Insights into factors affecting nitrate in PM 2.5 in a polluted high NO x environment through hourly observations and size distribution measurements

Transcription

1 PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Key Points: Hourly measurements of PM2.5 nitrate were reported for a high NOx location Less acidic particles and less sea-salt particles favored PM2.5 nitrate N2O5 hydrolysis pathway contributes significantly to the daytime PM episode Supporting Information: Readme Table S1, Figures S1 S5, and Appendix S1 Correspondence to: J. Z. Yu, jian.yu@ust.hk Citation: Xue, J., Z. Yuan, A. K. H. Lau, and J. Z. Yu (2014), Insights into factors affecting nitrate in PM 2.5 in a polluted high NO x environment through hourly observations and size distribution measurements, J. Geophys. Res. Atmos., 119, , doi: / 2013JD Received 29 OCT 2013 Accepted 16 MAR 2014 Accepted article online 19 MAR 2014 Published online 17 APR 2014 Insights into factors affecting nitrate in PM 2.5 in a polluted high NO x environment through hourly observations and size distribution measurements Jian Xue 1, Zibing Yuan 1,2, Alexis K. H. Lau 1,2, and Jian Zhen Yu 1,2,3 1 Division of Environment, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, 2 Atmospheric Research Center, HKUST Fok Ying Tung Graduate School, Guangzhou, China, 3 Department of Chemistry, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong Abstract Nitrate, a major PM 2.5 component in polluted environments, could be greatly elevated during pollution episodes. In this study, nitrate and other inorganic ions on PM 2.5 were measured half hourly at a residential location in Hong Kong in December Hourly nitrate concentrations in PM 2.5 varied from 0.8 to 40.5 μgm 3. In an episode during which hourly visibility was down to 3.7 ± 1.0 km and NO 2 was 80.7 ± 14.4 ppb, PM 2.5 NO 3 reached 27.8 ± 8.0 μgm 3, ~6 times the level during the normal hours. Nitrate was fully balanced by NH 4 +, indicating abundant presence of NH 3. Size-segregated measurements showed 84% of nitrate was in the fine mode during the episode and also suggested that less acidic fine particles and less abundant sea-salt particles were the contributing factors to the dominant presence in the fine mode. An observation-based model for secondary inorganic aerosols was applied to investigate the relative importance of homogeneous and heterogeneous reactions to production of NO 3 potential (sum of HNO 3 (g) and aerosol nitrate). The modeling analysis shows that both formation pathways were significantly more active during the episode. Gas phase production of HNO 3 through reaction of NO 2 +OH dominated during the initial rapid buildup of nitrate around noon time, but the heterogeneous N 2 O 5 hydrolysis pathway made a sizable contribution in the subsequent few hours due to sustained high-no 2 concentrations combined with reduced photolysis loss of N 2 O 5. This case study illustrates the important role of NH 3 and NO 2 in elevating PM 2.5 in a high-no x environment through the formation of nitrate. 1. Introduction Hong Kong (HK) is located on the southeastern coast of China, adjoining the rapidly developing Pearl River Delta (PRD) region. Elevated PM 2.5 (particulate matter with aerodynamic diameter smaller than 2.5 μm) level is a major air quality concern in HK and the PRD. Two 12 month studies show the annual average PM 2.5 concentrations in HK range from 23.7 at a rural site to 58.0 μgm 3 at a roadside location in 2000/2001 and from 28.4 (rural) to 53.0 μgm 3 (roadside) in 2004/2005. It is notable that the PM 2.5 levels at the rural location, which is not close to any major emissions, are more than double the annual air quality guideline of World Health Organization (WHO) (10 μgm 3 )[Louie et al., 2005a, 2005b; So et al., 2007]. Inorganic soluble aerosols (ISA), dominated by SO 2 4,NO 3, and NH + 4, are major constituents of PM 2.5 in HK and the PRD. Understanding their sources and formation mechanisms is important in evaluating various particulate matter (PM)-related issues such as potential health effects, visibility degradation, and climate change. Field measurements have consistently showed that SO 2 4 is the major ISA in the PRD [Louie et al., 2005a; Hagler et al., 2006; So et al., 2007; Xue et al., 2011]. Significant abundance of NO 3 was increasingly observed in recent studies due to the increasing contribution of vehicular emissions to urban aerosols [e.g., Zou et al., 2007]. He et al. [2009] reported NO 3 in PM 10 increased by a factor of 6.5 on hazy days with respect to normal days in Guangzhou. These observations demonstrate the need for a good understanding of the sources and factors influencing NO 3 abundance, especially during pollution episodes. Previously, most studies on ISA in HK and the PRD relied on filter-based measurements which typically need 12 h or longer to collect sufficient material for off-line analysis. The filter-based approach has two shortcomings. First, it is unable to capture temporal variations of aerosol composition on time scales shorter than the sampling duration. This information is critical in understanding the formation of secondary inorganic species, which are strongly influenced by in situ gas precursor concentrations and meteorological XUE ET AL American Geophysical Union. All Rights Reserved. 4888

