Characteristics of particulate constituents and gas precursors during
the episode and non-episode periods
Jiun-Horng Tsai1, Wei-Fan Lai1, Hung-Lung Chiang2*
1Department of Environmental Engineering, Sustainable Environmental Research Center, National Cheng-Kung University, Tainan, Taiwan.
2Department of Health Risk Management, China Medical University, Taichung, 40402, Taiwan
IMPLICATIONS
Size-segregated distribution and chemical compositions of atmospheric aerosols play important roles in their visibility reduction, health effects, and toxicity in urban areas. Inorganic ionic species are major constituents in particulate matter, except carbonaceous chemicals. In this work, the compositions of water-soluble ions in particulate matter and acid/base gaseous pollutants (such as HNO2, HNO3, HCl, SO2,
NH3) were determined during the day and at night during episode and non-episode
periods from 2006 to 2007 in southern Taiwan.
ABSTRACT
Size-segregated distribution of ambient particulate matter (PM) was determined using a Micro Orifice Uniform Deposition Impactor (MOUDI) and a Nano-MOUDI in southern Taiwan. Eleven water-soluble ionic species including six anions (NO3-, SO42-, Cl-, F-, NO2-, Br-) and five cations (NH4+, Na+, K+, Ca2+, Mg2+) for particulate inorganic ions and five gaseous pollutants (i.e., HNO2, HNO3, HCl, SO2, NH3) were analyzed during episode and non-episode periods. The particulate mass concentration was about 30 g/m3 higher at night than during the day, and it reached 162 g/m3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
during the episode periods. The difference was mainly attributable to the particle size of 0.1-2.5 m. Nitrate, sulfate, ammonium, and chloride ions were the dominant inorganic ions in PM. HONO and NH3 concentrations were high at night; in contrast, HNO3, HCl and SO2 were high during the day. The equivalent ratio of {[NO3-] +2[SO42-]}/[NH4+] was about 0.98 and revealed a high correlation between {[NO3-] +2[SO42-]} and [NH4+] that clearly pointed to ammonium neutralization or condensation of ammonium nitrate and ammonium sulfate in PM0.32. The precursor gases and ionic species in different particle sizes did not reveal a strong correlation, which could be attributed to the complex of source emissions, atmospheric reactions and meteorological parameters in the area.
Keywords: particulate matter; size segregated distribution; inorganic ions
INTRODUCTION
Particulate matter (PM) can cause a wide range of diseases in children and adults. It has contributed to a significant reduction in life expectancy in Europe (WHO, 2006) and the U.S. (Pope III et al., 2009). Many epidemiological studies have been published on the health risks, including cardiovascular and respiratory disease, associated with PM (Oberdorster et al., 1995; Burnett et al., 1997; Ostro et al., 2000; Health Effects Institute, 2003; Brunekreef and Forsberg, 2005; Pope III and Dockery, 2006). Research has also shown an increase in mortality due to lung cancer and other cardiopulmonary diseases (Naess et al., 2007; Brunekreef et al., 2009; Boldo et al., 2011). The size-segregated distribution and chemical compositions of atmospheric aerosols play important roles in their toxicity, health effects, and visibility in urban areas.
PM can come from natural sources such as volcanic ash, soil, road dust, sea salt and organics and from human activities such as fossil fuel combustion, industrial 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53
processes, and vehicle emission. PM particles can range in size from a few nm to tens of m. PM fractions have been shown to cause adverse health effects, and the differences reported in different studies may be partly due to variations in sources, particle size, and chemical composition. Therefore, an understanding of PM constituents is a basic but important issue for air quality management.
Generally, inorganic ionic species are dominant constituents in PM, except carbonaceous chemicals (Kim et al., 2000; Pathak et al., 2004; Bari et al., 2003; Pathak and Chan, 2005; Aneja et al., 2006; Hsieh et al., 2009). Several studies have reported sulfate, nitrate and ammonium as the dominant water-soluble ions in PM (Aneja et al., 2006; Perrone et al., 2006; Hsieh et al., 2009; Lin et al., 2009, Plaza et al., 2011). But the mass size distribution of water-soluble inorganic species is still not well understood, and information about how the gas precursors react and transfer to form aerosol constituents is still lacking in southern Taiwan. In addition, gas phase, condensation processes and photochemical reactions in the atmosphere for secondary aerosol formation could be important mechanisms in urban areas; NOx, NH3 and SO2 emitted from natural and artificial sources have been shown to lead to the formation of nitrate, ammonium and sulfate in atmospheric particulate matter (Buhr et al., 1995; Hazi et al., 2003; Pathak and Chan, 2005; Baker and Scheff, 2007; Brock et al., 2008; Renner and Wolke, 2010). Therefore, the size distributions of ionic species in PM and acid/base gases were investigated in this work to understand the PM composition and its relationship to gas precursors.
Sulfate and nitrate are mainly attributed to photochemical reaction, with different patterns evidenced during the day and at night (Kundu et al., 2009). In addition, meteorological parameters (e.g., temperature, humidity, and solar radiation) could be important factors with secondary aerosols. Brock et al. (2008) showed that in 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78
the northeastern United States, the gas-phase oxidation of SO2 played an important role in oxidation chemistry; sulfate and associated ammonium were the dominant components of PM in the summer. PM concentration and chemical composition are determined not only by emission sources, but also by atmospheric circulation, which influences important factors such as dispersion, transport and stagnation of pollutants.
A Micro Orifice Uniform Deposition Impactor (MOUDI) and a Nano-MOUDI were employed to measure the size-segregated distribution of ambient particulate matter in southern Taiwan. The water-soluble ionic species including anions (NO3-, SO42-, Cl-, F-, NO2-, Br-) and cations (NH4+, Na+, K+, Ca2+, Mg2+) for particulate constituents and gaseous pollutants (such as HNO2, HNO3, HCl, SO2, NH3) were determined during episode and non-episode periods. Day and night concentration variations of inorganic ion in particulate matter and acid/base gases were determined in this work.
EXPERIMENTAL
Characteristic of Sampling Area
The sampling site is located at Daliao ambient air quality monitoring station, which is part of the Taiwan Air Quality Monitoring Network established by the Taiwan Environmental Protection Administration (TEPA) in 1993. This monitoring station was located at the southeast end of the Kao-Ping ambient air quality basin, where the air quality has been reported as the worst in Taiwan, primarily due to the high emission of air pollutants in the area. Daliao is located in the rural area of Kaohsiung and has a population density of 1500 people/km2. Kaohsiung, an urban, agricultural and industrial metropolitan city in southern Taiwan, is the second largest city in the country.
