Levels and Composition of Ambient Particulate Matter at a Mountainous Rural Site in Northern Vietnam

Transcription

1 Aerosol and Air Quality Research, 14: , 2014 Copyright Taiwan Association for Aerosol Research ISSN: print / online doi: /aaqr Levels and Composition of Ambient Particulate Matter at a Mountainous Rural Site in Northern Vietnam Hoang Xuan Co 1, Nghiem Trung Dung 2, Nguyen Thi Kim Oanh 3*, Nguyen Thanh Hang 3, Nguyen Hong Phuc 3, Hoang Anh Le 1 1 Faculty of Environmental Science, Hanoi University of Science, Vietnam 2 School of Environmental Science and Technology, Hanoi University of Science and Technology, Vietnam 3 Environmental Engineering and Management, Asian Institute of Technology, Thailand ABSTRACT Samples of 24 h PM 10 and PM 2.5 were collected at a mountainous rural site of Tamdao, Vietnam, using collocated dichotomous and MiniVol samplers. The sampling was done in wet season (20 September 8 October 2005), dry season (17 December January 2006) and transitional season (5 April 26 April 2010). A pair of PM 2.5 and PM or PM 10 samples was collected on a sampling day using quartz and mixed cellulose filters for each size fraction. The samples were analyzed for mass, BC, water soluble inorganic ions and elemental compositions. Higher PM 2.5 levels were obtained during dry season, at an average of 51 µg/m 3, followed by the transitional season, 33 µg/m 3, and the lowest in wet season, 25 µg/m 3. The ratios between anions and cations, both in equivalence, were all below 1.0, but was higher for PM 2.5 than for PM The ammonium balance showed a good agreement between measured and estimated levels for PM 2.5, suggesting that most of sulfate and nitrate were in their ammonium salts. The reconstructed mass showed high contributions from secondary inorganic particles, OM-biomass (estimated based on K + ), crustal and soot groups, which accordingly helped to reveal major contributing sources. Specifically, the high K-biomass and OM-biomass mass group in the dry season indicated the important contribution from biomass burning. The regional transport from surrounding territories to the site was investigated using 5-day HYSPLIT backward trajectories. The differences in PM mass and compositional species that were statistically significant between the seasons for similar trajectory patterns, or between patterns within a season, suggested the effects of seasons and/or air mass trajectory pathways on PM pollution. The northeast continental type of air masses observed in the dry season, with the longest continental pathway and continental origin, was associated with the highest levels of PM mass and compositional species. Keywords: PM 2.5 ; BC; Contributing sources; Regional transport; Mountainous site; Northern Vietnam. INTRODUCTION Ambient particulate matter (PM) air pollution is a leading environmental problem in most developing countries. PM, especially those of fine sizes, causes multiple effects on human health and the environment (Pope III et al., 2009). The effects of PM depend mainly on their size and compositions which in turn are related to their emission sources and/or formation pathways. PM has a wide range of man-made and natural sources, such as traffic, industrial activity, biomass burning, construction dust or wind-blown soil dust and sea spray. PM is also formed in the atmosphere from relevant gaseous precursors, called the secondary PM, * Corresponding author. Tel.: ; Fax: address: kimoanh@ait.ac.th which are mainly present in the fine fraction, i.e., PM 2.5 (particles with the size not above 2.5 µm). Black carbon (BC), a product of incomplete combustion, a major component of PM 2.5, can efficiently absorb solar radiation. BC is currently considered as second to only CO 2 in term of the positive net climate-forcing (warming) effect (Bond et al., 2013). Atmospheric particles have a relatively short atmospheric lifetime of a few hours to a few weeks hence their levels and chemical compositions exhibit large variations in time and space depending on emission sources and meteorological conditions. A number of studies have been conducted to characterize PM levels and composition in the ambient air in Vietnam (Hien et al., 2002; Hien et al., 2005; Kim Oanh et al., 2006; Cohen et al., 2010a; Hai and Kim Oanh, 2013; and references therein). However, so far those studies focused mainly on two large cities, Hanoi and Ho Chi Minh City, and results consistently show high levels of PM 2.5 and PM 10 in these urban areas. Some of these studies have indicated

