quang, tran ngoc, thi hue, nguyen,thai, phong,mazaheri ...41 because of their potential to have...

This may be the author’s version of a work that was submitted/acceptedfor publication in the following source:

Quang, Tran Ngoc, Thi Hue, Nguyen, Thai, Phong, Mazaheri, Mandana, &Morawska, Lidia(2017)Exploratory assessment of indoor and outdoor particle number concentra-tions in Hanoi households.Science of the Total Environment, 599 - 600, pp. 284-290.

This file was downloaded from: https://eprints.qut.edu.au/107861/

c© Consult author(s) regarding copyright matters

This work is covered by copyright. Unless the document is being made available under aCreative Commons Licence, you must assume that re-use is limited to personal use andthat permission from the copyright owner must be obtained for all other uses. If the docu-ment is available under a Creative Commons License (or other specified license) then referto the Licence for details of permitted re-use. It is a condition of access that users recog-nise and abide by the legal requirements associated with these rights. If you believe thatthis work infringes copyright please provide details by email to [email protected]

License: Creative Commons: Attribution-Noncommercial-No DerivativeWorks 2.5

Notice: Please note that this document may not be the Version of Record(i.e. published version) of the work. Author manuscript versions (as Sub-mitted for peer review or as Accepted for publication after peer review) canbe identified by an absence of publisher branding and/or typeset appear-ance. If there is any doubt, please refer to the published source.

https://doi.org/10.1016/j.scitotenv.2017.04.154

https://eprints.qut.edu.au/view/person/Thai,_Phong.htmlhttps://eprints.qut.edu.au/view/person/Mazaheri,_Mandana.htmlhttps://eprints.qut.edu.au/view/person/Morawska,_Lidia.htmlhttps://eprints.qut.edu.au/107861/https://doi.org/10.1016/j.scitotenv.2017.04.154

1

Exploratory Assessment of Indoor and Outdoor Particle Number 1

Concentrations in Hanoi Households 2

Tran Ngoc Quanga,1, Nguyen Thi Huea, Phong Thaib, Mandana Mazaherib, and Lidia Morawskab 3

aFaculty of Environmental Engineering, National University of Civil Engineering, Hanoi, Vietnam 4

bInternational Laboratory for Air Quality and Health, Institute of Health and Biomedical 5

Innovation, Queensland University of Technology, Brisbane, QLD 4001, Australia 6

7 Abstract 8

No studies have been conducted in Vietnam to understand the levels of atmospheric ultrafine 9

particles, despite having adverse health effects. Information about indoor air quality in Vietnam is 10

also limited. Hence we aimed to conduct the first assessment of ultrafine particle concentrations in 11

terms of particle number (PN) in Hanoi, by simultaneously measuring indoor and outdoor PN 12

concentrations from six households at different locations across the city in January, 2016. We also 13

acquired PM2.5 data for this monitoring period from an air quality monitoring station located at the 14

US Embassy in Hanoi, to compare the general trends between PN and PM2.5 concentrations. The 15

mean daily indoor and outdoor PN concentrations for the monitoring period were 1.9 x 104 p/cm3 16

and 3.3 x 104 p/cm3, respectively, with an increase during rush hour traffic. It was concluded that 17

traffic was the main contributor to outdoor PN concentrations, with agricultural burning having a 18

small influence at one study location. The mean ratio of indoor to outdoor PN concentrations for 19

all six sites was 0.66 ± 0.26, which points to outdoor air as the main driver of indoor PN 20

concentrations, rather than indoor sources. These PN concentrations and I/O ratios are similar to 21

those reported for a number of cities in developed countries. However, in contrast to PN, ambient 22

mean PM2.5 concentrations in Hanoi (60 – 70 μg/m3) were significantly higher than those typically 23

recorded in developed countries. These findings demonstrate that urban particle mass (PM2.5) 24

concentrations are not indicative of the PN concentrations, which can be explained by different 25

1Corresponding author at: Faculty of Environmental Engineering, National University of Civil Engineering, Hanoi, Vietnam. Tel.: +844 3869 7035; Fax: +844 3869 1830. E‐mail address: [email protected] (TN. Quang).