79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103
Daliao sampling station is 12 km away from the coastline, near a rural-industrial complex area with various agricultural activities and heavy industry--i.e., Da-Fa industrial district is less than 0.3 km to the east, Lin-Hai industrial district is approximately 6.5 km to the west, and Lin-Yuan industrial district is approximately 4.5 km to the southwest.
In total, 34,000 ton yr-1 PM2.5, 157,000 ton yr-1 non-methane hydrocarbon, 66,000 ton yr-1 SOx, and 164,000 ton yr-1 NOx were emitted in the Kaohsiung area (TEPA, 2006). Fifty percent of the air pollutants was emitted from stationary sources (power plant, oil refinery plant, iron and steel industry, petrochemical industry, and others), 28% from area sources (fugitive emission) and 22% from mobile sources (motorcycles, gasoline vehicles, diesel vehicles and off-road vehicles)(TEPA, 2006). Based on the emission inventory conducted by TEPA, emissions from the Kaohsiung air basin contributed over 20% to total air pollutant emissions in Taiwan, and the environmental loading of air pollutants in Kaohsiung was nearly twice that of other air basins in Taiwan (TEPA, 2005 and 2006). The location of the sampling site and emission sources is shown in Figure 1.
Although particulate matter accounts for a large portion of the air pollution in this area, meteorological variations also influence air quality episodes. Generally, the rainy season runs from May to September (summer to autumn), and high-pollution episodes often occur between October and February (winter to spring) during the following year.
One sampling site was used in this work, which was a limitation of this study. But the topography of the Kao-Ping area facilitates transport and mixing. The station could accurately represent the air quality trend of the Kao-Ping air basin, with the 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
sampling period covering both cold and warm seasons and more than 60 samples taken in 2006-2007.
Sampling Program
In January, March, August and December 2006 and July, November and December 2007, there were 30 episode samples (with an average PM10 concentration of 166 ± 31 g m-3) and 35 non-episode samples (with an average PM10 concentration of 69 ± 33 g m-3) during which TEPA monitored for PM10 levels. The sampling concentration of PM10 ≥125 g/m3 was regarded as the episode days and the PM10 concentration <125 g/m3 was presented as the non-episode days which is base on the ambient air quality standard of 24 h PM10 concentration is set at 125 g/m3 in Taiwan.
MOUDI and nano-MOUDI
A MOUDI and a nano-MOUDI sampler were used to take the PM samples. This equipment has been used previously by many other investigators (e.g., Geller et al. 2002; Miguel et al. 2005). The designed cut-off sizes were 18, 3.2, 1.8, 1.0, 0.56, 0.32, 0.18, 0.10, 0.056, 0.032, 0.018, and 0.010 m. But 2.5 and 10 m are not the typical cut-off sizes of MOUDI. Therefore, the interpolation method was employed to determine the mass concentration at the special particle size range. The flow rates for MOUDI and nano-MOUDI were 30 and 10 L min–1, respectively. Particulate matter was collected using 47-mm Teflon filters (ZefluorTM-supported PTFE) for the nano-MOUDI sampler and 37-mm filters for the nano-MOUDI sampler. Prior to weighing, the filters were conditioned at 252oC and 405% relative humidity for 48 h. The weight of the filters and collected mass particulate concentration were measured using a microbalance (Mettler Toledo, MX5) with a reading precision of 3 g at 25oC and 40% relative humidity. Denuder Sampling 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152
The denuder system employed in this study was composed of a cyclone with a cut-off diameter of 2.5 m (University Research Glassware, URG, Chapel Hill Inc., USA) followed by four annular denuders (URG-2000-30EH), a filter pack, a flow controller and a pump(USEPA, 1998). Airflow was set at a constant rate of 16.7 l min-1.
The first denuder was coated with 10 ml of 0.1% (w/v) NaCl in 1:9 methanol/deionized water solutions for the absorption of HNO3 gas (Perrino et al., 1990; USEPA, 1998). The second and third denuders were coated with 10 ml 1:1 (v:v) mixtures of 2% (w/v) Na2CO3 in deionized water and 2% (w/v) glycerol in methanol solution for the absorption of HCl, HNO2 and SO2 gas. The fourth was coated with 10 ml of 1% (w/v) citric acid in methanol solution for the absorption of NH3 gas. Three filters placed in series followed the denuders. The first Teflon filter (Pallflex, 47 mm, pore size: 2 m, USA) was set up to collect particulate matter < 2.5 m in diameter. In order to collect acid gas that evaporated from particles or that was not completely absorbed by the denuder, the next quartz filter was coated with Na2CO3 solution. The last quartz filter was coated with a citric acid solution and designed to collect NH3 evaporated from the particles. After sampling, each denuder tube and filter was extracted with deionized water and analyzed by ionic chromatography. Two denuder sampling systems were analyzed at Daliao station for quality assurance and quality control procedures, and the relative error for all gas species and particulate ions ranged from 8-17%. In addition, the additives of HNO3, SO2 and NH3 gases were used to measure the recovery of the denuder adsorption system. Recoveries were 8910, 958 and 1027% for HNO3, SO2 and NH3, respectively. The gas collection efficiency was similar to that reported in other studies (Sioutas et al., 1996; Acker et al., 2005).
153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177
Chemical Analysis
The collected aerosol filters were ultrasonically extracted for 2 h into 20 ml of deionized distilled water and passed through a Teflon filter of 4.5 m nominal pore size. Ion chromatography (Dionex, 120) was used to analyze the concentration of anions (Br-, F-, Cl-, NO2-, NO3-, SO42-) and cations (Na+, NH4+, K+, Mg2+, Ca2+). The separation of anions was accomplished using an IonPac AS 12A (4×200 mm) analytical column, an AG 14 guard column with a 10 l sample loop, and an anion self-regenerating suppressor-ultra. A solution of 2.7 mM Na2CO3/0.3 mM NaHCO3 was used as an effluent at a flow rate of 1.5 ml min-1. The separation of cations was accomplished using an IonPac CS 12A (4×250 mm) analytical column, a CG 14 guard column with a 50 l sample loop, and a cation self-regenerating suppressor-ultra. A solution of 20 mM methanesulfonic acid was used as the eluent at a flow rate of 1 ml min-1. This analysis method yielded detection limits between 0.002 (Mg2+) and 0.04 (NO2-) g m-3 and recoveries from 89 (Na+) to 107% (NO2-).