2 1918 Co et al., Aerosol and Air Quality Research, 14: , 2014 a high potential of long range transport (LRT) of pollution to Hanoi during the northeast monsoon (Cohen et al., 2010b). No detail data have yet reported for any rural site. To partly fill this gap, the Asian regional air pollution research network (AIRPET), as detailed in Kim Oanh et al. (2006), extended the monitoring activities to a rural mountainous site in Northern Vietnam. This paper reports the results of this monitoring effort for levels and composition of PM 10 (particles with size equal or below 10 µm) and PM 2.5, and discussed the possible contributing sources. METHODOLOGY Sampling Location Tamdao is a long mountain range running along the northwestern and south-eastern direction (Fig. S1, supplementary information, SI), in Northern Vietnam. The sampling site ( N, E) was located in the Tamdao (TD) village, at the altitude of about 1000 meters above the sea level, of Vinh Phuc province which is northwest of Hanoi. The area experiences the typical monsoon climate of the Northern Vietnam with relatively cold and dry winters (Nov Mar) when it is under the influence of northeast monsoon, wet and hot summers (May Sept) when it is under the influence of southwest monsoon, and the transitional periods between these two seasons (Ngu and Hieu, 2004). Due to its location, the average annual temperature of TD is C (Vu and Nguyen, 2000) as compared to Hanoi of C (GSO, 2013). It also has a relatively high annual rainfall, mm, and more than 90% of which is received during the wet season (Ngu and Hieu, 2004). This is a tourism site but most activities are mainly concentrated in the summer months with the operation of a few hotels and restaurants. There is a small and scattered agricultural community around the site (see Google map inserted in Fig. S1) with a population of around 600 people spreading over an area of 215 ha. Some small towns are located around the site but the nearest town is 10 km away while Hanoi is about 50 km to the south. The industrial activities, such as a large metallurgical industrial complex in Thai Nguyen and several medium size industrial estates located in Hanoi, Tuyen Quang, Vinh Phuc, and Phu Tho provinces, are situated within a radius of km from the site (Fig. S1). PM Sampling The PM sampling was first conducted in the wet season (20 Sept 8 Oct 2005) and the dry season (17 Dec Jan 2006). Later, an additional sampling period was conducted to characterize the PM in the transitional season (5 Apr 26 Apr 2010). During the sampling periods, 24h samples of PM 2.5 and PM 10 were collected using a dichotomous sampler (collecting PM 2.5 and PM ) and collocated two Airmetrics MiniVol samplers (collecting PM 2.5 and PM 10 ). In the transitional season of 2010, however, only Airmetrics MiniVol samplers were used to collect 24 h samples of PM 2.5 and PM 10, respectively. To enable a more complete characterization of PM composition, two filter types (quartz and mixed cellulose ester) were used simultaneously to collect samples for each size range (PM 2.5 and PM or PM 10 ) on every sampling day. Before sampling, the quartz filters were prebaked at 550 C for 5 6 hours to remove carbonaceous/organic contaminants. Filters were conditioned for about 24 h (temperature 20 ± 5 C, relative humidity 40 ± 10%) for the gravimetric mass determination before sampling. Each pre-weighed filter was kept in a Petri-dish and then put in an airtight bag until sampling start. After sampling, the sampled filter was placed back in the Petri-dish and then the airtight bag and refrigerated. The samples were transported to the analytical laboratories in Hanoi and the Asian Institute of Technology (AIT) for analyses. The period between sampling and analysis was generally less than one month for the samples in the dry and wet season, but was about 1.5 months for the transitional season samples. The flow rate of the deployed samplers was calibrated at the site before each sampling period. Sample Analysis The PM samples were analyzed for mass and chemical compositions including BC, water soluble inorganic ions and elements. Mass was determined using the quartz filter samples by a 5-digit analytical balance AT261 DeltaRange, Mettler Toledo, Switzerland at the Hanoi University of Science and Technology (HUST). The sampled filters were segregated and subjected to multiple compositional analyses following the same methods as previously described in Kim Oanh et al. (2006). The samples were analyzed for eight water soluble ions (see detail in Fig. 2) by the Ion Chromatography (IC), and 13 elements by X-Ray Fluorescence (XRF) in the Institute for Nuclear Science and Technique (Vietnam Atomic Energy Commission). At AIT, the elemental composition of the transitional season samples were analyzed by Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). The detail on the elements analyzed is presented in Fig. 3 and Table S1(a), SI together with the analytical results. All BC measurements were done using M43D Digital Smoke Stain Reflectometer at AIT, Thailand with the detail QA/QC presented in Kim Oanh et al. (2009). About 3 4 trip/field blanks and laboratory blanks were analyzed for each sampling period and the results were accordingly blank corrected. The average blanks were below 1 µg per filter for all ions except for calcium which had a higher blank, 2.7 µg per filter. The elemental analyses by the AIRPET network were previously evaluated using a standard reference material and proven to be satisfactory as previously reported (Kim Oanh et al., 2006). To identify potential contributing sources to PM, the mass was reconstructed for each sample using the major measured mass groups, including soot (BC), sea salt (2.54 Na + ), secondary inorganic particles (NH 4 +, NO 3 and SO 4 2 ), crustal oxides [1.16 (1.9Al Si Ca Ti Fe)] and trace metals (remaining analyzed non-crustal elements). In addition, a group called K-biomass which was estimated as (K Fe) as suggested by Chan et al. (1997), was also estimated to give an indication on biomass emission. There was no organic carbon (OC) data hence the total organic matter (OM) was not determined. Instead,

3 Co et al., Aerosol and Air Quality Research, 14: , to roughly estimate the contribution from biomass burning the OC-biomass was first calculated based on the K-biomass data following the method presented in Duan et al. (2004). Recognizing that the ratio of OC/K + for ambient air PM is site specific, this study used the ratio obtained from the measurement results for rice straw burning smoke to estimate OC-biomass, i.e., OC = 335 ± 88 vs. K + = 50 ± 34 mg/g of PM 2.5, and OC = 330 ± 85 vs. K + = 47 ± 36 mg/g of PM 10 (Kim Oanh et al., 2010). Accordingly, an OC/K + ratio of 330/50 or 6.6 was used for both PM size ranges to calculate OC-biomass from the available K-biomass data. Further, OC-biomass was converted to OM-biomass using a factor of 1.9 which was the value obtained for fresh smoke (fire place) compiled by Turpin and Lim (2001). There was no elemental composition data for the coarse fraction (PM ) in dry and wet season samples hence K + (instead of K- biomass) was used to estimate OC-biomass but then a factor of 1.7 (for urban aerosol) was used to convert OC-biomass to OM in these cases. The potential LRT of air pollution to the study site was studied using the 5 day HYSPLIT backward trajectories of the air masses arriving at the site at 00:00 UTC (7:00 LST) on each monitoring day. RESULTS AND DISCUSSION Daily and Seasonal Levels of PM and BC A total of 57 pairs of valid 24 h PM 2.5 and PM 10 samples were obtained at the sampling site, one pair on each sampling day. Some samples during the transitional season had broken filters hence were discarded. More PM samples were collected in the polluted dry season (30) than the wet season (15) and the transitional season (12). All valid samples were analyzed for PM mass and the results are summarized in Table 1. As expected, higher levels of PM were observed during the dry season, the seasonal PM 2.5 average of 51 ± 29 µg/m 3, followed by the transitional season of 33 ± 21 µg/m 3 and the lowest was in the wet season (25 ± 12 µg/m 3 ). A similar trend was also observed for PM 10, i.e. 67 ± 32, 44 ± 22 and 33 ± 11 µg/m 3 for the 3 seasons, respectively. Overall, the PM levels varied widely from day to day during a season, which can be seen in the large standard deviations shown in Table 1 and the fluctuations in the daily levels presented in Fig. 1. The maximum 24h PM 2.5 level was 99 µg/m 3 (Fig. 1) which was obtained on 18 and 21 Dec 2005, the middle of dry season. The highest 24h PM 2.5 level in the transitional season was 83 µg/m 3 (11 Apr 2010), which was almost double of the maximum level in the wet season (43 µg/m 3, 5 Oct 2005). For PM 10, the maximum 24h level observed in the dry season was on 22 Dec (117 µg/m 3 ) while for the transitional and wet season it appeared on the same day when PM 2.5 was also maximum and was 98, and 49 µg/m 3, respectively. The concentration of the coarse fraction (PM ) was relatively small compared to the fine fraction (Fig. 1). Accordingly, the average ratios between PM 2.5 and PM 10 (PM 2.5 /PM 10 ) were between in the 3 seasons Table h PM 2.5 and PM 10 mass concentrations at Tamdao, µg/m 3 (1 atm., 25 C). Season PM 2.5 PM 10 R 2 of PM (µg/m 3 ) (µg/m 3 PM ) 2.5 /PM 10 ratio 2.5 vs. PM 10 regression Dry (n = 30) 51 ± ± ± Wet (n = 15) 25 ± ± ± Transitional (n = 12) 33 ± ± ± Fig. 1. Daily mass of PM and associated BC levels at Tamdao site.