2 conditions, e.g., solar radiation, temperature, and relative humidity (RH). Second, accurate determination of semivolatile species on filters, e.g., NO 3 and NH + 4, remains to be a challenging task. Filter-based determination for these species is often subjected to various sampling artifacts due to gas-particle interactions and evaporation of semivolatile species [Schaap et al., 2004; Pathak et al., 2004]. In this study, online measurement of major ISA in PM 2.5 with half-hourly resolution was conducted to overcome the above mentioned limitations. The objective of this work is to describe high-resolution temporal variations of nitrate and other ISA constituents and to improve our understanding of processes leading to high PM episodes. The size distributions of ISA in the range of μm were also characterized. Special attention is paid to nitrate, since apart from being the most significant PM 2.5 component during the pollution episode, it is also a more varied and less understood component. 2. Experimental Section 2.1. Meteorological Conditions PM 2.5 ionic composition was measured at Tung Chung (TC), a residential town in southwest HK, during December Figure S1a in the supporting information shows the location of HK and the TC sampling site. At TC, major pollution sources include vehicular emissions from the upwind urban areas to the east and the northeast, emissions from marine vessels in the water channel to the north, and the power plants at Tap Shek Kok to the north and at Lamma Island to the east. Weather charts, wind profiles and back trajectory analysis indicate that HK was under three types of synoptic conditions during the observation period. During December and on 26 December, a strong high-pressure anticyclonic system hovered over the continent in the north (Figure S1b). Air masses arriving in HK originated from southeastern China. During December, the continental high-pressure system weakened and a high-pressure system developed over the western Pacific Ocean (Figure S1c). Air mass back trajectories show that air passed over East China Sea before arriving in HK. On 25 December, a land-sea breeze circulation developed in the coastal areas of HK, during which hourly visibility dropped down to 3.7 ± 1.0 km. The land-sea breeze circulation is known to trap pollutants and thereby elevate pollution levels in the western part of HK [Fung et al., 2005] Sampling and Analysis The sampling site was on the roof top of a district hospital, about 25 m aboveground. A PILS-IC system (particle-into-liquid system coupled with ion chromatography) [Weber et al., 2001; Orsini et al., 2003] was deployed to obtain PM 2.5 ionic chemical composition at a time resolution of 30 min. Detailed description of the PILS-IC system used in this work is given in Xue et al. [2011]. Briefly, air is drawn through a cyclone (with a cut size of 2.5 μm) and two denuders before entering the particle-into-liquid system (PILS) at a flow rate of 16.7 L min 1. In PILS, particles absorb water vapor, grow to sizes of 1 5 μm in diameter and are collected by an inertial impactor. Water-soluble components on the particles are then dissolved in water, and the extracts are subsequently delivered to the two online ion chromatography (IC) systems for determination of anions and cations at the same time. Validation of measurements by this PILS-IC was conducted by comparing with denuder/filter off-line measurement, and the details were in our previous paper [Xue et al., 2011]. The slopes of the linear regression lines of PILS-IC data versus filter data deviate less than 10% from unity for SO 2 4,Na +, and K + and less than 20% for NO 3,NH + 4, and Cl. Size-segregated aerosol samples were collected using a 10-stage Micro-Orifice Uniform Deposition Impactors (MOUDI ) sampler (MSP Corp., Shoreview, MN, USA) operating at a flow rate of 30 L min 1. The 50% cut sizes for the 10 stages are 18, 10, 5.6, 3.2, 1.8, 1.0, 0.56, 0.32, 0.18, 0.1, and μm. The sampling duration of individual samples was h. Nine sets of samples were collected, including five sets during the daytime ( LST (Local Standard Time)) and four sets during the nighttime ( LST). The collection substrates were 47 mm quartz fiber filters for seven sets of samples and 47 mm nylon (P5PJ047, PALL Corporation, USA) for two sets. The filter samples were stored at 18 C before analysis. Half of each filter was extracted with 7.0 ml of ultrapure water in an ultrasonic bath for 30 min. Then the extracts were filtered with a 0.45 μm Teflon filter (Millipore, Billerica, MA, USA) before off-line analysis using IC (DX500, Dionex, Sunnyvale, CA, USA). The anions (i.e., Cl,NO 3,andSO 2 4 ) were separated on an AS-11 column with a gradient elution solution of NaOH. The cations (i.e., Na +,NH + 4,K +,Mg 2+, and Ca 2+ ) were separated on a CS-12 column with an isocratic elution solution of methanesulfonic acid. The details of the off-line IC XUE ET AL American Geophysical Union. All Rights Reserved. 4889

3 Table 1. Statistic Summary of Concentrations (μgm 3 )ofpm 10,PM 2.5, and Inorganic Soluble Species on PM 2.5 During the Observation Period 2 PM 10 PM 2.5 SO 4 NO 3 Cl + NO 2 NH 4 Na + K + H +a Mean Standard deviation Median th th <DL b <DL 3.3 <DL a In neq m 3, calculated as the difference between the anion equivalence and cation equivalence measured on PM2.5 [Xue et al., 2011]. b Below detect limit. measurements were given in Yang et al. [2003]. Additionally, hourly data including PM 2.5 mass, NO, NO 2, SO 2,CO,O 3, and visibility at the sampling site are provided by the Hong Kong Environmental Protection Department (HKEPD). PM 2.5 mass is measured using Tapered Element Oscillating Microbalance [Grover et al., 2005], operating at 35 C and fitted with a dryer upstream. Visibility is monitored with a Belford Visibility Sensor (model 6000). 3. Results and Discussion 3.1. Sampling Artifacts of MOUDI MOUDI is widely used to study size characteristics of aerosol chemical composition. A small number of studies have documented its sampling artifacts of semivolatile species (e.g., NO 3,Cl,andNH + 4 )[Yao et al., 2001; Malm et al., 2005]. In this study, sampling artifacts of ISA measurements by MOUDI are evaluated by comparison with PM 2.5 measurements by PILS. Because a cut size of 2.5 μm is not available in the MOUDI, the average of PM 1.8 (particles collected on and below the 1.8 μm cut stage) and PM 3.2 (particles collected on and below 3.2 μm cut stage) measurements was used to compare with the PM 2.5 data by PILS during the same period. The two sets of data are highly correlated, with r 2 = 0.99, 0.79, 0.95, and 0.96 for NO 3,Cl,NH + 4, and SO 2 4, respectively (Figure S2). The slope values for NH + 4 and SO 2 4 comparisons are close to unity. For NO 3 and Cl, the slope values of the linear regression lines deviate 32% and 26% from unity, and PILS measures higher concentrations. This indicates evaporation loss of nitrate and chloride on MOUDI stages. Collection efficiency of MOUDI for species A is calculated as follows: [A] MOUDI /[A] PILS 100% + ([SO 2 4 ] PILS [SO 2 4 ] MOUDI )/[SO 2 4 ] PILS 100%, where [A] PILS and [A] MOUDI are the concentration of A by PILS and MOUDI, respectively. The term containing [SO 2 4 ] is included to correct for possible small systematic errors associated with the two sets of measurements. The collection efficiencies of NO 3,Cl,andNH + 4 are 68 ± 16, 77 ± 30, and 110 ± 18%, respectively, which suggests that MOUDI is capable of capturing major features of ISA species, with moderate underestimation of NO 3 and Cl. We note that the correlations of Na + (r 2 : 0.32) and K + (r 2 : 0.26) between the two methods are poor. This is probably due to their mass concentrations on some stages near or lower than the detection limits (0.52 and 0.40 μg/filter for Na + and K +, respectively) Concentration of ISA Species Table 1 shows the statistical summary of PM 2.5 mass concentrations and ISA composition during the sampling period. The concentration of PM 2.5 was 43.2 ± 18.2 μgm 3,significantly higher than the WHO 24 h air quality guideline (25 μgm 3 ). SO is the most abundant ISA species (27 ± 4% of PM 2.5 mass), followed by NH 4 (10 ± 2%) and NO 3 (9 ± 5%). The sum of the three ions accounts for 47 ± 6% of PM 2.5,indicatingthe importance of secondary formation processes to PM 2.5 loading. The average SO 2 4 level of 11.5 μgm 3 is close to past winter observations in HK [Louie et al., 2005a; Ho et al., 2003; Pathak et al., 2004], but slightly lower than those measured in other cities in PRD ( μgm 3 in Guangzhou, 13.0 μgm 3 in Shenzhen, and 17.1 μgm 3 in Zhuhai) [Zou et al., 2007]. The average NO 3 concentration of 4.5 μgm 3 is higher than the past filter-based measurements in winter in HK ( μgm 3 in year 2000/2001 and 2004/2005) [Louie et al., 2005b; Ho et al., 2003; Pathak et al., 2004]. The NO 3 concentration is comparable to winter observations in industry areas of Guangzhou (4.7 μgm 3 ) and urban areas in Shenzhen (4.4 μgm 3 ) but much lower than XUE ET AL American Geophysical Union. All Rights Reserved. 4890