Some studies reported in the literature have indicated an ionic imbalance due to carbonate species, especially in coarse particles when dust was abundant (Noguchi et al., 2004; Hodzic et al., 2006). In this study, there was not an abundance of coarse particles, and the anion-to-cation charge ratio was 0.940.13 in coarse particles. Therefore, the carbonate content did not seem to affect the ionic balance of particulate composition; however, the carbonate species were not examined in this work, which could be a limitation of the study.
In addition, two sets of MOUDI and Nano-MOUDI samplers and Denuder samplers were run for the same sampling site for quality assurance and quality control procedures, for a total of 12 samples. The relative errors of mass concentrations were 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201
about 6-12% for micro-scale PM and 15-43% for nanoscale PM, and the relative errors of ionic species analysis were 12-18% in micro-scale PM and 16-45% in nanoscale PM. Therefore, high uncertainty was observed in the nanoscale particles.
RESULTS AND DISCUSSION PM Mass Concentration
Mass size-segregated distribution of particulate matter is shown in Table 1 and Figure 2. The mass concentrations of different particle sizes were insignificantly different between daytime and nighttime on non-episode days. But the particulate mass concentration was about 30 g m-3 higher at night, and it reached 162 g m-3
during the episode days. The difference of PM mass concentration was mainly attributed to particles in the size range of 0.1-2.5 m (accumulation mode), and it increased about 60 g m-3 at night during episode days compared to non-episode days.
Some samples were high in nanoparticles during the day, which suggests that photochemical reaction is one source of nanoparticles in the atmosphere (shown in Figure 2). In addition, the mass concentration during the day was about 59% and 22% higher than that at night during the episode and non-episode periods, respectively, at a particle size of less than 0.1 m. In other size particles (> 0.1 m), the mass concentrations during the day were higher than at night. This could suggest that photochemical reaction is a source of nanoparticle formation in ambient air.
Three particulate mass concentration peaks were observed, as shown in Figure 2. One was at 3.2 m (coarse particles), another was at 0.56 m (accumulation mode, fine particles), and a small peak was at 0.032 m. Coarse particles are formed by mechanical processes such as wind erosion or grinding processes from large particles. Therefore, soil, wind-blown dust, or sea spray could be the sources of coarse particles 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226
in Daliao. Fine particles are formed by nucleation with gases, coagulation of smaller particles in the nuclei range or condensation of low-volatility vapors. Industrial processes, fuel combustion (boiler, motor vehicles such as diesel vehicles) and chemical reactions could be sources of fine particles. Seinfeld and Pandis, (2006) reported a small peak at Aitken modes (in the vicinity of 0.032 m), which was formed by the hot vapor condensation of combustion sources and the nucleation of atmospheric species to form fresh particles.
Table 2 shows the meteorological parameters during the episode and non-episode periods. The day and night wind speeds were 1.80.5 and 1.30.5 m s-1 on the
episode days and 2.10.7 and 1.00.5 m s-1 on the non-episode days. The temperature
was 262oC during the day and 212oC at night for episode days and 293oC during
the day and 265oC at night for non-episode days. The humidity was 615% during
the day and 754% at night during the episode periods and 599% during the day and 775% at night during non-episode periods. The difference of wind speed and humidity was insignificant during the episode and non-episode periods. The low temperature was observed during the episode periods, reflecting the poor air quality in the cold seasons such as winter and spring.
Figure 3 presents the relation of wind direction and particulate mass concentration distribution. Results indicated that the high PM concentration was associated with winds from the northwest (pollutants from motor vehicles could be transported from the downtown area of Kaohsiung), north (Renda petrochemical industrial district) and northeast (Dafa industrial district) in winter. Low PM concentration was associated with winds from the southwest (Linyuan petrochemical industrial district) and southeast (agricultural area), and the day and night wind directions were more different in summer than in winter. Based on the back trajectory 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251
analysis (Figure 1)—the back trajectory was a grid cell model (2 2 km) developed by Chang’s groups (Lin and Chang, 2002)—the air mass was transported through the ocean to carry clean air to the station in the summer. In the winter, the air mass was transported over the land to carry the upwind polluted air and pass the station. The prevailing monsoon wind affects wind direction seasonally (northerly in winter and southerly in summer) and local circulation, i.e., land-sea breeze, affects the daily fluctuation of wind direction. The wind direction was determined by the back trajectory, which was the pathway of the air parcel passing Daliao station (it took 3 hours for the air parcel to travel this distance). In this study, 60% of the samples were taken during PM episode periods, and 40% were taken during non-episode periods in the winter. The prevailing wind directions in the winter were northwest (24%), north (20%) and northeast (16%), with these winds transporting the polluted air mass to Daliao. In the summer, the air mass came primarily from the west (21%), southwest (36%), southeast (29%) and east (14%), resulting in clean air at Daliao station (Figure 1).
Mass Concentration Distribution of Inorganic Ions
The mass concentrations of sodium, calcium, magnesium, and potassium ions were less than 3% of PM mass. Chloride ions accounted for 1.6-4.6% PM mass. Ammonium, nitrate, and sulfate were about 5.4-11.2, 9.4-21 and 12-15% of PM mass, respectively. Nitrate, sulfate, ammonium, and chloride ions were the dominant inorganic ions in PM (Figures 4 and 5).
Sodium ion. Sodium ions were not significantly different between day and night during the non-episode periods, and a similar mass size distribution was observed during the day and at night. During the episode periods, sodium ions were 1.8 times higher than on non-episode days and increased to 3.1 g m-3; however, the difference 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277
between day and night was still not significant.
Calcium ion. The concentration of calcium ions was also not significantly different between day and night during the non-episode periods. A similar mass size distribution was observed during the day and at night. An increase in calcium ions of about 2.6 times was observed during the episode days.
Magnesium ion. The concentration of magnesium ions was not significantly different between day and night during the non-episode periods. Magnesium ions were 2.4 times higher on episode days than on no-episode days. A similar mass size distribution was observed during the day and at night during both periods.
Potassium ion. Potassium ion level was 30% higher at night than during the day. In addition, the K+ content was 2.4 times higher on the episode days than on non-episode days. An increase was observed at the size range of 0.1-1 m during the episode days. Sea breezes could have been the prevailing wind, carrying some sea spray and potassium ions in the composition of sea salt. A fertilizer industry located in the vicinity of Lin-Hai industrial district could be one of the emission sources of potassium ions. Furthermore, vegetable burning and agricultural activities could be other sources of K+ in the accumulation mode (Silva et al., 1999).