4 1920 Co et al., Aerosol and Air Quality Research, 14: , 2014 (Table 1). This suggested important contributions from combustion emission and secondary particles which, in principle, generate PM in the fine mode. A strong correlation existed between PM 2.5 and PM 10 in each season with a large value of R 2 ( ) which indicated common sources/processes leading to build-up of PM of both size fractions. The variations in PM 10 levels were thus largely determined by those in PM 2.5 and this also emphasized on the importance in investigation of the source contributions to PM 2.5 at this rural site. In contrast, the correlation between PM 2.5 and PM was poor with their regression lines having R² of 0.017, and , for the three seasons, respectively. This was anticipated as the fine and coarse particles are, in principle, originated from different sources and processes. The variations in seasonal average PM levels in TD can be explained by the variations in meteorology and regional emission sources. For example, higher levels in dry season were linked to the less wet removal, more stable atmosphere under the influence of a high-pressure ridge, higher potential of LRT to Northern Vietnam by the NE monsoon (Hien et al., 2002; Cohen et al., 2010b; Hai and Kim Oanh, 2013). As compared to the levels reported for industrial and traffic sites in large cities in Vietnam, such as Hanoi and Ho Chi Minh City, PM levels in TD were relatively lower (Table 2) which was anticipated because of a general absence of significant local PM sources at this rural area. For example, traffic, residential, construction activities have been reported to be major local sources in Hanoi (Hai and Kim Oanh, 2013). Overall, the differences in PM 10 reported in these studies were more pronounced than the differences in PM 2.5. In fact, there were no significant differences in PM 2.5 levels measured in the dry season between TD and one urban site in Hanoi reported by Hien et al. (2002) and Cohen et al. (2010a). However, when other sites in Hanoi were considered, such as the average for 5 sites in Hanoi (Kim Oanh et al., 2006) or the level at an industrial mixed site in the city (Hai and Kim Oanh, 2013), the levels in Hanoi were significantly above those in TD for both PM 2.5 and PM 10. The PM 2.5 levels in TD were also lower than those reported at a traffic site in Ho Chi Minh City (Giang, 2008) as shown in Table 2. This suggests that the spatial variations of PM measured in a city are significant hence the levels measured at a single site reported in some previous studies for Hanoi may not be representative for the whole city. More uniformity in PM 2.5 (than PM 10 ) across sites in a region is normally expected as the fine PM have a higher potential for LRT than coarse PM. PM 2.5 also contains secondary particles that are formed in the atmosphere, and during the time period required for their formation both precursors and secondary PM would spread over a wide region. Fig. 1 also shows the daily BC levels in PM 2.5 and PM 10, and which were respectively averaged at 4.1 ± 1.4 and 5.3 ± 1.9 µg/m 3 in dry season, 1.8 ± 2.8 and 2.0 ± 2.7 µg/m 3 in transitional, and 2.2 ± 0.6 and 2.9 ± 0.6 µg/m 3 in the wet season. Majority of BC in TD was found in the fine particles (76 78% of the total BC in PM 10 ). The average BC concentrations measured in this site were lower than the levels averaged over 5 sites in Hanoi during , which respectively for PM 10 and PM 2.5 were 10.7 ± 6.9 and 5.9 ± 3.2 µg/m 3 in the dry season and 10.3 ± 7.1 and 4.8 ± 2.6 µg/m 3 in wet season (Kim Oanh et al., 2006, 2012). There were higher variations in daily BC and PM levels during the transitional season (Fig. 1). Generally, the days with low PM levels were shown consistently with low BC. Based on our observation, the spikes of high measured BC and PM 2.5 may be linked to the influence of diesel powered vehicles running on local roads passing near the site. For example, occasionally there were trucks and tourist buses operating on these roads but these activities were mainly observed in the transitional and wet season (summer time) and more on weekends. During the dry season, which is the cold season in the study area, there generally was no tourist activity. It is also interesting to note that the days with high BC (and PM) were mainly around weekend (Friday, Saturday Table 2. Comparison of 24 h PM in Tamdao remote site with levels in large cities of Vietnam. City Location Period Particulate matter size (µg/m 3 ) PM 10 PM 2.5 Reference Tam dao Rural site 17 Dec Jan. dry 67 ± ± 29 This study 2006 Rural site 20 Sep. 8 Oct wet 33 ± ± 12 This study Rural site 5 26 Apr transitional 44 ± ± 21 This study Hanoi One urban site Oct Mar dry 122 a 52 ± 29 Hien et al. (2002) May 1999 Jul wet 47 a 19 ± 8 One urban site Sunday, & Wedn. multiyear, NA b 54 ± 33 Cohen et al. (2010) all seasons Industrial mixed site Dec Feb dry 98 ± ± 32 Hai and Kim Oanh (2013) Average, 5 urban dry 144 ± ± 50 Kim Oanh et al. sites wet 67 ± ± 27 (2012) Ho Chi Minh city Roadside dry NA b 82 ± 17 Giang (2008) a estimated based on the average coarse and fine fractions presented in Hien et al. (2002). b Not available.