4 Figure 1. Relationships of SO 4 2,NO3,andNH4 + during the observation period. The circled data points were measurements during the episodic hours ( LST on 25 December). those in urban and suburban areas in Guangzhou ( μgm 3 ) and in Zhuhai (8.6 μgm 3 )[Zou et al., 2007]. We note that the previous filter-based measurements systematically underestimate NO 3 concentrations, with percentage loss ranging from 38 to 90% [Pathak et al., 2004]. Thus, comparison shown here only provides a rough comparison of NO 3 level in this region. For a better understanding of the regional and seasonal pattern of NO 3, artifact-free measurements are needed. NH + 4 is the major species to neutralize SO 2 4 and NO 3 in PM 2.5. Figure 1 shows comparisons of the measured equivalent concentrations of [NH + 4 ], 2 [SO 4 2 ] and [NO 3 ]+2[SO 4 2 ]. It is clear that [NH 4 + ] does not entirely balance the sum of 2[SO 4 2 ] and [NO 3 ], suggesting acidic nature of the aerosols Temporal Variation of ISA Species Time series of hourly concentrations of PM 2.5 and its inorganic soluble composition are plotted in Figure 2. The PM 2.5 concentration was generally below 45 μgm 3 before 25 December while increased rapidly in the morning and peaked at 1600 LST on 25 December, with hourly concentration reaching 148 μgm 3. Visibility deteriorated during two periods, LST on 24 December (visibility: 4.5 ± 0.4 km) and on 25 December (visibility: 3.7 ± 1.0 km). In the first period, normal PM 2.5 loading (42.1 ± 6.4 μgm 3 ) and high RH (88 ± 1.0%) were recorded, indicating that visibility degradation was caused by mist. In the second period, visibility degradation was accompanied by high levels of PM 2.5 loadings (107 ± 33 μgm 3 ) and RH in the range of 67 75%. We therefore denote the second period as the pollution episode. Table 2 compares aerosol chemical composition and meteorological parameters during the pollution episode and the same hours ( ) on the other sampling days (termed as normal hours). During the pollution episode, ISA explained 70% of the PM 2.5 mass and NO 3 became the most abundant ISA species (27.8 μgm 3 ), slightly exceeding SO 2 4 (27.5 μgm 3 ). K +,NO 2, and sea-salt aerosols (i.e., Na + and Cl ) accounted for small fractions of PM 2.5 mass (4%). Samples during the pollution episode were highlighted by dashed circles in Figure 1. The equivalent concentration of [NH + 4 ] far exceeded 2 [SO 2 4 ] but lower than the sum of 2 [SO 2 4 ]and[no 3 ]. This shows that NH 3 is an important contributor to elevated PM 2.5 in this episode. Figure 2. Time series of concentrations of PM 2.5 and major ionic species in PM 2.5 and the visibility during the sampling period. PM 2.5 during the episodic hours (12:00 19:00) was higher by 62.8 μgm 3 than that during the same hours on the normal days, 80% of which was attributable to the three secondary ISA species (i.e., SO 4 2,NO 3,and NH 4 + ). NO 3 concentration increased by a factor of 5.2, while SO 4 2 concentration only increased by a factor of 1.4 during the episode. The notable increase of NO 3 is therefore worth special attention. XUE ET AL American Geophysical Union. All Rights Reserved. 4891