2

sources contributing to PN and PM, and that direct measurements of PN are necessary to provide 26

information about population exposure to ultrafine particles and for management of air quality. 27

28

Keywords: particle number concentration; ultrafine particles; indoor emission sources; traffic 29

emissions; air quality; 30

Highlights 31

The first study to monitor both indoor and outdoor PN concentrations in Vietnam. 32

Indoor level ranged from 1.3 – 3.0 x 104 p/cm3 and outdoor level from 2.1 – 4.7 x 104 33

p/cm3. 34

Outdoor PN concentrations were influenced by vehicle emissions and rainfalls. 35

Indoor PN concentrations were contributed by both indoor and outdoor sources. 36

PM2.5 concentrations were not indicative of PN concentrations. 37

38

1. Introduction 39

There is an growing interest in understanding concentrations of ultrafine particles (< 0.1 µm), 40

because of their potential to have adverse health effects on humans (Franck et al., 2011; HEI, 41

2013; Lanzinger et al., 2016). Ultrafine particles (UFPs) can be emitted from biomass burning 42

(Reid et al., 2005) and photo-chemical form (Pey et al., 2009). However, in urban areas, the source 43

of ultrafine particle is mainly attributed to vehicle emissions (Perez et al., 2010; Pey et al., 2008; 44

Quang et al., 2012). Outdoor UFPs contribute to the indoor concentration, as they are brought 45

inside the buildings through ventilation or via penetration through the building envelopes. At the 46

same time, indoor activities, such as cooking and burning of candles can increase indoor UFP 47

concentrations (Abt et al., 2000; Bekö et al., 2014; He et al., 2004; Meier et al., 2015). Increased 48

indoor particle levels directly increase exposure to occupants of the building to UFPs. 49

50

3

UFPs are measured in terms of particle number (PN) concentration. It should be noted, however, 51

that most of the instruments for measuring particle number concentrations cover a wide range of 52

particle sizes, from ultrafine range to much larger particles depending on the instrument 53

specification. Since the majority of the particles in terms of number are in the ultrafine size range, 54

measurements of PN are considered a good representation of UFPs. In this study, we used Philips 55

Aerasense NanoTracers to measure PN in the size range of 10 up to 300 nm. Nevertheless, for the 56

sake of accuracy, in this manuscript we will refer to PN, rather than UFPs. 57

To our knowledge, there have been no studies reporting PN concentrations measured either indoor 58

or outdoor in Vietnam including in large cities where combustion sources are expected to 59

contribute significantly to their PN concentration level. Meanwhile, several studies have reported 60

mass concentrations of PM10 and PM2.5 in Hanoi, the capital of Vietnam, with >7 million 61

inhabitants (Cohen et al., 2010; Hien et al., 2002; Kim Oanh et al., 2006; Saksena et al., 2008) as 62

well as their impact on human health (Luong et al., 2017). 63

To provide at least a preliminary assessment of urban PN concentrations in Vietnam, this pilot 64

study aimed to: (1) quantify the indoor and outdoor PN concentration at several residential houses 65

in Hanoi; (2) investigate factors influencing household indoor and outdoor PN concentrations; and 66

(3) assess the association of daily outdoor PN concentrations with outdoor PM2.5 concentrations in 67

Hanoi. 68

69

2. Methods 70

2.1. Study area 71

This study was conducted in 2016 in Hanoi, which is a growing city in the North of Vietnam 72

(21.02oN, 105,85oE). It has 30 urban and suburban districts covering an area of 3345 km2, and has 73

a population of 7.2 million (Statistic, 2015). 74

The city has the tropical monsoon climate, with hot and rainy summers (May to August) and 75

winters are cold and dry (November to January). Located near the tropics, Hanoi receives 76

4

abundant solar radiation (average of 122.8 kcal/cm2) and has a relatively high annual average 77

temperature (23.6ºC). The average annual relative humidity is 79% and the average annual rainfall 78

is 1.800 mm (Statistic, 2015). 79

Motorbikes are the main mode of transport for the city commuters in Hanoi, with passenger cars 80

becoming more popular in recent years. In the first eight months of 2015, the capital saw 183,000 81

newly-registered vehicles (>39,000 cars and 143,000 motorcycles), bringing the total number of 82

resisted vehicles to 5.5 million (about 535,000 cars and 4.9 million motorcycles) (Times, 2015). 83

The passenger car fleet in Hanoi still includes many old and ill-maintained vehicles, and 84

motorcycles emissions are not controlled in Vietnam (Times, 2015). Hence, traffic emissions are 85

considered the main cause of air pollution in Hanoi. 86

87 Figure 1: The location of the monitoring sites in Hanoi, Vietnam. 88

89

2.2. Study design 90

Six urban residential houses were included in this study, covering different house styles and 91

locations in Hanoi. They were assigned as sites S1 to S6 (Figures 1). S1 - S4 are semi-detached 92