5 Co et al., Aerosol and Air Quality Research, 14: , or Sunday) such as 11 Apr (Sunday) and 24 Apr 2010 (Saturday, transitional season) or Sept 2005 (Friday Sunday, wet season). In addition, the local community may contribute emissions from residential cooking and/or open burning. Nevertheless, the number of valid samples was still relatively small, especially in the transitional season, hence a routine sampling is essentially required to produce seasonal representative results in future studies. Seasonal Levels of Ionic and Elemental Compositions Seasonal levels of water soluble inorganic ions in PM 2.5 and PM 10 are shown in Fig. 2. The levels in fine and coarse PM fractions collected by the dichotomous sampler for dry and wet seasons were summed up to get those in PM 10. The daily variation patterns in ion levels of fine particle and coarse particle were quite similar, especially for those which predominantly presented in the fine fraction (sulfate, ammonium and nitrate). High levels of these ions in PM 2.5 indicate a significant contribution of secondary inorganic particles to the fine PM mass. Sulfate was the most abundant ion specie in PM 2.5 and was the highest during the dry season (9.8 ± 5.9 µg/m 3 ), followed by the wet (7.5 ± 4.3 µg/m 3 ) and the lowest in the transitional season (2.1 ± 1.0 µg/m 3 ). Ammonium in PM 2.5 was also highest during the dry season (3.9 ± 2.3 µg/m 3 ), closely followed by the wet season (3.1 ± 1.7 µg/m 3 ) while the lowest level was observed in the transitional season (1.2 ± 0.6 µg/m 3 ). Nitrate was the third most abundant specie in PM 2.5 and was also the highest during the dry season, 1.6 ± 1.5 µg/m 3. Note that, the nitrate level in the coarse fraction was also equally high. Potassium level was highest during the dry season and more abundant in the fine fraction (1.2 ± 0.9 µg/m 3 ) than the coarse fraction (PM ) while the opposite was observed for magnesium and calcium which had higher levels in the coarse fraction (Table S1(a), SI). The ion balance was checked for each PM size fraction in three seasons. The ratios between the sum of anions (chloride, nitrate and sulfate, in µeq/m 3 ) to the sum of cations (ammonium, sodium, potassium, magnesium and calcium, in µeq/m 3 ) were all less than 1.0, in spite of the lack of H + data (Table 3). The difference may be due to the presence of sulfate and/or nitrate salts in other forms than ammonium sulfate and/or ammonium nitrate. Higher ratios obtained for the fine fraction suggesting its higher acidity than the coarse fraction. The linear regression between cation sum (X) and anion sum (Y) also had higher slopes for PM 2.5, 0.81 for dry and 0.77 for wet season, than the coarse fraction, 0.40 for dry and 0.44 for wet season. The higher anion to cation ratios obtained for PM 2.5 in the dry season suggested a higher contribution from acidic particles which in turn may be explained by a more efficient wet removal and less formation potential of these acidic particles in other seasons. The correlations of the anion sum and cation sum were however significant with R 2 for all regression lines of (Table 3 and Fig. S2, SI). Note that the use of MiniVol samplers in the transitional season sampling did µg/m³ 20 a) Ions in PM 2.5 Dry Trans Wet µg/m³ 20 b) Ions in PM 10 Dry Trans Wet Cl NO₃ SO₄² Na+ NH₄+ K+ Mg²+ Ca²+ Cl NO₃ SO₄² Na+ NH₄+ K+ Mg²+ Ca²+ Fig. 2. Levels of water soluble ions in PM 2.5 (a) and PM 10 (b) at Tamdao site. Table 3. Ion balance for PM in different seasons. Season PM size Anion/Cation ratio Cation (x) vs. Anion (y) regression Slope R 2 Dry PM ± (n = 30) PM ± a PM ± Wet PM ± (n = 15) PM ± PM ± Transitional PM ± (n = 12) PM ± a Intercept = 0.06, for other cases intercept = 0.