Ammonium. High ammonium was measured at night. Ammonium concentration during the episode periods was about 3.2 times higher than on non-episode days. Mass concentration fractions of ammonium were dominant at particle sizes of 0.1 and 1-2.5 m.
Chloride ion. High chloride ions were determined at night during both periods. During the day, chloride ions were 45% higher on episode days than on non-episode days. But at night, chloride ions increased significantly to 7.40 g m-3 during the episode periods. A large increase was observed at the size range from 0.1-2.5 m, and a slight increase was seen at particle size > 2.5 m.
278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303
Sulfate. Sulfate concentration was 7 percent higher at night than during the day. Sulfate concentration on the episode days was about 2.7 times higher than on non-episode days. Mass concentration was predominant at particle size of 0.1-1 and 1-2.5 m.
Nitrate. The nitrate concentration was 1.6 times higher at night than during the day. Nitrate concentration during the episode periods was about 3.9 times that of non-episode periods. Mass concentration fractions of nitrate were dominant at sizes 0.1-1 and 1-2.5 m, especially at night during episode periods. A nitrate mass fraction of 24-57% was determined in coarse particles, and a high fraction (45-57%) was observed during the day (NaNO3, sea breeze). It has been reported that coarse mode nitrate particles result from reactions of nitric acid or its precursors with sea salt or soil dust and ammonium nitrate in fine particles (Lee et al., 2008).
Some studies in the literature indicated that PM2.5 concentration was 44-68
g/m3, and the main ionic constituents were SO
42- at 7.7-10 g/m3, NO3-at 3.5-6.1
g/m3, NH
4+ at 3.9-5.1, K+ was 1.0-1.4 g/m3, and Cl- was 1.3-1.4 g/m3 in southern
Taiwan (Tsai and Chen, 2006). The mass concentration and ionic concentration were in the range of episode and non-episode periods of this study, and the sulfate and nitrate contents were about half of those measured in this study. In addition, another study investigated PM2.5 concentration, and their results were similar to ours during
non-episode periods; but high chloride ion and sulfate content were observed, which they attributed to their sampling site being near the coast (Tsai et al., 2011).
To compare the mass concentration ionic species in the daytime during episode and non-episode periods, ammonium, nitrate and sulfate were the major abundant ionic species. The increase of these ionic species was significant in the size range of 0.1-2.5 m, and the mass increases were 5.27 g/m3 for NH
4+, 6.91 g/m3 for
NO3- and 10.62 g/m3 for SO42-. The increment of 0.1-2.5 m could explain the
increase in TSP constituents between the episode and non-episode days: 92% for 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330
NH4+, 59% for NO3- and 87% for SO42-. There was a 4.66 g/m3 increase for NO3- at
particle sizes over 2.5 m. This demonstrates that high nitrate fraction can occur in coarse particulate matter, not only on fine particles. At night, NH4+, NO3- and SO4
2-were also the major ionic species, and the increase of these ionic species was significant in the size range of 0.1-2.5 m. The mass increases were 11.56 g/m3 for
NH4+ (87% of NH4+ increase in TSP), 20.68 g/m3 for NO3- (77% of NO3- increase in
TSP) and 11.49 g/m3 for SO
42-(81% of SO42- increase in TSP). More NH4+ and NO3
-concentration increases were determined in fine particles at night than during the day during episode periods.
Viana et al. (2005) investigated the levels of crustal components and found that secondary inorganic and carbon species are higher at night. Nitrate levels are higher at night due to the thermal stability of NH4NO3. Sulfate levels are high at night as a consequence of lower mixing height. Perrone et al. (2006) found that sulfate, nitrate, sodium ions and ammonium were the main inorganic ionic species, accounting for up to 38% of PM mass at a coastal site. Results were similar to this work, with high nitrate, sulfate and ammonium in PM. Kundu et al. (2009) found that SO42- and CH3SO3- were the photochemical products during the daytime. NO3- was also a photochemical product, and it transitioned to the aerosol phase under lower temperature and higher humidity. The hydrolysis of N2O5 on aqueous aerosol particles yields NO3-.
The higher abundance of SO42- in daytime samples and high concentration of NO3- at night is due to high humidity and low temperature, which thermodynamically favors the reaction between gaseous NH3 and HNO3 to form aerosol nitrates such as ammonium nitrate.
Acid and Base Gases
Table 3 shows the concentrations of acid and base gases. HONO and NH3 concentrations were high at night. The HONO concentration ratio of night and day was 1.3 for non-episode days and 1.8 for episode days. Nitrous acid concentration was high during episode days, especially at night. High HONO at night could come from emissions, i.e., combustion engines (diesel vehicles) (Kurtenbach et al., 2001), or 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361
chemical conversion of heterogeneous NO2-HONO (Su et al., 2008; An et al., 2009; Yu et al., 2009) In addition, nitrous acid was rapidly photolyzed at wavelengths 400 nm during the day (Calvert et al., 1994). Thus, HONO accumulated mostly at night, and it could be consumed by photolysis from “OH push” after sunrise (Platt and Perner, 1980; Staffelbach et al., 1997; Acker et al., 2005).
The night-day NH3 concentration ratio was 2.2 for non-episode days and 1.8 for episode days. In addition, the difference of ammonia concentration was insignificant between the episode and non-episode periods. Industrial process emissions and agricultural activities near the sampling station could be the reasons for high NH3 concentration in the area. Furthermore, the stable atmosphere could be another reason for higher NH3 at night (Cadle et al., 1982; Singh et al., 2001).
The concentration of HNO3 during the day was about 8.2 times higher than at night for Daliao for both periods. In addition, the HNO3 concentration during the episode days was 1.8 times higher than on non-episode periods. Hydroxyl radicals react with NO2 during the day and produce HNO3, which could be one of the dominant mechanisms after sunrise (Russell et al., 1984 and 1985) and might cause the high HNO3 concentration during the day. The observed low mixing ratio of HNO3 at night aerosol suggests that NO3- production was due to the reaction of HNO3. Hydrolysis of N2O5 on aqueous aerosol particles may occur more at night than during the day in sampling periods.