5 Table 2. Comparison of PM 2.5, Inorganic Soluble Species, Criteria Gaseous Pollutants, Visibility, and Meteorological Conditions During the Episodic Hours and the Normal Hours (μgm 3 2 ) PM 2.5 SO 4 NO 3 Cl + NO 2 NH 4 Na + K + H + (neq m 3 ) Episode hours ± ± ± ± ± ± ± ± ± 75 Normal hours 44.2 ± ± ± ± 0.5 a 4.5 ± ± ± ± 38 ppb NO (ppb) NO 2 (ppb) SO 2 (ppb) O 3 (ppb) CO (ppm) Visibility (km) T (K) RH Wind speed (m/s) Episode hours 26.7 ± ± ± ± ± ± ± ± ± 0.8 Normal hours 18.3 ± ± ± ± ± ± ± ± ± 1.5 a Below detect limit. b Calculated as difference between the anion equivalence and cation equivalence measured on PM2.5 [Xue et al., 2011] Identification of Pollutant Source Areas Through Circular Pollution Wind Maps Circular pollution wind map method was applied to examine relationships between surface winds and pollutant loadings, thereby providing information on pollution sources (Figure 3). Detailed description of circular pollution wind map was introduced in Lau et al. [2005]. Briefly, wind speeds are indicated by the dotted concentric circles at 2, 5, and 8 m s 1 (from innermost to outermost) and wind direction is indicated by angles. Occurrence frequency of winds at a given speed and direction are described by four colored contour lines, representing frequency of top 25% (light blue), 50% (red), 75% (green), and 95% (blue) of wind speed-direction pair, respectively. Surface wind used in this analysis was measured at the Hong Kong International Airport, about 3 km northwest of the station, to avoid local topography influence. Since the pollution episode on 25 December was associated with special meteorological conditions, data collected on this day were not included in this analysis SO 2, NO, and NO 2 Previous studies using long-term observational data in HK had revealed three dominant sources of SO 2, that is, regional transport from the PRD, combustion of residual fuel oil from local marine sources, and emissions from the airport and the local power plants [Yu et al., 2004; Lau et al., 2005]. High SO 2 levels were observed when the wind had a northerly component, suggesting regional transport from the north was likely the major contributor of elevated SO 2 in our observation period. As indicated by the regions in red in the pollution wind maps, high levels of NO and NO 2 were associated with moderate easterly winds. This suggested that local transport from the urban areas of HK, which are situated to the east of the station, was an important contributor of NO and NO PM 2.5 and ISA High levels of SO 4 2,NH 4 +, and PM 2.5 were associated with moderate to strong northerly and easterly winds. Such a pattern indicates both local sources and long-range transport contributed to high concentrations of SO 4 2,NH 4 +, and PM 2.5. Higher concentrations of NO 3 were associated with northerly/northeasterly wind, which was a result of the lower temperature in wintertime when northeasterly wind prevailed. A thermodynamic equilibrium exists between HNO 3 and NH 3 in the gas phase and NO 3 /HNO 3 in the aerosol phase ((R1) and (R2)). The equilibrium shifts to the particle phase when the temperature drops. H þ þ NO 3 ðaq; sþ HNO 3ðgÞ (R1) NH 4 NO 3 ðaq; sþ NH 3 ðgþþhno 3 ðgþ (R2) Higher concentration of K +, a tracer for biomass burning emissions, was associated with strong northeasterly winds, reflecting strong biomass burning emissions to the northeast of HK. This was confirmed by the map of hot spots (Figure S1e) derived from the low spatial resolution infrared satellite data [Wright et al., 2004]. As indicated by the regions in red and yellow on the circular plots, higher levels of Cl were associated with two wind components. One was strong wind from the east and accompanied with high loading XUE ET AL American Geophysical Union. All Rights Reserved. 4892

6 Journal of Geophysical Research: Atmospheres 3 Figure 3. Circular Pollution Wind Maps: Concentrations of the aerosol species in μg m and the gas species in ppb are color coded. Concentrations are averaged for different wind speeds (given by the radius with 1 m/s resolution) and wind directions (given by angle with 10 resolution). The black concentric circles correspond to winds of 2, 5, and 8 m/s from the inner to the outer circles, respectively. The contours in the last plot correspond to the most frequent 95%, 75%, 50%, and 25% of the measured wind speed and direction pairs. of Na+, characteristic of the sea-salt aerosol source. Samples associated with this wind pollution sector were collected during December, when easterly air flow originated from the oceandominated HK. The other more significant wind component was from the north/northeast in association with negligible Na+ level. Cl can be either emitted from biomass burning in the forms of KCl and NH4Cl or from coal combustion process in the form of gaseous HCl [Li et al., 2007; Alves et al., 2010; Ninomiya et al., 2004]. Since high Cl and K+ did not coincide in the same wind sectors, we therefore deduce that coal combustion emissions from power plants to the north/northeast of the station were more likely the major sources of Cl in PM2.5 at TC Size Distributions of ISA Past studies have shown that ambient ISA normally exhibits three modes, condensation mode, droplet mode, and coarse mode, in their mass size distributions [e.g., Huang et al., 2006; Seinfeld and Pandis, 2006]. In this study, an inversion method [Dong et al., 2004] was applied to resolve the MOUDI measurements of SO42, NH4+, K+, NO3, and Ca2+ into the three modes. The size distributions of Na+ and Cl could not be retrieved using this inversion method, because their mass on certain stages was below detection limits or very low. As a result, Na+ and Cl in PM18 1.8, PM , and PM0.32 were instead used to represent their coarse, droplet, and condensation mode concentrations, respectively SO42, NH4+, K+, and Ca2+ The size distributions of SO42, NH4+, K+, and Ca2+ were consistent among different sets of samples and with previous observations in this region [e.g., Zhuang et al., 1999a; Huang et al., 2006]. Figure 4 shows the average inverted log-normal distributions of SO 42, NH4+, K+, and Ca2+, together with the measured MOUDI data. A predominant droplet mode was observed for SO42, NH4+, and K+ with an average mass medium aerodynamic diameter close to 1 μm (1.05, 1.05, and 0.95 μm, respectively). The droplet mode accounted for 89%, 85%, and 72% for SO42, NH4+, and K+, respectively. SO42 in the XUE ET AL American Geophysical Union. All Rights Reserved. 4893

7 Figure 4. Average size distributions of SO 4 2,NH4 +,K +, and Ca 2+ measured by MOUDI. Error bars indicate the standard deviation of nine sets of samples. Three log-normal size modes (condensation, droplet, and coarse modes) in smooth curves are inverted from the MOUDI measurements. XUE ET AL American Geophysical Union. All Rights Reserved. 4894