6 1922 Co et al., Aerosol and Air Quality Research, 14: , 2014 not directly produce the coarse fraction (PM ) and the anion to cation ratio was 0.61 for PM 2.5 and 0.80 for PM 10. A longer gap between sampling and analysis for the transitional samples may induce some loss of volatile ions (nitrate, sulfate and ammonium). Further, the ammonium concentration was estimated assuming its balance with the measured sulfate and nitrate concentrations, i.e., NH 4 + = 0.29 NO SO 4 2 (Chow et al., 2006), and the results were compared with the measured ammonium levels (Fig. S3, SI). It is noted that the measured and estimated ammonium levels were quite close for PM 2.5 in all 3 seasons with the slopes of the regression lines were in the range of and high R 2 of The estimated values were the most close to the measured values for PM 2.5 in the dry season, i.e., the slope = 1.0, which suggested that sulfate and nitrate ammonium were of the main salts presented. In the wet and transitional season the measured were higher than estimated values suggesting that the excess ammonium may be in forms of other compounds but that still needs further studies to confirm. For the coarse fractions, the regression slope varied, i.e., as high as 0.93 for dry season but with a low R 2 (0.43) and as low as 0.53 for the wet season but with a high R 2 (0.91). In general, it is expected that the nitrate and sulfate found in the coarse PM fraction may be in other forms than the ammonium salts. These nitrate and sulfate compounds could be of other origins (than secondary formation). For example, NaNO 3 (aged sea salt) may contribute to PM at the site when the marine air mass arriving because the transport distance of approximately 100 km may facilitate the aging process to transform NaCl into NaNO 3. The element levels in PM 2.5 are summarized in Fig. 3 while those for PM 10 (transitional season) are given in Table S1(a), SI. No element data were available for the coarse fraction samples (PM ). PM 2.5 contained detectable levels of most analyzed elements but many were at low levels, generally below 0.3 µg/m 3 (Fig. 3). Major elements in PM 2.5 included Si, Al, Ca, and Fe. The concentration of S was also significant in the wet season when the data was available, i.e., 2.9 ± 1.7 µg/m 3, that was consistent to the high levels of sulfate particles in the PM. The presence of other elements, such as Si, Fe, Ca and Al, indicated contributions from soil/road dust and construction activities (Hai and Kim Oanh, 2013). The presence of elements such as Si, Fe, Mg, Cr, Mn, and V in the fine PM may also be linked to combustion or industrial activities. Lead (Pb) found in PM 2.5 also suggested a combustion origin, for example coal combustion. However, the levels were quite low, with the seasonal average of 0.1 µg/m 3, and the maximum 24 h level of 0.3 µg/m 3 which is below the Vietnam 24 h national ambient air quality standard of 1.5 µg/m 3. Low levels of Pb were expected as a result of the successful phase-out of leaded gasoline in the country in 2001 (ADB, 2002). Source Contribution Reconstructed Mass The reconstructed mass accounting for contributions from major mass groups is shown in Fig. 4 while detail data is presented in Table S1(b), SI. The average mass explained, in percentage, for PM 2.5 was 83 84% in both dry and wet seasons. The average mass explained for the coarse fraction (PM ) was 64 and 71% for the dry and wet season samples, respectively, which was lower than the values for PM 2.5 because of the lack of elemental composition data. To roughly estimate the mass closure for PM 10, the available elemental data for PM 2.5 was used. The resulting percentage of mass explained for PM 10 was quite close to that for PM 2.5, i.e., 79 ± 14% for dry and 84 ± 14% for the wet season samples, which is explained by the predominant contribution of PM 2.5 to PM 10 mass discussed above. The percentage of mass explained in the transitional season was quite low, 40 ± 11% for PM 2.5 and 36 ± 6.0% for PM 10 (Table S1(b), SI). Note that, to avoid double counting, the K-biomass group was not included in the total mass explained (because K was indirectly included in the crustal group). Likewise, S elemental concentration was not included because sulfate µg/m³ 6 5 Element concentrations in PM 2.5 Dry Trans Wet µg/m³ V Zn Mg Pb Cu Mn Cr Ti Co Ni 0 Al Si Ca Fe V Zn Mg Pb Cu Mn Cr Ti Co Ni Fig. 3. Elemental compositions in PM 2.5 at Tamdao site.

7 Co et al., Aerosol and Air Quality Research, 14: , Fig. 4. Reconstructed mass for different PM sizes at Tamdao (no element data for PM in wet and dry seasons). group was already considered in the mass explained and Ca 2+ was not included because Ca was already accounted for in the crustal group. The major mass groups in PM 2.5 were inorganic particles (sulfate, ammonium, nitrate), OM-biomass, crustal and soot. Collectively, the inorganic particles contributed most significantly, i.e., 15 µg/m 3 in dry and 11 µg/m 3 in the wet season or roughly 30% and 43% of the PM 2.5 mass, respectively. This group was also substantial in the transitional season, 4 µg/m 3, but only contributed about 12% of the PM 2.5 mass, that may be related to some vaporization loss of nitrate particles during a long storage period (1.5 months). The second most significant contribution in the dry season was OM-biomass, about 12 µg/m 3 or 23% PM 2.5 mass, that was higher than the contribution in the transitional (5.1 µg/m 3 or 12%) and wet seasons (2.5 µg/m 3 or 10%). Note that OM-biomass is just an important part of the contribution from biomass burning emission but not its total contribution. The crustal group, mainly indicating the contribution of soil/road dust at the site, was the second most significant in the wet season, 21% of the PM 2.5 mass, and the third significant in the dry season, 19%, but was only 6% of the PM 2.5 mass in the transitional season. The soot group, contributed about 5 8% of the PM 2.5 mass in all seasons, indicated the contribution from incomplete combustion which in turn would be associated with diesel vehicles and also biomass burning (cooking and open burning) in the study area. The BC fraction in diesel exhaust PM could be as high as 68% (Kim Oanh et al., 2010a) as compared to that in the PM of biomass burning smoke, e.g., about 6% for rice straw burning (Kim Oanh et al., 2010b). However, diesel powered vehicles were only occasionally observed on the local roads while biomass burning (for cooking and open burning of crop residue and solid waste) was routine activities by the local community. As discussed above some days with peaks of BC (and PM) were seen in the transitional season which likely indicated a high contribution from tourist diesel buses. The lack of OC data did not allow a rough estimation of OM originated from diesel vehicles hence lowered the overall mass explained percentage for the transitional season samples. In addition, the number of valid samples collected in the transitional season was still too small to produce seasonal representative results. Consistently to the OM-biomass group, the K-biomass group was higher in the dry season (averaged at 1.0 ± 0.8 µg/m 3 ) as compared to the wet season (0.2 ± 0.1 µg/m 3 ) which suggested more contribution from open burning activity in the former when weather was dry. Coal combustion should be a major source of SO x and

