass. Concurrent measurements of SVM, SVOC and nitrate in fine aerosols are clearly needed here to arrive at more definitive conclusions. 4. Conclusions [51] A detailed comparison study of various PM 2.5 measurements has been performed in Beijing during summertime and has lead to contrasted results depending on wet/dry periods. Results of this comparison can be summarized below as follows: [52] (1) A very good agreement was found between all the TEOM measurements during the periods of RH below 60%, with bias of the order of 2 4 mg/m 3. Periods of RH > 60% were characterized by significant loss of SVM in aerosols for the TEOMs heated at 30 C and 50 C, with averaged bias of 10 and 20% of the total PM 2.5, respectively, by comparison with TEOM-FDMS measurements. [53] (2) Gravimetric measurements from SFUs have shown unsatisfactory results with systematic underestimations of the order 40-50% by comparison with TEOM- FDMS measurements. The reason of this bias cannot be solely explain by sampling artifacts and is not well understood yet. [54] (3) GRIMM measurements have shown to reproduce very well all the TEOM-FDMS variations (wet and dry periods) suggesting that optical measurements could be used to derive PM 2.5 and could also account for SVM in aerosols. On the other hand, the filter-based mass calibration applied to convert the GRIMM data into PM 2.5 measurements showed an important bias of 21 to 41 mg/m 3 for low and high RH periods, respectively. These biases point out the limitations of the field mass calibration provided by the GRIMM. It remains interesting to note that, if properly calibrated, PM 2.5 GRIMM measurements remain particular useful, versus TEOM FDMS measurements, for real-time mass closure studies since they provide 1-min resolution data which cannot be obtained by TEOM FDMS measurements, since TEOM FDMS data are obtained every 6 min and normally expressed as a 1-h moving average. [55] In order to present a more complete picture of factors controlling the periods with/without semi-volatile species in PM 2.5, semi-quantitative estimates of liquid water content (LWC) were also performed from measurements performed in the field from GRIMM and nephelometers running at ambient/dry RH. One of the major results of this study relies on the importance of the aerosol LWC as a factor controlling the periods with/without PM loss in heated TEOM(50 C). This result suggests that, for humid conditions, highly hydrated particles are likely to promote aerosol mass production through a significant change in the gas-particle partitioning of semi-volatile species through absorption processes leading to partial/ total dissolution of the species in the aqueous phase. [56] Levels of SVM in PM 2.5 were calculated here as the difference between TEOM FDMS (used here as a PM 2.5 reference) and TEOM(50 C) measurements, and were compared with artifact-free measurements of semi-volatile nitrate performed in the field (SJAC-IC instrument). The very good correlation between the two dataset suggests close behavior of these two semi-volatile components; with high concentrations concomitant with high levels of LWC in aerosols. Another striking result arises from the comparison between this two datasets which suggest that half of SVM only is related to ammonium nitrate. The composition of the remaining half is still not clearly understood yet and could originate either from SVOC or from strong particle bound water associated with nitrate aerosols. Further studies (including SVOC measurements) are clearly needed for conclusive assessments on the composition of SVM in aerosols as it is recorded between TEOM(50 C) and TEOM-FDMS. [57] Acknowledgments. The authors want to thank BMEMC for hosting the experiment and for efficient assistance during the campaign. B. Guinot, O. Favez, E. Larmanou and K. Oikonomou are acknowledged 13 of 14