5

houses. S5 and S6 are apartments in high-rise buildings. Information about the monitoring sites 93

and the periods when the measurements were conducted at each site are presented in Table 1. 94

S1 and S2 are two neighbouring four-storey houses, located in a new urban area in southern Hanoi. 95

They are about 120m away from the main city ring-road with a daily traffic volume on the nearest 96

road of about 83000, consisting of 52000 motorcycles (TEDI, 2007). S3 and S4 are four storey 97

houses located within the city centre. S3 is about 75m from a busy road with daily motorbike and 98

car traffic volumes of 31000 and 11000, respectively. S4 is close to a new main road (about 50m), 99

connecting the city centre to the Hanoi International Airport, with estimated daily traffic volume of 100

55000, dominated by cars (TEDI, 2007). 101

Table 1: Information of the monitoring sites and the respective measurement periods in January 102

2016. 103

Site S1 S2 S3 S4 S5 S6

Monitoring period 5-7 Jan 7-9 Jan 16-18 Jan 18-20 Jan 9-13 Jan 13-16 Jan

Duration (h) 64 48 94 63 44 50

Weather Cloudy Cloudy Light

shower/cloudy Cloudy Clear

sky/Cloudy Cloudy/Light

shower

House type Semi-detached 4-storey house Apartment in high-rise

building

Outdoor position Level 4 Level 4 Level 4 Level 4 Level 8 Level 12

Indoor position Level 2 Level 1-3 Level 1 Level 1 Level 8 Level 12

Distance to the nearest road (m) 120 120 75 50 100

Separated by a similar building

Traffic volume (vehicle/d) 83000 83000 42000 55000 34000 25000

104

S5 is located in an apartment building of southern Hanoi. The building is close to the National 105

Express Way No1B, with a traffic volume (> 4 wheels) of about 34000 per day (TEDI, 2007). In 106

the vicinity of this site farmers on occasionally burn crop residue. The apartment building where 107

S6 is located is in south-western Hanoi. This building is separated from a street by an identical 108

6

building. The street has a total daily traffic volume of about 25000, of which about 8000 are cars 109

(TEDI, 2007). 110

At each site, simultaneous indoor and outdoor measurements of PN levels were conducted using 111

two NT instruments (as described in Section 2.3) for 43-90 hours (Table 1). At the same time, 112

diary entries were completed by the occupants to record indoor activities that took place during the 113

monitoring campaign. Due to security reason, all outdoor measurements at sites S1-4 were carried 114

out at level 4 while indoor measurements were carried out at lower level in living rooms where 115

most activities took place. At site S2, there was a short period of PN measurement in an 116

unoccupied bedroom with tightly closed doors and windows to evaluate the impact of air 117

exchange/infiltration on the measured PN concentration. At S5 and S6 the measurements were 118

conducted on the eighth and the twelfth floor, respectively. 119

120

2.3. Instrumentation and quality assurance 121

Two Philips Aerasense NanoTracers (NTs) were used to measure PN concentrations. NT measures 122

PN concentrations up to 1 x 106 cm-3 in the size range of 10 to 300 nm. The NTs were operated in 123

the Advanced mode, where PN concentrations are measured at a fixed sampling interval of 16 s. 124

Details of design and operational procedures for the NT devices are available elsewhere (Marra et 125

al., 2010). 126

The NT’s time stamp was synchronised to the local time using the Nano Reporter software prior to 127

each measurement. The NTs were tested at the International Laboratory for Air Quality and 128

Health, Queensland University of Technology, Brisbane, Australia prior to their shipment to 129

Hanoi, and correction factors were derived for each NT according to the procedure described by 130

(Mazaheri et al., 2014). Briefly, the two NTs (n = 1, 2) were run side by side with a TSI model 131

3787 condensation particle counter (CPC) for 24 h and all the readings were analysed to derive the 132

correction factors. 133

134

7

2.4. Meteorological and PM2.5 data 135

Meteorological data (temperature, relative humidity, wind components and rainfall) for the 136

monitoring period were acquired from the meteorological station of the Hanoi International 137

airport, which is located 20 km from the city centre (Figure 1). 138

Average hourly PM2.5 concentrations were obtained from an air quality monitoring station located 139

at the US Embassy in Hanoi, about 5 - 7 km from the study sites (Figure 1). 140

141

2.5. Data analysis 142

Data from the NTs was downloaded after each measurement and multiplied by the corresponding 143