8 1924 Co et al., Aerosol and Air Quality Research, 14: , 2014 subsequently sulfate particles in the study area as coal is still a major energy source in Asian countries such as Vietnam and China. In particular, several coal-fired thermal power plants, capacity between 120 to 700 MW, are located in Northern Vietnam within a radius of 150 km from the site, mainly concentrated in Quang Ninh province. There are also industrial activities, mainly in a circle of a radius below 50 km from the sampling and most of that are located to the north of the site. For example, a metallurgical complex or a tin mining and processing industry, both are located in Thai Nguyen province, about 20 km NE to TD site, hence may contribute to the PM pollution through the regional transport. There are also potential transboundary LRT of PM to the site which can be qualitatively analyzed using HYSPLIT backward trajectories of air masses. However, to obtain quantitative contributions from these sources, more measurements are still required to generate sufficient data for receptor modeling studies. For PM 10, due to the lack of elemental composition data for the coarse fraction (PM ) no in depth analysis of the reconstructed mass was carried out in this study. However, because of the small portion of the coarse particles in PM 10 (less than 30% of PM 10 mass, see Table 1) the contributing sources for PM 10 should be similar to those of PM 2.5. Note that the lack of element composition data for the coarse fraction would result in underestimation of contributions from the crustal and the remaining trace elements groups which, in principle, are the major mass groups of PM Overall, the unexplained mass of PM 2.5 and PM 10 may be attributed to the OM originated from other sources (than biomass burning), secondary organic particles, as well as those species which were not analyzed in this study. Backward Trajectory Analysis The 5 day air mass backward HYSPLIT trajectories were computed (Draxler and Rolph, 2003) using the final analysis (FNL) meteorological data which is a product of the GDAS (Global Data Analysis System). The start point was selected at the height of 500 m above the ground level, over the TD coordinates ( N, E). The model vertical velocity option, i.e., to use the vertical velocity field that is included with most meteorological data, was selected when running HYSPLIT. A preliminary analysis was done to check for the differences in the trajectories arriving at the site at the heights of 300 m, 500 m and 1000 m and the results showed that the trajectories of 500 m and 1000 m start heights were basically identical (See Fig. S4, SI). Remarkable differences in the trajectories were only noticed when the start height reduced to 300 m. Therefore, the start height of 500 m was selected for the final analysis because it was close enough to the ground to represent wind in the lower boundary and high enough (above the mixing height) to minimize the friction effects from the Earth's surface. The analysis was done for every PM 2.5 sampling day at the start time of 00:00 UTC (07:00 LST) which was the time that air mass arrived at the site. The HYSPLIT results show that during the wet season sampling period, there were three types of air masses arriving at the site. The first type included air masses originating from the Yellow Sea, to the south of South Korea, and had a continental pathway over Southern China before arriving at the study area following the northeast direction (Fig. S5, SI). It was identified as the northeast continental trajectory pattern (NEC-w; w for wet season) and had the occurrence frequency of 40% during the wet season (Table 4). The second type, equally prevalent in the wet season (40%), had air masses originated from the Pacific Ocean, to the south of the Gulf of Thailand (between Vietnam, Thailand and Malaysia). It had a long marine pathway and arrived at the site following the southeast direction hence was named the southeast marine type 1 (SEM1-w). The third trajectory pattern, the southeast marine type 2 (SEM2-w), had an Pattern name NEC-d/t NEC-w SWC-t SEM1-w SEM1-t SEM2-d/w/t Table 4. HYSPLIT patterns description and occurrence frequency during the monitoring period. Pattern description (see the detail in Fig. S5, SI) Originated from the Northern continental territories, mainly above China, and arrived at the site following NE monsoon. Almost entirely pathway was continental. Originated from the Yellow Sea, had the continental pathway over Southern China and arrived at the study area following the northeast direction Originated from Southwest of Vietnam, passing through Lao and Cambodia before arriving at the site. Originated from the Pacific Ocean, to the south of the Gulf of Thailand, and had entire long marine pathway. Arriving at the site following the southeast direction. Originated in Pacific Ocean, east to Vietnam and had marine pathway before arriving to the site following the southeast direction. Originated mainly from the Eastern China sea, between China, Taiwan and the Philippines and having a long marine pathway before arriving to the side following the southeast direction. Frequency, % Wet (Total: 15) Dry (Total: 30) Transitional (Total: 11)