HCl was found in higher concentrations during the daytime and in lower concentrations at night for both episode and non-episode periods. At night, the HCl concentration was high on episode days. The reaction of HNO3 with NaCl in sea salt
particles could be one of the important sources of HCl near the coast (Eldering et al.,1991; Seinfeld and Pandis, 2006). Higher HCl concentration was observed on non-episode days than on non-episode days. This could be attributed to the reaction of HCl 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388
with NH3 producing NH4Cl (Chang and Allen, 2006; Seinfeld and Pandis, 2006),
which can accumulate in fine particles. The acid solutions including HCl were used in tank cleaning processes at a plant in the vicinity of Daliao station (Da-Fen Industrial District). This is an important source of HCl in the area. In addition, the chlorine industry (producing chloralkali, liquid chlorine, hydrochloric acid, etc.) in the Lin-Hai industry district (near the Daliao station) and the hazardous waste incinerator and municipal waste incinerator (TEPA, 2006) could be potential sources of HCl. High ammonia concentration was determined in the area, and it could neutralize acid gases (such as HNO3, H2SO4 and HCl) to form particles, which could be a reason that high
HCl concentrations were found during the day but not at night during non-episode periods. In addition, HCl could be emitted from the coal combustion and refuse, and waste incineration can lead to higher HCl concentration during the daytime in urban areas (Biswas et al., 2008). High NH3 concentration and low HCl in gas form and high
NH4+ and Cl- in fine PM was found during episode periods. The rich ammonia could
promote the reaction of NH4Cl in fine particles.
SO2 concentration was 1.7 times higher during the day than at night in the area. In addition, the SO2 concentration during the episode periods was 1.8 times higher than on non-episode days. Human activities such as motor vehicles (i.e., diesel engines) and industrial processes (i.e., boiler combustion, oil refinery, power plant) could be the main reasons for SO2 concentration to be high during the day. On the episode days, high SO2 concentration could be attributed to meteorological effects such as low mixing height, low wind speed and different wind direction oriented to the different pollution sources.
Comparison of the acid and base gas levels during episode and non-episode periods showed that HNO2 was high on episode days, especially at night. An increase
389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413
of about two times was determined for HNO3 and SO2 during episode periods. But the
concentration difference of NH3 was insignificant between episode and non-episode
periods.
Correlations of Inorganic Ions
A strong correlation was observed among Na+, Mg2+ and Ca2+ at fine particle sizes, indicating that these ions could come from the same sources, such as sea salt or road salt (Maxwell-Meier etal., 2004; John et al., 2007).
Sodium ion, potassium ion, chloride ion and sulfate
Generally, potassium ions at fine particle sizes could be released from the burning of biomass and react with the sulfate to form K2SO4. A high correlation between K+ and SO42- was determined at PM0.1 (Figure 6(a)). But the relationship of Na+ and SO42- was insignificant. There was little relationship between K+ and SO42- at particle sizes > 0.1 m.
The molar concentration of the sodium ion, potassium ion, and chloride ion system at PM0.1 indicated a strong correlation between Na+ and Cl-, but K+ and Cl- did not evidence the same trend (Figure 6(b)). Sea salt could be an important source of Na+ and Cl- at PM0.1 (Mason, 2001). More recent studies have indicated that particles < 0.1 m also contain sea salt (Geever et al., 2005; Clarke et al., 2006). In addition, a high correlation was determined in fine particles (dp < 1m) but not in coarse mode particulate matter.
Ammonium, nitrate and sulfate
Based on the molar concentration of ammonium, sulfate and nitrate at 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438
different particle sizes, ammonium did not in general have a strong correlation to nitrate (r2 was from 0.44-0.86) or sulfate (r2 was from 0.56-0.64). However, a strong correlation was found between ammonium and nitrate at the particle size >1 m (Figure 6(c)). Results indicated that ammonium could neutralize nitrate to form NH4NO3 at the particle size > 1 m. Nitrate came from both primary and secondary sources, with the coarse mode nitrate generated from sea salt spray and the fine mode nitrate produced by photochemical reaction. Lee et al (2003) indicated that combustion was the dominant source of NH4+, NO3-, SO42-, and CO and NH4+could neutralize the NO3- and SO42- during ACE (Aerosol Characterization Experiment)-Asia and TRACE-P (Transport and Chemical Evolution over the Pacific). Their results were similar to this work, which implies a high correlation among ammonium, sulfate and nitrate in PM.
The equivalent ratio of {[NO3-]+2[SO42-]}/[NH4+] was about 0.98 and revealed a high correlation between {[NO3-]+2[SO42-]} and [NH4+] that clearly pointed out the ammonium neutralization or condensation of ammonium nitrate and ammonium sulfate in PM0.32 (Figure 6(d)). In addition, emissions of precursor gases (e.g., SO2, NOx, NH3) convert and react to form ammonium nitrate (NH4NO3), ammonium sulfate ((NH4)2SO4), and ammonium bisulfate (NH4HSO4) in the particulate phase.
According to the results reported by Wall et al. (1988), aerodynamic diameters of nitrate peaks were 0.2, 0.7 and 3 m. The sulfate distribution in PM was significant in the sub-micron range, about 0.5 m (Lestari et al., 2003), and most of the SO42- is
in the fine particles, particularly particle size less than 1 m (Turpin et al., 1997; Zhuang et al., 1999; Park and Kim, 2004). In addition, a large fraction of ammonium, sulfate and nitrate were determined in the particle size range 0.1-1 m, and (NH4)2SO4
formed in 0.03-0.3m and (NH4)2SO4·2NH4NO3 formed in 0.3-1.0 m (Bassett and
439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463
Seinfeld, 1983 and 1984). The concentration peaks of ammonium, sulfate and nitrate were around 0.2 m, which is the result of condensation of the secondary components from the gas phase (Wall et al., 1988; Seinfeld and Pandis, 2006).
But the precursor gases and ionic species in different particle sizes did not reveal a strong correlation in this study. The complex of source emissions, atmospheric reactions and meteorological parameters could affect the relationship of precursor gases and ionic species in particulate matter.