8 Figure 5. Size distributions of NO 3. The center large plot is the size distribution of nitrate obtained from the daytime sample collected during the episodic day (25 December 2009). (a) Average size distribution of nitrate in samples dominated by a droplet mode (the episodic day sample is excluded). (b) Average size distribution of nitrate in samples dominated by a coarse mode. (c) Average size distribution of nitrate in samples with a bimodal distribution. Error bars represent the standard deviations of MOUDI measurements. droplet mode is formed through aqueous oxidation of SO 2 in cloud/ fog droplets followed by water evaporation [Meng and Seinfeld, 1994; Kerminen and Wexler, 1995] and partly neutralized by NH 4 + [Zhuang et al., 1999a]. K + in the droplet mode is a result of biomass burning aerosols serving as effective cloud condensation nuclei [Novakov and Corrigan, 1996; Kaufman and Fraser, 1997]. High percentages of SO 4 2,NH 4 +, and K + in the droplet mode indicate that cloud processing was important in particle aging in winter in our study region. Ca 2+ was predominant in the coarse mode, reflecting its origin in crustal CaCO 3 followed by reaction with acidic gases (e.g., HNO 3 and H 2 SO 4 ) [Huang et al., 2006] NO 3 Different from SO 4 2 and NH 4 +,size distribution of NO 3 varied among different samples. Three sets of samples were dominated by the droplet mode, two sets were dominated by the coarse mode, and the remaining four sets were bimodally distributed in the droplet mode and the coarse mode. The average distribution curves in each of the three size distribution groups are shown in Figure 5. The modal concentrations of nitrate in individual samples are listed in Table 3. Notably, during the episode hours on 25 December, 77% of NO 3 was in the droplet mode. Therefore, the enhancement of NO 3 in the droplet mode played a key role in elevating PM 2.5 during the episode. We further examined the size-segregated aerosol composition by comparing three sets of samples that represent distinct characteristics in nitrate size distributions (Figure 6). The negative sampling artifact for nitrate was moderate in these samples, as indicated by the collection efficiency of fine mode NO 3 better than 74%. Figure 6a shows the size distributions of ISA during the daytime of 25 December, NO 3,SO 2 4,andNH all exhibiting a dominant peak in the μm size bin. NH 4 concentration in fine mode (763 neq m 3 ) was more than sufficient to neutralize SO 2 4 (494 neq m 3 ). The extra NH + 4 concentration is 269 neq m 3, close to the amount needed to fully neutralize NO 3 (297 neq m 3 ). This indicates that NO 3 was mostly in the form of NH 4 NO 3 during the episode. Figure 6b shows distribution of ISA species in different size bins during the nighttime of 21 December. In this sample, though the fine mode nitrate was discernible, NO 3 in the coarse size bin of μm dominated. The extra NH + 4 concentration in the coarse mode was 13 neq m 3, far lower than NO 3 concentration in the coarse mode (56 neq m 3 ). Hence, around 77% of NO 3 in the coarse mode had to be balanced by other cations. The similar size distributions of Na + and Ca 2+ to that of NO 3 suggest their possible association with NO 3. As shown in Figure S3, the correlation between NO 3 and Ca 2+ in the coarse mode was insignificant; however, a moderate correlation between NO 3 and Na + was observed, suggesting that coarse mode NO 3 was more likely associated with Na +. Figure 6c shows distribution of ISA during the daytime of 21 December. A bimodal distribution of NO 3 was observed, with a fine mode of NO 3 peaking in the μm size bin and a coarse mode NO 3 peaking in the μm size bin. In the fine mode, the extra NH + 4 concentration of 69 neq m 3 was sufficient to balance NO 3 (53 neq m 3 ), indicating fine mode NO 3 was in the form of NH 4 NO 3. However, in the coarse mode, the NO 3 concentration (37 neq m 3 ) far exceeded the extra NH + 4 concentration of 19 neq m 3 and part of it was balanced by Na + and Ca 2+. XUE ET AL American Geophysical Union. All Rights Reserved. 4895

9 Table 3. Modal Concentrations (in neq m )ofno 3,Cl,Na, and Ca in Individual Sets of MOUDI Samples NO 3 Cl Na +d Ca 2+ No. a Time b Cond c Droplet Coarse Cond c Droplet Coarse Cond c Droplet Coarse Cond c Droplet Coarse R +/ e Temperature(K) RH (%) Cloud Cover f Samples Having a Dominant Droplet Mode of NO th, N th,D <DL 6 12 <DL <DL th,D <DL <DL 9 19 <DL <DL Samples With NO 3 Bimodally Distributed in Fine and Coarse Modes 3 18th,N <DL 3 <DL <DL <DL 3 <DL <DL th,D <DL 4 12 <DL <DL <DL st,D <DL <DL th,N <DL <DL <DL <DL <DL <DL 12 <DL <DL <DL Samples Having a Dominant Coarse Mode of NO st,N <DL g <DL 9 47 <DL 5 63 <DL <DL rd,D <DL 8 61 <DL <DL <DL a The samples are numbered in chronological order. b N, nighttime and D, daytime. c Cond stands for condensation mode. d Data in the three size modes were approximated to be PM 0.32, PM , and PM e R+/ is [NH 4 + ]/(2[SO4 2 ] + [NO3 ]). f Average observations at Hong Kong International Airport. g Below detect limit. XUE ET AL American Geophysical Union. All Rights Reserved. 4896

10 NH4+/2 SO42-/2 NO3- Na+ Ca2+ Cl- K+ Formation pathways of aerosol nitrate have been discussed in a number of studies [e.g., Seinfeld and Pandis, 2006; Zhuang et al., 1999a, 1999b; Xie et al., 2009; Pathak et al., 2009, 2011]. These studies conclude that the fine mode NO 3 is formed through two pathways: (1) homogeneous gas-phase transformation of NO 2 to HNO 3 (g) (R3), followed by reaction with ammonia to form NH 4 NO 3 (reverse reaction of (R2)), and (2) heterogeneous hydrolysis of N 2 O 5 on the preexisting particles (R4). NO 2 þ OH M HNO 3 ðgþ (R3) N 2 O 5 H2O;surface 2HNO 3 (R4) Figure 6. Distributions of inorganic soluble species in individual size bins during (a) daytime of 25 December when nitrate mostly resided in the droplet mode size bins, (b) nighttime of 21 December when nitrate was mostly in the coarse mode, and (c) daytime of 21 December when nitrate was distributed in both droplet and coarse modes. Equivalent concentrations of [NH 4 + ] and [SO4 2 ] are scaled down to half for better visual inspection of other species. NH 4 NO 3, a semivolatile species, exists in reversible phase equilibrium with gaseous HNO 3 and NH 3 ((R1) and (R2)). The dissociation equilibrium of NH 4 NO 3 highly depends on temperature and RH. Increase in temperature or drop in RH could release gaseous HNO 3.The subsequent reactions of gaseous HNO 3 with coarse soil and sea-salt particles ((R5) and (R6)) could shift nitrate to coarse particles and thereby change size distributions of nitrate [Xie et al., 2009]: NaClðaq; sþþhno 3 ðgþ NaNO 3 ðaq; sþþhclðgþ CaCO 3 ðþþ2hno s 3 g ð Þ CaðNO 3 Þ 2 ðþþh s 2 O þ CO 2 ðgþ (R5) (R6) Varied size distributions of NO 3 are expected as a result of the semivolatile nature of NH 4 NO 3 and the reaction of HNO 3 with alkaline soil and sea-salt coarse particles. Such a variable feature is observed in this study and also reported for elsewhere in the world in the literature. For example, at a rural location (Big Bend Region) in the U.S., NO 3 was almost exclusively in the coarse mode [Lee et al., 2004]. In Bondville, Illinois, in the U.S., the fine mode NH 4 NO 3 was the dominant contributor to particle NO 3 in winter [Lee et al., 2008]. In Sheffield, central England, size distribution characteristics of NO 3 were strongly influenced by air mass origins: when the air masses had traveled long distances over land before reaching the sampling site, NO 3 exhibited a bimodal distribution; when the air masses moved mostly over the sea and just short distances over land, only the coarse mode was observed [Xie et al., 2009]. In past studies conducted in HK, Zhuang et al. [1999a] reported that NO 3 was exclusively distributed in the coarse mode in samples collected at a suburban area in winter of 1996; Yao et al. [2003] observed a clear presence of the fine mode NO 3 peak, although the coarse mode NO 3 dominated at an urban site (Ho Man Tin) in summer of We examined chemical composition in individual size-segregated samples and the relevant ambient conditions (e.g., temperature and RH) (Table 3) in order to identify the key factors influencing the relative abundance of nitrate in fine and coarse modes. A direct link between NO 3 size characteristics and temperature or RH was absent. Instead, factors such as the acidity of fine particles and abundance of Na + in XUE ET AL American Geophysical Union. All Rights Reserved. 4897