NT correction factors. Statistical analyses (t-test and ANOVA test) were performed with SPSS 144

version 20 (SPSS Inc.), with a 5% level of significance (p < 0.05). 145

146

3. Results and Discussion 147

3.1. PN concentrations at the investigated sites within Hanoi 148

Data on PN concentration was successfully collected at all the sites, without interruptions or loss 149

of data. Box plots of outdoor and indoor PN concentrations at each site are presented in Figure 2. 150

The box plots represent the maximum, minimum, 75th percentile, 25th percentile, and median 151

values. Complete data on the indoor and outdoor PN concentrations and the concentration ratios at 152

each site are presented in Tables S1-2. Time-series of PN concentrations at S5 is presented as an 153

example in Figure 3, and for the other sites in Figure S1. 154

8

155 Figure 2: Summary of the PN concentration during the monitoring period at sites S1-6. (Box plots 156

denote minimum values, 1st quartile, median, 3rd quartile and maximum values.) 157

158

9

159 Figure 3: Time-series of indoor and outdoor PN number concentrations and their ratio (I/O) at Site 160

5 161

162

Outdoor concentrations 163

Overall, mean outdoor PN concentrations at the six sites of Hanoi ranged from 2.1 – 4.7 x 104 164

p/cm3. These values are comparable to those measured in the urban atmosphere of Beijing, China, 165

with mean PN concentration of 3.3 x 104 p/cm3 (Wu et al., 2008), and average ambient 166

concentration of 3.8 x 104 p/cm3 (Apte et al., 2011). The values are, relatively high compared to 167

the concentrations of PN of approximately 1.0 x 104 p/cm3measured at urban locations of 168

Brisbane, Australia (Quang et al., 2012), where population and traffic volumes are low compared 169

to most cities. 170

The overall mean outdoor PN concentration for all the sites was 3.2 x 104 p/cm3, which was 171

similar to the average PN concentrations of nearly 40 cities worldwide (3.5 ± 2.4 x 104 p/cm3), as 172

reported by (Kumar et al., 2014). It should be noted that the above worldwide average excluded 173

values from the three very highly polluted cities of Delhi, Shanghai and Hsinchu. 174

Vehicle emissions are considered the main source of PN in urban areas (Kumar et al., 2014; Liu et 175

al., 2014). Therefore, as expected, it was observed that at all the monitoring sites the outdoor PN 176

concentration levels during rush-hour periods were significantly higher than during other periods 177

(p < 0.05), with the mean difference ranging from 12.4% (Site S6) to 49.3% (Site S5). 178

10

Mean outdoor concentration of PN at S1 was significantly higher than the mean values at the other 179

sites (p < 0.01), while the values at S2, S4 and S5 were similar (p = 0.06). In contrast, the levels at 180

S3 and S6 were significantly lower than at the other four sites (p < 0.01). The highest outdoor 181

concentrations at S1 could be explained by a strong influence of vehicle emissions from a busy 182

street with traffic light intersection; it has been reported that under such stop and start conditions 183

PN concentrations are the highest, and several times exceed the concentrations under traffic free–184

flowing conditions (Goel and Kumar, 2015). While S2 is next to S1, it is positioned at leeward 185

side of the building with regard to the street (Fig. S1a) and therefore is less affected by emissions 186

from the traffic. A similar phenomenon was reported by Quang et al. (2012) in their study in 187

Brisbane, Australia. 188

The lowest levels of PN concentrations at S3 and S6 could be explained by the rainy weather 189

during the measurement. Additionally, both S3 and S6 are located near streets with lighter traffic 190

volumes compared to other sites. 191

The degree of variation in outdoor PN concentrations during the measurement period at S1 and S5 192

(evaluated by their standard deviations) were higher than at other sites (Table S1). This can be 193

explained by the fact that both these sites are located close to intermittent additional sources of PN. 194

In case of S1, it is the nearby traffic intersection which is an important emission source, especially 195

during rush hours as described above. At S5, the concentrations were influenced not only by 196

vehicle emissions but also by burning of garden residues, which was observed in the vicinity of 197

this site during the monitoring period, with visible smoke plumes. The smaller variations in PN 198

concentrations at S3, S4 and S6 could be explained by the larger distance from the monitoring 199

points to the nearby streets. The most stable PN concentrations at S6 can be attributed to the 200

lowest, among all the sites, traffic volume on the nearby street, as shown on Table 1. 201

Beside the influence of emission sources, outdoor concentrations of PN in Hanoi were affected by 202

weather conditions. During the monitoring period at site S3, there were rainfall events that made 203