CONCLUSIONS
PM mass concentration was 13332 and 16226 g/m3 for daytime and nighttime
during the episode periods, and the concentration level was 2-3 times higher than that during non-episode periods. The mass fractions of particulate size of 0.1-2.5m were about 53-63% of TSP mass concentrations. Three particulate mass concentration peaks were observed: one at the size at 3.2 m, another at 0.56 m and a small peak at 0.032 m PM mass. Ammonium was 5.4-11.2%, nitrate was 9.4-21%, sulfate was 12-15%, and chloride ion was 1.6-4.6% of PM mass. HONO concentration ratio of night and day was 1.3 for non-episode days and 1.8 for episode days, and the NH3 concentration ratio of night and day was 2.2 for non-episode days and 1.8 for episode days. The concentration of HNO3 during the day was about 8.2 times higher than that at night for Daliao for both periods. SO2 concentration was 1.7 times higher during the day than at night in the area. In addition, the SO2 concentration during the episode periods was 1.8 times that of non-episode days. A high correlation between K+ and SO42- and Na+ and Cl- was determined at PM0.1. A high correlation was determined between {[NO3-]+2[SO42-]} and [NH4+], which clearly pointed out the ammonium neutralization or condensation of ammonium nitrate and ammonium sulfate in PM0.32. The precursor gases and ionic species in different particle sizes did not reveal a strong 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489
correlation, which could be due to the complex of source emissions, atmospheric reactions and meteorological parameters.
REFERENCES
Acker, K., D. Möller, R. Auel, W. Wieprecht, and D. Kala. 2005. Concentration of nitrous aid, nitric acid, nitrite and nitrate in the gas and aerosol phase at a site in the emission zone during ESCOMPTE 2001 Experiment.
Atmospheric Research 74:507-524.
An, J., W. Zhang, and Y. Qu. 2009. Impacts of a strong cold front on concentrations of HONO, HCHO, O3 and NO2 in the heavy traffic urban area of Beijing.
Atmospheric Environment 43:3454-3459.
Aneja, V.P., B. Wang, D.Q. Tong, H. Kimball, and J. Steger. 2006. Characterization of major chemical components of fine particulate matter in North Carolina.
Journal of Air & Waste Management Association 56:1099-1107.
Baker, K., and P. Scheff. 2007. Photochemical model performance for PM2.5 sulfate, nitrate, ammonium, and precursor species SO2, HNO3, and NH3 at background monitor locations in the central and eastern United State.
Atmospheric Environment 41:6185-6195.
Bari, A., V. Ferraro, L.R. Wilson, D. Luttinger, and L. Husain. 2003. Measurements of gaseous HONO, HNO3, SO2, HCl, NH3, particulate sulfate and PM2.5 in New York, NY. Atmospheric Environment 37:2825-2835.
Bassett, M. and J.H. Seinfeld. 1983. Atmospheric equilibrium model of sulfate and nitrate aerosols. Atmospheric Environment 17:2237-2252.
Bassett, M. and J.H. Seinfeld. 1984. Atmospheric equilibrium model of sulfate and nitrate aerosols II. Particle size analysis. Atmospheric Environment 18:1163-490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514
1170.
Biswas, K.F., B.M., Ghauri, and L. Husain. 2008. Gaseous and aerosol pollutants during fog and clear episodes in South Asian urban atmosphere. Atmospheric Environment 42:7775–7785.
Boldo, E., C. Linares, J. Lumbreras, R. Borge, A. Narros, J. Garćia-Pérez, P. Fernández-Navarro, B. Pérez-Gómez, N. Aragonés, R. Ramis, M. Pollán, T. Moreno, A. Karanasiou, and G. López-Abente. 2011. Health impact assessment of a reduction in ambient PM2.5 levels in Spain. Environment
International 37:342-348.
Brock, C.A., A.P. Sullivan, R.E. Peltier, R.J. Weber, A. Wollny, J.A. de Gouw, A.M. Middlebrook, E.L. Atlas, A. Stohl, M.K. Trainer, O.R. Cooper, F.C. Fehsenfeld, G.J. Frost, J.S. Holloway, G. Hübler, J.A. Neuman, T.B. Ryerson, C. Warneke, and J.C. Wilson. 2008. Sources of particulate matter in northeastern United States in summer: 2. Evolution of chemical and microphysical properties. Journal of Geophysical Research 113:D08302, doi:10.1029/2007JD009241.
Brunekreef, B., R. Beelen, G. Hoek, L. Schouten, S. Bausch-Goldbohm, P. Fischer, et al., 2009. Effects of Long-Term Exposure to Traffic-Related Air Pollution on Respiratory and Cardiovascular Mortality in the Netherlands: The NLCS-AIR Study. Research Report Health Effects Institute 5-71.
Brunekreef, B., and B. Forsberg. 2005. Epidemiological evidence of effects of coarse airborne particles on health. European Respiratory Journal 26:309-318. Buhr, S.M., M.P. Buhr, F.C. Fehsenfeld, J.S. Holloway, U. Karst, R.B. Norton, D.D.
Parrish, and R.E. Sievers. 1995. Development of a semi-continuous method for the measurement of the nitric acid vapor and particulate nitrate and 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539
sulfate. Atmospheric Environment 29:2609-2624.
Burnett, R.T., S. Cakmak, J.R. Brook, and D. Krewski. 1997. The Role of particulate size and chemistry in the association between summertime ambient air pollution and hospitalization for cardiorespiratory disease. Environmental
Health Perspectives 105:614-620.
Cadle, S.H., R.J. Countessand, and N.A. Kelley. 1982. Nitric acid and ammonia in urban and rural locations. Atmospheric Environment 16:2501-2506.
Calvert, J.G., G. Yarwood, and A. Dunker. 1994. An evaluation of the mechanism of nitrous acid formation in the urban atmosphere. Research on Chemical
Intermediates 20:463-502.
Chang, S., and D.T. Allen. 2006. Chlorine chemistry in urban atmospheres: Aerosol formation associated with anthropogenic chlorine emissions in southern Texas. Atmospheric Environment 40 (Supplement 2) s512-s523.
Clarke, A.D., S.R. Owens, and J. Zhou. 2006. An ultrafine sea-salt flux from breaking waves: implications for cloud condensation nuclei in the remote marine atmosphere. Journal of Geophysical Research 111:D06202, doi:10.1029/2005JD006565.
Eldering, A., P.A., Solomon, L.G., Salmon, T., Fall, and G.R., Cass. 1991. Hydrochloric-acid –a regional perspective on concentrations and formation in the atmosphere of southern California. Atmospheric Environment 25: 2091–2102.
Geever, M., C.D. O’Dowd, S. van Ekeren, R. Flanagan, E.D. Nilsson, G. de Leeuw, and U. Rannik. 2005. Submicro sea-spray fluxes. Geophysical Research
Letters 32:L15810, doi:10.1029/2005GL023081.
Geller, M.D., S. Kim, C. Misra, C. Sioutas, B.A. Olson, and V.A. Marple. 2002. A methodology for measuring size-dependent chemical composition of 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565
ultrafine particles. Aerosol Science and Technology 36:748-762.