11 the coarse mode seem to be important in determining the relative distribution of fine and coarse mode nitrate. In the two coarse nitrate-dominated samples (Sample sets 6 and 7), the fine particles had higher apparent acidity, with an average [NH + 4 ]/(2[SO 2 4 ] + [NO 3 ]) molar ratio (abbreviated as R +/ ) of 0.67 ± The lower R +/ may suggest lack of NH 3 to neutralize HNO 3, leaving more HNO 3 (g) available for reaction with sea-salt or soil particles. In these two samples, Na + in the coarse mode was relatively abundant (an average of 57 neq m 3 ), providing alkaline surface to take up gaseous HNO 3. In comparison, in two of the three fine nitrate-dominated samples (Sample sets 1, 2, and 9), the fine particles were less acidic, with an average R +/ of 0.81 ± 0.08, and the coarse mode [Na + ] was relatively low (an average of 13 neq m 3 ). Both factors favor retaining HNO 3 on the fine particles. The other sample sets (sets 3, 4, 5, and 8) had their fine particle apparent acidity in-between, with an average R +/ of 0.75 ± 0.02, which may explain their bimodal size distribution. It is noted that Sample set 5, despite the presence of a high level of Na + in the coarse mode (69 neq m 3 ), had a significant fine mode NO 3. This indicates that abundant sea-salt particles alone would not lead to a dominated coarse mode for nitrate and that the relative distribution of nitrate between fine and coarse particle is a result of NH 3 and coarse alkaline particles (soil and sea-salt particles) competing for gaseous HNO 3. A more quantitative description will require a modeling investigation that incorporates kinetics of relevant chemical reactions and gas-particle transfer Size Distributions of Cl and Na + Size distributions of Na + and Cl are closely related to those of NO 3. For samples that have an obvious coarse mode of NO 3 (Sample sets 3 8 in Table 3), Na + and Cl exhibit unimodal distributions in the coarse mode. In samples with a predominant fine mode of NO 3 (Samples sets 1, 2, and 9), enhancement of Cl in fine mode was observed. It is notable that a clear condensation mode Cl was observed in Sample sets 1 and 2 but absent in all the other samples. These two sets of samples were collected on 17 and 18 December, when strong northerly winds prevailed (Figure 3). The northerly winds were associated with high loadings of Cl but low loadings of Na +. As discussed previously, coal combustion emissions from power plants to the north/northeast of the station were likely the source of Cl. 4. Observation-Based Modeling Investigation of Major Nitrate Formation Pathways During the Haze Episode Production of NO 3 in fine mode is mainly via two pathways, i.e., homogeneous reaction (R3) and heterogeneous reaction (R4). The homogeneous reaction is believed to be the dominant contributor while the heterogeneous reaction plays a more important role during nighttime [Xie et al., 2009]. In recent studies, Pathak et al. [2009, 2011] observed an NO 3 peak in PM 2.5 (20 90 μgm 3 ) in Beijing and Shanghai, China. They suggested that heterogeneous hydrolysis of N 2 O 5 on the aerosol surface was the most likely formation pathway because the particles were characterized by high level of acidity. In this section, we estimate the relative contributions of homogeneous and heterogeneous reactions in production of NO 3 potential (the sum of HNO 3 in gas phase and NO 3 in the aerosol phase) during the episode using an Observation- Based Model for Secondary Inorganic Aerosols (OBM-SIA) Observation-Based Model The details of OBM-SIA were described in Xue et al. [2014]. Briefly, OBM-SIA is a zero-dimensional multiphase chemistry box model which uses hourly observations of atmospheric species as well as the meteorological parameters as inputs. A summary of the input data and their measurement methods is given in Table S1. The model first calculates unmeasured species (e.g., OH and HO 2 ) by integrating a set of coupled differential equations taking the following form: C A t ν A ¼ P A L A C A Ht ðþ HðÞ t FT C A C A Ht ðþ* t (1) where C A is the concentration of species A and P A and L A are chemical production and destruction rates of A, respectively. Chemical mechanism incorporated in OBM-SIA is the CB05 mechanism plus two recently discovered OH enhancement pathways [Li et al., 2008; Hofzumahaus et al., 2009]. The third term on the right XUE ET AL American Geophysical Union. All Rights Reserved. 4898