9 Co et al., Aerosol and Air Quality Research, 14: , occurrence frequency of 20% and also with a long marine pathway, but its trajectory origin was mainly from the Eastern China sea, between China, Taiwan and the Philippines. In the dry season, especially in December (Fig. S5, SI), air masses arrived at the site were mostly originated from the northern territories and entered the study area following the prevalent northeast monsoon direction hence they were classified as NEC-d (d for dry). Only on a few days in December there also observed SEM2-d types of trajectories. In January, these 2 patterns were observed but with a lower frequency of NEC-d and a higher frequency of SEM2-d (Fig. S5, SI) than December. Overall, in the dry season the NEC-d pattern was more prevalent (70%) than SEM2-d (30%). In the transitional season, all 3 patterns observed in the dry and wet seasons were shown (Fig. S5, SI) plus one pattern that had air masses arriving to the site following the southwest direction. This pattern was named as SWC-t as it had a long continental pathway over Indochina before arriving at the site. The occurrence frequency of the patterns was 27% for SWC-t (t for transitional), 37% for NEC-t and 18% for each SEM1-t and SEM2-t pattern (Table 4). Although the NEC pattern was identified in all 3 seasons, its pathways varied and the longest continental pathway (of all HYSPLIT patterns identified in this study, Fig. S5, SI) was recorded for the NEC-d (dry season) hence it was expected to bring more contaminated air to the site. On the opposite, the long marine pathways of SEM1 and SEM2 types would bring less air pollution from distant sources to the monitoring site. To analyze the effects of the HYSPLIT patterns on the measured air pollution levels, the PM 2.5 mass and compositions were calculated for each pattern (Table 5). It is noted that, for the transitional season, due to the small number data points of PM 2.5 composition in a pattern the results were not likely to be statistical inferred. Therefore, our further discussion and the statistical analysis for the differences between patterns, in terms of PM compositions, would mainly focus on the wet and dry season. Table 5 shows that the NEC-d pattern had the highest concentrations of PM 2.5 mass and most composition species, including BC, SO 4 2, NH 4 +, NO 3, K +, Al and Si. As compared to NEC-w (wet season), NEC-d also had comparably high sulfate (both patterns had about 10 µg/m 3 ) and ammonium, i.e., 4.2 ± 2.5 µg/m 3 vs. 4.6 ± 1.2 µg/m 3. However, NEC-d had remarkably higher K + (indicating the biomass smoke contribution) and Si (soil dust and/or construction). The high PM mass and compositions associated with the NEC-d trajectories may be explained by their longest continental pathway of the air masses before arriving at the site. This in turn indicated a high potential of the LRT pollution associated with the NEC-d air mass trajectories. The independent samples t-test (SPSS package) was conducted to compare the PM and composition between NEC-d and NECw. The results (Table S2(a), SI) showed that the levels of mass and all species presented in Table 5 were statistically different between these two patterns at a significance level, i.e., p-value of 0.05, except for sulfate and ammonium which were in fact equally high in both patterns. It is noted that, as compared to NEC-w, NEC-d had longer continental pathways. NEC-d also had continental origin, i.e., above the Northern China continental territories (Figs. S5(b) 5(c), SI) while NEC-w was mainly originated from Yellow Sea (Fig. S5(a), SI). Different air mass types associated with NEC-d and NEC-w plus the seasonal effects (additional emission sources, less wet removal and more stable air in the dry season) would explain the differences between PM pollution between two seasons. This in turn also suggested more potential contributions of LRT pollution to the site when NEC-d was observed. For example, the days with high PM 2.5 levels of 21 and 22 Dec (Fig. 1) also had the NEC-d trajectory pattern (Fig. S5(b), SI). Comparison of PM 2.5 mass and composition between the two patterns observed in the dry season, the NEC-d and the SEM2-d, showed that the SEM2-d (marine type) had lower mass, BC, sulfate and ammonium. SEM2-d had higher average nitrate levels although the range of nitrate was largely overlapped with NEC-d. SEM2-d also had relatively high K +, second only to the NEC-d among all trajectory patterns (Table 5). However, the independent samples t-test results (Table S2(b), SI) did not confirm the statistical significance of the differences between mass or any composition species at the p-value of 0.05 or even 0.10, which may be due to the overlaps of the variable ranges. Thus, both trajectory types in the dry season were associated with high levels of PM mass and composition species which in turn suggested the seasonal effects. For the wet season, the mass was the highest in NEC-w (31 ± 12 µg/m 3 ) which was closely followed by SEM2-w (29 ± 8 µg/m 3 ) and the lowest was for SEM1-w (17 ± 9 µg/m 3 ). The independent samples t-test results showed that the difference between SEM1-w and NEC-w were significant for SO 4 2, NH 4 + and K + at the p-value of 0.05, and for PM 2.5 mass, BC, Cl and Na + at the p-value of 0.10 (Table S2(e), SI). (NO 3 was the only species which was not statistically different between these 2 patterns.) This suggested that NEC-w, which had a continental pathway and originated from Yellow Sea, was associated with significantly higher PM pollution than SEM1-w, hence would confirm the LRT contribution associated with NEC-w. In fact, the days with high PM levels of 5 6 Oct (Fig. 1) had the NEC-w trajectories pattern (Fig. S5(a), SI). There was less difference in PM mass and composition between the two marine air mass types observed in the wet season, SEM1-w and SEM2-w. The independent samples t-test results showed that there was no difference in any species between these two patterns that was statistically different at the p-value of 0.05 (Table S2(c), SI). In fact, the difference in BC was statistically significant at the p- value of 0.06, while the difference in PM 2.5 mass was statistically significant at the p-value of SEM1-w had lower PM pollution, e.g., both days with low PM levels observed in the wet season, Sept (Fig. 1) belonged to the SEM1-w pattern. Between NEC-w and SEM2-w, the independent samples t-test results showed that there was no species which was statistically different at the p-value of 0.05 or even 0.10 (Table S2(d), SI). This result was similar to the comparison result between NEC-d and SEM2-d in the dry season above, which further suggested that the air masses with

10 1926 Co et al., Aerosol and Air Quality Research, 14: , 2014 Table 5. Average (and 1SD) of PM and compositions in different HYSPLIT patterns, µg/m 3. Pattern SEM1 SEM2 NEC SWC Season Wet Trans. Wet Trans. Dry Wet Dry Trans. Trans. Mass 17 ± ± ± ± ± ± ± ± ± 34 BC 1.7 ± ± ± ± ± ± ± ± ± 4.4 Cl 0.05 ± ± ± ± ± ± ± ± ± 0.01 NO ± ± ± ± ± ± ± ± ± 0.6 SO ± ± ± ± ± ± ± ± ± 1.3 Na ± ± ± ± ± ± ± ± ± 0.02 NH ± ± ± ± ± ± ± ± ± 0.6 K ± ± ± ± ± ± ± ± ± 0.4 Mg ± ± ± ± ± ± ± ± ± 0.03 Ca ± ± ± ± ± ± ± ± ± 0.5 Al 0.28 ± ± ± ± ± ± ± ± 0 Si 0.85 ± ± ± ± ± ± ± ± 0 Ti 0.07 ± ± ± ± ± ± ± ± 0 V NA ± 0 NA ± ± 0.1 NA 0.18 ± ± ± 0 Fe 0.25 ± ± ± ± ± ± ± ± 0 Zn 0.07 ± ± ± ± ± ± ± ± 0 Pb 0.08 ± ± ± ± ± ± ± ± 0 Note: NA - not analyzed; some minor elements are not presented in the table.