Hazi, Y., M.S.A. Heikkinen, and B.S. Cohen. 2003. Size distribution of acidic sulfate ions in fine ambient particulate matter and assessment of source region effect. Atmospheric Environment 37:5403-5413.
Health Effects Institute. 2003. Revised analyses of the national morbidity, mortality
and air pollution study, part II: revised analyses of selected time-series studies of air pollution and health. Cambridge, MA.
Hodzic, A., B. Bessagnet, and R. Vautard. 2006. A model evaluation of coarse-mode nitrate heterogeneous formation on dust particles. Atmospheric Environment 40: 4158-4171.
Hsieh, L.Y., S.C. Kuo, C.L. Chen, and Y.I. Tsai. 2009. Size distribution of nano/micro dicarboxylic acids and inorganic ions in suburban pm episode and non-episodic aerosol. Atmospheric Environment 43:4396-4406.
John, K., S. Karnae, K. Crist, M. Kim, and A. Kulkarni. 2007. Analysis of trace elements and ions in ambient fine particulate matter at three elementary schools in Ohio. Journal of Air & Waste Management Association 57:394-406.
Kim, B.M., S. Teffera, and M.D., Zeldin. 2000. Characterization of PM2.5 and PM10 in
the south coast air basin of southern California: Part I-spatial variations.
Journal of Air & Waste Management Association 50:2034-2044.
Kundu, S., K. Kawamura, T.W. Andreae, A. Hoffer, and M.O. Andreae. 2009. Diurnal variation in the water-soluble inorganic ions, organic carbon and isotopic compositions of total carbon and nitrogen in biomass burning aerosols from the LBA-SMOCC campaign in Rondônia, Brazil. Journal of
Aerosol Science 41:118-131. 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590
Kurtenbach, R., K.H. Becker, J.A.G. Gomes, J. Kleffmann, J.C. Lörzer, M. Spittler, P. Wiesen, R. Ackermann, A. Geyer, and U. Platt. 2001. Investigations of emissions and heterogeneous formation of HONO in a road traffic tunnel.
Atmospheric Environment 35:3385-3394.
Lee, T.Y., X.Y. Yu, B. Ayres, S.M. Kreidenweis, W.C. Malm, and J.L. Collett Jr. 2008. Observations of fine and coarse particle nitrate at several rural locations in the United States. Atmospheric Environment 42:2720-2732. Lee, Y.N., R. Weber, Y. Ma, D. Orsini, K. Maxwell-Meier, D. Blake, S. Meinardi, G.
Sachse, C. Harward, T.Y. Chen, D. Thornton, F.H. Tu, and A. Bandy. 2003. Airborne measurement of inorganic ionic components of fine aerosol particles using the particle-into-liquid sampler coupled to ion chromatography technique during ACE-Asia and TRACE-P. Journal of
Geophysical Research 108;D238646, doi:10.1029/2002JD003265.
Lestari, P., A. K., Oskouie, and K. E. Noll. 2003. Size distribution and fry deposition of particulate mass, sulfate and nitrate in urban area. Atmospheric
Environment 37: 2507-2516.
Lin, C.C., K.L. Huang, S.J. Chen, S.C. Liu, J.H. Tsai, Y.C. Lin, and W.Y. Lin. 2009. NH4+, NO3- and SO42- in roadside and rural size-resolved particles and transformation of NO2/SO2 to nanoparticle-bound NO3- / SO42-. Atmospheric
Environment 43:2731-2736.
Lin, C.H., and L. F.W. Chang. 2002. Relative source contribution analysis using an air trajectory statistical approach. Journal of Geophysical Research 107, (D21) 4583, doi;10.1029/2001JD001301.
Lin, Y.C., M.T. Cheng, W.Y. Ting, and C.R. Yeh. 2006. Characteristics of gaseous HNO2, HNO3, NH3 and particulate ammonium nitrate in an urban city of
Central Taiwan. Atmospheric Environment 40:4725-4733. 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616
Mason, B.J. 2001. The role of sea salt particles as could condensation nuclei over the remote oceans. Quarterly Journal of the Royal Meteorological Society 127:2023-2032.
Maxwell-Meier, K., R. Weber, C. Song, D. Orsini, Y. Ma, G.R. Carmichael, and D.G. Streets. 2004. Inorganic composition of fine particles in mixed mineral dust-pollution plume observed from airborne measurements during ACE-Asia.
Journal of Geophysical Research 109:D19S07, doi:10.1029/2003JD004464.
Miguel, A.H., A. Eiguren-Fernandez, C. Sioutas, P.M. Fine, M. Geller, and P.R. Mayo. 2005. Observation of twelve USEPA priority polycyclic aromatic hydrocarbons in the Aitken size range (10-32 nm Dp). Aerosol Science and
Technology 39:415-418.
Naess, O., F.N. Piro, P. Nafstad, G.D. Smith, and A.H. Leyland. 2007. Air pollution, social deprivation and mortality: a multilevel cohort study. Epidemiology 18:686-694.
Noguchi, I., and H. Hara. 2004. Ionic Imbalance Due to Hydrogen Carbonate from Asian Dust. Atmospheric Environment 38: 6969-6976.
Oberdorster, G., R.M. Gelein, J.Ferin, and B. Weiss. 1995. Association of particulate air pollution and acute mortality: involvement of ultra-fine particles?
Inhalation Toxicology 7:111-124.
Ostro, B.D., R, Broadwin, and M.J. Lipsett. 2000. Coarse and fine particles and daily mortality in the coachella valley, California: a follow-up study. Journal of
Exposure Science and Environmental Epidemiology 10:412-419.
Park, S.S., and Y.J. Kim. 2004. PM2.5 Particles and size-segregated ionic species
measured during fall season in three urban sites in Korea. Atmospheric
Environment 38:1459-1471. 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641
Pathak, R.K., X. Yao, and C.K. Chan. 2004. Sampling artifacts of acidity and ionic species in PM2.5. Environmental Science and Technology 38:254-259.
Pathak, R.K., and C.K. Chan. 2005. Inter-particle and gas-particle interactions in sampling artifacts of PM2.5 in filter-based samplers. Atmospheric
Environment 39:1597-1607.
Perrone, M.R., A. Turnone, A. Buccolieri, and G. Buccolieri. 2006. Particulate matter characterization at a coastal site in south-eastern Italy. Journal of
Environmental Monitoring 8:183-190.