12 side represents dry deposition rate of A, where v A is the dry deposition velocity and H(t) is the mixing height at time t; and the far-right term represents the loss by dilution as the mixing height expands, where C FT A is the free tropospheric concentration of species A (assumed to be zero for all unspecified species). The time-dependent differential equations are solved using a standard Gear routine. Contributions of various pathways to the production of a target species are calculated by integrating corresponding formation rates during a given time. The productions of NO 3 potential via (R3) is calculated as follows: Figure 7. Model-predicted NO 3 potential contributed by the homogeneous reaction (red area) and heterogeneous reaction (blue area) (a) during the daytime of 25 December (an episodic day) and (b) during the daytime of 21 December (a normal day). Also shown are the observed PM 2.5 nitrate increase rates in the periods of 10:30 12:30 and 14:00 16:30 (plotted in shaded columns) and temporal variation of PM 2.5 NO 3 concentrations on the two select days. ΔNO 3 ðpotentialþ ¼ t k 0 1½NO 2 Š t ½OHŠ t dt (2) where ΔNO 3 (potential) is production of NO 3 potential via (R3) during a short time interval t, k 1 is the reaction rate constant of (R3), and [NO 2 ] t and [OH] t are the gaseous phase concentrations of NO 2 and OH radical at time t, respectively. The productions of NO 3 potential via (R4) is calculated as follows: ΔNO 3 ðpotentialþþ ¼ t 2k 0 2 ½N 2 O 5 ¼ t 2 γ N 2O Š t dt 8kT 0:5 A p ½N 2 O 5 Š t dt πm N2O 5 where k 2 is the reaction rate constant of (R4); [N 2 O 5 ] t is the gaseous phase concentrations of N 2 O 5 and γ N2O5 is the reaction probability of N 2 O 5 on the aerosol surface. A value of 0.1 was adopted for γ N2O5 as recommended by Jacob [2000]. (8RT/πM N2O5 ) 0.5 (m s 1 ) is the mean molecular speed of N 2 O 5, M N2O5 is the molecular mass, and A p is the aerosol specific surface area (m 2 m 3 ). Generally, A p can be calculated using the measured particle number size distributions (assuming spherical particles) [Yue et al., 2010]. However, since such data were not available during the sampling periods, A p is approximated by the following equation: A p ¼ 6 C PM2:5 ρ*d PM2:5 þ 6 C ð PM10 C PM2:5 Þ 10 6 (4) ρ*d PM2:5-10 (3) where C PM2.5 and C PM10 are concentrations of PM 2.5 and PM 10 in μgm 3, respectively, D PM2.5 and D PM are the effective aerodynamic diameter of PM 2.5 and PM D PM2.5 is set to be 0.1 μm, following observations at two sites in PRD [Yue et al., 2010]; D PM is set to be 3.5 μm to be consistent with the observed size distribution of Ca 2+ ;andρ is the density of particles and set to be 1 g cm 3 [Lin and Cheng, 2007]. A sensitivity test assuming two different values of ρ (1.0 and 1.5 g cm 3 ) was carried out to examine the effect on the XUE ET AL American Geophysical Union. All Rights Reserved. 4899

13 calculated production of NO 3 potential via the heterogeneous pathway (i.e., (R4)). A larger assumed ρ would lower the modeled NO 3 potential production rate via (R4). The details are given in Appendix S1. Figure 8. Comparison of time profiles of NO, NO, O 3,N 2 O 5, and N 2 O 5 photolysis rates during the daytime of 25 December (an episodic day) and 21 December (a normal day). (a) Measured NO, NO 2, and O 3 and (b) modeled N 2 O 5 concentrations and N 2 O 5 photolysis rates. Solar insolation is presented in Figure S4c in the supporting information Nitrate Production Through Different Formation Pathways Figure 7 shows the time series of the model-predicted NO 3 potential contributed by the homogeneous and heterogeneous reactions, together with the observed NO 3 concentration in PM 2.5, during daytime of 25 December (episodic day) and 21 December (an example of normal day). Both pathways are significantly more active during the episodic hours. The two pathways contribute to an average combined production rate of 4.31 μgm 3 h 1, significantly higher than that during the normal day daytime (1.29 μgm 3 h 1 ). During the episode hours, the homogeneous pathway had an average NO 3 potential production rate of 2.95 μgm 3 h 1, about 2 times that of the heterogeneous reaction (1.36 μgm 3 h 1 ). The relative importance of the two pathways strongly depends on the time of the day. The homogeneous pathway is more important during the noon time when OH radical concentrations (shown in Figure S4) are high, but its contribution is significantly lowered in the late afternoon as solar radiation decreases. On the other hand, the heterogeneous reaction dominates production of NO 3 potential in the late afternoon when O 3 and NO 2 levels are high (Figure 8a), as high O 3 and NO 2 leads to high N 2 O 5 through reactions (R7) and (R8) NO 2 þ O 3 NO 3 þ O 2 NO 3 þ NO 2 N 2 O 5 (R7) (R8) Figure 8a compares the time profiles of measured NO, NO 2, and O 3 during the daytime of the episodic day and the normal day. NO 2 was significantly higher during the episodic hours, possibly due to the holiday effect (more traffic flow was observed on the nearby road), than the same hours on the normal day. O 3 reached a peak mixing ratio of 43 ppbv at 14:00 on the episode day while O 3 remained at an almost flat level of ~20 ppbv in the early afternoon hours on 21 December. The model-predicted N 2 O 5 reached above 10 pptv and peaked at 25 pptv in the period of 14:00 16:45 due to the sustained high NO 2 in combination with reduced photolysis loss (Figure 8b). Similar high abundance of daytime N 2 O 5 had been measured in the field. Brown et al. [2005] reported aircraft observations of a high N 2 O 5 level (10 15 pptv) in late afternoon of 6 August in the region near New York City and Boston. They attributed the high abundance of N 2 O 5 to increased NO x in the region and reduced photolysis due to cloudiness. Our model results indicate that the heterogeneous pathway could play a key role in elevating aerosol nitrate even during daytime. For the rapid increase in PM 2.5 nitrate observed in the periods of 10:30 12:30 and 14:00 and 16:30 on the episodic day (Figure 7), we note that the sum of the model-predicted NO 3 potential productions (5.3 and 5.8 μgm 3 h 1 during the two periods) fall short in accounting for the rapid increase of NO 3 concentration (8.0 and 9.3 μgm 3 h 1, respectively). Such a deficiency in nitrate production could be contributed by transport of NO 3 from the adjacent areas. XUE ET AL American Geophysical Union. All Rights Reserved. 4900