11 Co et al., Aerosol and Air Quality Research, 14: , trajectories along the coastal line of the Southern China may also be associated with the LRT pollution to the site in both dry and wet seasons. Within the transitional season, the SWC-t which had a continental pathway also showed the highest PM and BC as compared to other patterns. Note that the SEM1-t also had the second highest PM and BC and its pathway and origin were not the same as of SEM1-w (wet season). SEM1-t had the trajectories originated from the Pacific Ocean, to the east of Vietnam, and had a shorter pathway (indicating slow moving air masses) as compared to SEM1-w. The day with the highest level of PM 2.5 in the transitional season, 11 Apr (Fig. 1), was associated with SWC-t that had a continental pathway before arriving at the site. CONCLUSIONS The 24 h PM levels at this mountainous rural site were higher during the dry season, followed by the transitional season and the lowest in the wet season. Day to day fluctuations of the PM levels within a season were also significant. The seasonal average PM 2.5 and PM 10 in dry, transitional and wet seasons were 51 ± 29 and 67 ± 32 µg/m 3, 33 ± 21 and 44 ± 22 µg/m 3, and 25 ± 12 and 33 ± 11 µg/m 3, respectively. Fine fraction (PM 2.5 ) contributed the majority, above 70%, of the PM 10 mass. There existed strong linear correlations between PM 2.5 and PM 10 with the R 2 ranged between , which indicated that the variations in PM 10 were largely determined by the variations of PM 2.5 and that they were originated from similar sources/processes. On average, the seasonal levels measured at the site were comparable to those reported for an urban site in Hanoi but were lower when compared to the averaged across different characteristic sites (traffic, industrial, commercial and mix sites) in the city. The major compositions of PM 2.5 varied with seasons and mainly included secondary inorganic particles (12 43% of mass), OM-biomass (10 23%), crustal elements (6 21%) and BC (5 8%). The secondary inorganic particles may be originated from the precursor emission of both local and distant emission sources. The crustal group suggested the contribution from soil/road dust and construction activities which are mainly local or regional. The BC content in PM suggested contributions from incomplete combustion, including diesel powered vehicles operated in local roads, biomass burning for cooking and open burning activities, both from local and distant sources. In addition, considerable levels of potassium and subsequently the K-biomass and OMbiomass groups in the dry season samples indicated a higher contribution from biomass burning emission. Overall, the total PM 2.5 mass explained percentage in the wet and dry seasons was quite similar, i.e., of 83 84%. Lack of the element data for the coarse fraction (PM ) resulted in its lower mass explained percentage (64 71%) than PM 2.5 in the dry and wet seasons. Further studies should analyze for OC content in the PM samples to estimate the OM mass originated from other combustion sources (than biomass) and secondary organic particles which would improve the mass closure. The continental pathway of air masses arriving at the monitoring site in each season was associated with higher PM levels in the season. The northeast continental backward trajectory pattern observed in the dry season, with its longest continental pathway and continental origin, showed the highest levels of PM 2.5 mass and composition species among all patterns identified for three seasons. Comparison of PM pollution between the northeast continental air mass types, observed in the dry season, with that observed in the wet season showed that they were statistically different which suggested potential effects of seasons and LRT pollution. The NEC and SEM2 air mass types identified for the dry season and wet season, respectively, all had high sulfate and ammonium levels. The pathway of SEM2, i.e., moving along the Southern China coastal line, before arrive to the site would also induce a high potential of LRT pollution similar to the NEC trajectory pattern. Although SEM2 had lower levels of PM pollution as compared to the NEC in each wet and dry season, respectively, the difference was not statistically significant. More monitoring activities are still required, especially for the transitional season, to produce the seasonal representative data at the site. ACKNOWLEDGMENT The authors acknowledge partial funding of this research by Swedish International Development Agency (SIDA) funding through the AIRPET project activities in Vietnam. The funding provided by the Vietnam National Foundation for Science & Technology Development (NAFOSTED, ) for the sampling and analysis of samples during the transitional period is greatly acknowledged. Furthermore, we acknowledge the contribution of the researchers and students who involved in the project activities, especially Mr. Nguyen Phan Dong and Ms. Do Thanh Canh at AIT, Ms. Dao Thi Hong Van and Mr. Dao Van Huy at VNU-HUS, Mr. Nguyen Duy Hung, Mr. Do Cong Tung and Mr. Nguyen Duc Quang at HUST. The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and/or READY website ( used in this publication. 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13 Supplementary information Levels and Composition of Ambient Particulate Matter at a Mountainous Rural Site in Northern Vietnam Hoang Xuan Co a, Nghiem Trung Dung b, Nguyen Thi Kim Oanh c, Nguyen Thanh Hang c, Nguyen Hong Phuc c and Hoang Anh Le a Fig. S1. Geographical location of the sampling site in Tamdao, Vinh Phuc

14 Anion, µeq/m a) Ion balance, PM 2.5, dry season y = x R² = Cation, µeq/m 3 Anion, µeq/m b) Ion balance, PM , dry season y = x R² = Cation, µeq/m 3 Anion, µeq/m c) Ion balance for PM 2.5, wet season y = x R² = Cation, µeq/m 3 Anion, µeq/m d) Ion balance, PM , wet season y = x R² = Cation, µeq/m 3 Anion, µeq/m 3 e) Ion balance, PM 2.5 transitional season y = x R² = Anion, µeq/m f) Ion balance, PM 10, transitional season y = x R² = Cation, µeq/m Cation, µeq/m 3 Fig. S2. Ion balance for different PM size fractions, Tamdao

15 10.0 a) Measured vs. estimated NH 4 + in PM 2.5, dry season 3.5 b) Measured vs. estimated NH 4+, in coarse fraction, dry season Estimated, µg/m y = x R² = Estimated, µg/m y = x R² = Measured, µg/m Measured, µg/m c) Measured vs. estimated NH 4+, in PM 2.5, wet season 2.5 d) Measured vs estimated NH 4+, in coarse fraction, wet season Estimated, µg/m³ y = x R² = Estimated, µg/m³ y = x R² = Measured, µg/m³ Measured, µg/m³ Estimated, µg/m³ e) Measured vs. estimated NH 4+, in PM 2.5, transitional season y = x R² = Estimated, µg/m³ f) Measured vs estimated NH 4+, in PM 10, transitional season y = x R² = Measured, µg/m³ Measured, µg/m³ Fig. S3. Measured vs. estimated ammonium levels in different PM fractions

16 (a1) Wet season (22 Sept 2005) (a2) Wet season (4 Oct 2005) (b1) Dry season ( 20 Dec 2005) (b2) Dry season (10 Jan 2006) (c1) Transitional season (5 Apr 2010) (c2) Transitional season ( 16 April) 1000m 500m 300m Fig. S4. HYSPLIT 5 day back trajectories showing the air mass arriving at Tamdao site at different heights above the ground

17 NEC-w SEM2-w NEC-d SEM1-w SEM2-d a) Wet season, 2005 b) Dry season, December 2005 NEC-d NEC-t SEM2-t SWC-t SEM2-d SEM1-t c) Dry season, January 2006 d) Transitional season, 2010 Fig. S5. HYSPLIT 5 day back trajectories showing the air mass arriving at Tamdao site in different seasons