Perrino, C., F. DeSantis, and A. Febo. 1990. Criteria for the choice of a denuder sampling technique devoted to the measurement of atmospheric nitrous and nitric acids. Atmospheric Environment 24A:617-626.
Platt, U., and D. Perner. 1980. Direct measurements of atmospheric CH2O, HNO2, O3, NO2 and SO2 by differential optical absorption in the near UV. Journal of
Geophysical Research 85:7453-7458.
Plaza, J., M. Pujadas, F.J. Gómez-Moreno, M. Sánchez, and B. Artíñano. 2011. Mass size distribution of soluble sulfate, nitrate and ammonium in the Madrid urban aerosol. Atmospheric Environment 45:4966-4976.
Pope III, C.A., and D.W., Dockery. 2006. Health effects of fine particulate air pollution: lines that connect. Journal of Air & Waste Management
Association 56:709-742.
Pope III, C.A., E. Majid, and D.W. Dogulas. 2009. Fine-particulate air pollution and life expectancy in the United States. The New England Journal Medicine 360:376-386.
Renner, E., and R. Wolke. 2010. Modelling the formation and atmospheric transport of secondary inorganic aerosols with special attention to regions with high ammonia emissions. Atmospheric Environment 44:1904-1912.
642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667
Russell, A.G., G.J. McRae, and G.R. Cass. 1984. Acid deposition of Photochemical
Oxidation Products-a Study Using a Lagrangian Trajectory Models. In Air
Pollution Modeling and its Application III. De Wispelaere, C. Ed., Plenem
press, New York, p.539-564.
Russell, A.G., G.J. McRae, and G.R. Cass. 1985. The Dynamics of Nitric Acid
Production and the Fate of Nitrogen Oxides. Atmospheric Environment 19:
893-902.
Seinfeld, J.H., and S.N. Pandis. 2006. Atmospheric Chemistry and Physics: from Air
Pollution to Climate Change. John Wiley & Sons, Inc. New York.
Silva, P.J., D.Y. Liu, C.A. Noble, and K.A. Prather. 1999. Size and chemical characterization of individual particles resulting from biomass burning of local southern California species. Environmental Science and Technology 33:3068-3076.
Singh, S.P., G.S. Satsangi, P. Khare, A. Lakhani, K. Maharaj Kumari, and S.S. Srivastava. 2001. Multiphase measurement of atmospheric ammonia.
Chemosphere – Global Change Science 3:107-116.
Sioutas, C., P.Y. Wang, S.T. Ferguson, P. Koutrakis, and J.D. Mulik. 1996. Laboratory and field evaluation of an improved glass honeycomb denuder/filter pack sampler. Atmospheric Environment 30:885-895.
Staffelbach, T., A. Neftel, and L.W. Horowitz. 1997. Photochemical oxidant formation over southern Switzerland: 2. model results. Journal of
Geophysical Research 102:23363-73.
Su, H., Y.F. Cheng, P. Cheng, Y.H. Zhang, S. Dong, L.M. Zeng, X. Wang, J. Slanina, M. Shao, and A. Wiedensohler. 2008. Observation of nighttime nitrous acid (HONO) formation at a non-urban site during PRIDE-PRD2004 in China. 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692
Atmospheric Environment 42:6219-6232.
Taiwan Environmental Protection Agency (TEPA). 2005. Air Pollutants Emission
Database and Air Quality Management Program. EPA-94-FA11-030-A139.
Taipei, Taiwan.
TEPA. 2006. Emission of air pollutants in Taiwan- Taiwan emission data system (TEDS 6.1), Taipei. (in Chinese).
Tsai, H.H., C.S., Yuan, C.H., Hung, and C. Lin, 2011. Physicochemical properties of
PM2.5 and PM2.5-10 at inland and offshore sites over southeastern Coastal
region of Taiwan Strait. Aerosol and Air Quality Research 11: 664-678.
Tsai, Y.I., and C.L., Chen. 2006. Characterization of Asian Dust Storm and Non-Asian Dust Storm PM2.5 Aerosol in Southern Taiwan. Atmospheric
Environment 40: 4734-4750.
Turpin, B.J., P., Saxena, G. Allen, P., Koutrakis, P., McMurry, L., Hidemann and, Mead-view, AZ. 1997. Characterization of the southwestern desert aerosol.
Journal of Air & Waste Management Association 47:344-356.
USEPA. 1998. Compendium of Methods for the Determination of Inorganic
Compounds in Ambient Air –io-4.2 Determination of Reactive Acid and Basic Gases and Strong Acidity in Fine Particles, USEPA publication
625/R-96/010a, Cincinnati, OH.
Viana, M., C. Pérez, X. Querol, A. Alastuey, S. Nickovic, and J.M. Baldasano. 2005 Spatial and temporal variability of PM levels and composition in a complex summer atmospheric scenario in Barcelona (NE Spain). Atmospheric
Environment 39:5343-5361.
Wall, S.M., W. John, and J.L., Ondo. 1988. Measurement of aerosol size distributions for nitrate and major ionic species. Atmospheric Environment 22:1649-1656. World Health Organization (WHO). 2006. Health Risks of Particulate Matter from
Long-Range Transboundary Air Pollution. Denmark.
693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719
Yu, Y., B. Galle, A. Panday, E. Hodson, R. Prinn, and S. Wang. 2009. Observations of high rates of NO2-HONO conversion in the nocturnal atmospheric boundary layer in Kathmandu, Nepal. Atmospheric Chemistry and Physics 9:6401-6415.
Zhuang, H., C.K., Chan, M., Fang, and A.S., Wexler. 1999. Size distributions of particulate sulfate, nitrate, and ammonium at a coastal site in Hong Kong.
Atmospheric Environment 33:843-853. 720 721 722 723 724 725 726
Table and Figure captions
Table
Table 1 PM mass concentration at different particle sizes on episode and non-episode days
Table 2 Meteorological parameter during the sampling periods
Table 3 Acid and base gases concentration (μg m-3) on episode and non-episode days
Figure
Figure 1 Map of sampling site
Figure 2 PM mass concentration distribution of different size segregation
Figure 3 PM mass concentration distribution at different wind directions in winter and summer
Figure 4 Distribution of inorganic ions in different PM sizes during the day and at night during non-episode periods
Figure 5 Distribution of inorganic ions in different PM size during the day and at night during episode periods
Figure 6 Relationships of inorganic ions in particulate matter 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749