14 5. Summary Chemical composition and size distributions of inorganic soluble aerosol (ISA) on PM 2.5 were characterized with a PILS-IC system and MOUDI in a residential district in Hong Kong during December The sampling campaign captured a severe pollution episode on 25 December, during which the visibility dropped to 3.7 ± 1.0 km. Among the ISA species, nitrate increased most prominently; therefore, special attention was paid to investigate its formation and chemical transformation characteristics. Major findings include the following: 1. The three major secondary inorganic ions, SO 4 2,NH 4 +, and NO 3, were significant contributor to PM 2.5, accounting for 47 ± 6% of PM 2.5 mass. The average NO 3 concentration was 4.5 μgm 3, with significant temporal variation from 0.8 to 40.5 μgm The episodic hours were characterized by nitrate being the most abundant component (27.8 μgm 3 ) in PM 2.5 (107.0 μgm 3 ), an increase by 5.2 times in comparison with the normal hours. Nitrate was fully balanced by NH 4 +, indicating abundant presence of NH 3. These observations highlight the importance of nitrate in leading to pollution episodes in a polluted high NO x environment where NH 3 is also abundant. 3. Varied size distributions were observed for NO 3. During the episode, 84% of NO 3 was distributed in fine mode particles, significantly contributing to the elevated PM 2.5 level. Investigation of size characteristics of NO 3 shows that the fine mode NO 3 is more likely to occur when the fine particles are less acidic and the sea-salt aerosol concentrations are low. 4. Analysis using an Observation-Based Model for Secondary Inorganic Aerosols shows that both the gasphase production of HNO 3 and the heterogeneous pathway are significantly enhanced during the episodic hours in comparison with normal hours. The heterogeneous hydrolysis of N 2 O 5 was largely responsible for sustaining high PM 2.5 nitrate in the episodic afternoon due to persistently high NO 2 and reduced photolysis loss of N 2 O 5. Acknowledgments This work was partly supported by the Research Grant Council of Hong Kong (615406), Hong Kong University Grant Council Special Equipment Grant (SEG HKUST07), the Hong Kong University Science and Technology (FSGRF12IPO07), and the HKUST Fok Ying Tung Graduate School (NRC06/07. SC01). We thank Peter Louie and Connie Luk of HKEPD for providing air quality data and logistic help in setting up the PILS at Tung Chung. References Alves, C. A., C. Goncalves, C. A. Pio, F. Mirante, A. Caseiro, L. Tarelho, M. C. Freitas, and D. X. Viegas (2010), Smoke emissions from biomass burning in a Mediterranean shrubland, Atmos. Environ., 44, Brown, S. S., et al. (2005), Aircraft observations of daytime NO3 and N2O5 and their implications for tropospheric chemistry, J. Photochem. Photobio. A Chem., 176, Dong, Y. J., M. D. Hays, N. D. Smith, and J. S. Kinsey (2004), Inverting cascade impactor data for size-resolved characterization of fine particulate source emissions, J. Aerosol Sci., 35, Fung, J. C. H., A. K. H. Lau, J. S. L. Lam, and Z. Yuan (2005), Observational and modeling analysis of a severe air pollution episode in western Hong Kong, J. Geophys. Res., 110, D09105, doi: /2004jd Grover, B. D., M. Kleinman, N. L. Eatough, D. J. Eatough, P. K. Hopke, R. W. Long, W. E. Wilson, M. B. Meyer, and J. L. Ambs (2005), Measurement of total PM2.5 mass (nonvolatile plus semivolatile) with the Filter Dynamic Measurement System tapered element oscillating microbalance monitor, J. Geophys. Res., 110, D07S03, doi: /2004jd Hagler, G. S., et al. (2006), Source areas and chemical composition of fine particulate matter in the Pearl River Delta region of China, Atmos. Environ., 40, He, K. B., J. H. Tan, J. C. Duan, Y. L. Ma, F. K. Duan, Y. Chen, and J. M. Fu (2009), Chemical characteristics of PM(2.5) during a typical haze episode in Guangzhou, J. Environ. Sci. China, 21, Ho, K. F., S. C. Lee, C. K. Chan, J. C. Yu, J. C. Chow, and X. H. Yao (2003), Characterization of chemical species in PM2.5 and PM10 aerosols in Hong Kong, Atmos. Environ., 37, Hofzumahaus, A., et al. (2009), Amplified trace gas removal in the troposphere, Science, 324, Huang, X. F., J. Z. Yu, L. Y. He, and Z. B. Yuan (2006), Water-soluble organic carbon and oxalate in aerosols at a coastal urban site in China: Size distribution characteristics, sources, and formation mechanisms, J. Geophys. Res., 111, D22212, doi: /2006jd Jacob, D. J. (2000), Heterogeneous chemistry and tropospheric ozone, Atmos. Environ., 34, Kaufman, Y. J., and R. S. Fraser (1997), The effect of smoke particles on clouds and climate forcing, Sci. Total Environ., 277, Kerminen, V. M., and A. S. Wexler (1995), Growth laws for atmospheric aerosol-particles An examination of the bimodality of the accumulation-mode, Atmos. Environ., 29, Lau, K. H., W. M. Wu, J. C. H. Fung, R. C. Henry, and B. Barron (2005), Significant marine source for SO2 levels in Hong Kong. Lee, T., S. M. Kreidenweis, and J. L. Collett (2004), Aerosol ion characteristics during the Big Bend Regional Aerosol and Visibility Observational study, J. Air Waste Manage. Assoc., 54, Lee, T., X. Y. Yu, B. Ayres, S. M. Kreidenweis, W. C. Malm, and J. L. Collett (2008), Observations of fine and coarse particle nitrate at several rural locations in the United States, Atmos. Environ., 42, Li, S. P., J. Matthews, and A. Sinha (2008), Atmospheric hydroxyl radical production from electronically excited NO2 and H2O, Science, 319, Li, X. G., S. X. Wang, L. Duan, J. M. Hao, C. Li, Y. S. Chen, and L. Yang (2007), Particulate and trace gas emissions from open burning of wheat straw and corn stover in China, Environ. Sci. Technol., 41, Lin, Y. C., and M. T. Cheng (2007), Evaluation of formation rate of NO 2 to gaseous and particulate nitrate in the urban atmosphere, Atmos. Environ., 41, XUE ET AL American Geophysical Union. All Rights Reserved. 4901