11

outdoor PN concentrations significantly lower than those during the periods of dry weather (p < 204

0.05). Rainfalls also took place during monitoring at site S6. 205

206

Indoor concentrations 207

Mean indoor PN concentrations at the six sites ranged from 1.5 to 3.0 x 104 p/cm3. These values 208

are similar to three high rise apartments in Beijing, China, which ranged from 1.3 to 2.9 x 104 209

p/cm3 (Mullen et al., 2011). The values are comparable to the mean value of 1.8 x 104 p/cm3 210

measured inside residential houses in Brisbane, Australia (Morawska et al., 2003). They are also 211

comparable to concentrations reported for residential houses in California (Bhangar et al., 2011) 212

and in Denmark (Bekö et al., 2013), but higher than the mean value of 0.7 x 104 p/cm3 calculated 213

by Morawska et al. (2013). 214

Unsurprisingly, indoor activities contributed to the variation in PN concentrations indoor, similarly 215

to what was reported by He et al. (2004). According to the diary entries, rice frying, re-heating 216

food with a microwave, and bread toasting with gas oven, resulted in indoor PN concentrations 217

and I/O ratios peaking at S3 and S4 (Fig. S2c,d). Cooking activities over lunch times also 218

contributed to the increase in indoor particle concentration, as seen at S4. Two particular events of 219

elevated indoor PN concentrations were observed and attributed to the use of a microwave. Firstly, 220

PN concentration sharply rose up to 9.1 x 104 p/cm3 at S2 during roasting of peanuts in a 221

microwave on 8 January. Secondly, at S5, at 1:30 am on 13 January, indoor PN concentration in 222

the dining room suddenly increased. While not recorded in the diary, the house owner recalled that 223

he got up at that time to watch a European Champion League football match and cooked instant 224

noodle in the microwave. These two events confirmed microwave cooking as a source of indoor 225

PN, which was also previously reported by Zhang et al. (2014). As microwave cooking is a 226

convenient way of cooking/warming food, this source is likely to become more important in 227

affecting indoor exposure to PN, in addition to other sources reported by He et al. (2004) such as 228

frying, toasting, and stove use, which could increase the indoor PN concentration several fold. 229

12

230

Indoor to outdoor ratios of PN concentrations 231

24-h mean outdoor PN concentrations were significantly higher than the respective indoor mean 232

concentrations for all six sites (p < 0.01), i.e. I/O ratios of the concentrations for all the sites were 233

significantly lower than 1 (p < 0.01) (Figure 4). The mean ratio of indoor to outdoor PN 234

concentration for all six sites was 0.71 ± 0.23 (mean ± SD). This value is comparable to the I/O 235

ratios of PN concentrations for naturally ventilated buildings as summarised by Morawska and 236

Salthammer (2003). 237

238

Figure 4: Indoor to outdoor PN concentration ratios for the six monitoring sites. (Box plots denote 239 minimum values, 1st quartile, median, 3rd quartile and maximum values.) 240

241

The similarity in the I/O ratios between our study and those reported previously (Morawska and 242

Salthammer, 2003) is not unexpected, considering the similarity in the building ventilation (natural 243

ventilation), similarity in the indoor sources (cooking using modern methods), and similarity in the 244

outdoor sore contribution (outdoor traffic emissions). Under such a scenario, the activities of the 245

occupants are likely to have a strong influence, particularly on the instantaneous I/O ratios. For 246

example, I/O ratios at S5 were significantly higher than at other sites; while the ratios at the S2, 247

significantly lower (p < 0.05). At S5, the indoor NT instrument was placed at the living room on 248

13

the top of fishing tank, where the doors were usually opened for natural ventilation, although it 249

was winter time. At S2, the indoor NT was placed in a tight, un-occupied bedroom, which resulted 250

in I/O ratios of PN concentrations of 0.31 ± 0.08, significantly lower than at other locations. This 251

demonstrated that tighter room or low infiltration/ventilation can remarkably reduce contribution 252

of outdoor particles to the indoor concentrations. 253

254

3.2 Ambient PM2.5 concentrations in Hanoi and relation to PN concentrations 255

A summary of the descriptive statistics for the ambient PM2.5 concentrations in Hanoi 256

corresponding to the monitoring periods at each sites is presented in Table 2. The mean 257

concentration of PM2.5 for the entire measurement period was 66 ± 22 μg/m3 (Mean ± SD), which 258

is similar to the annual mean concentration of 67 ± 33 μg/m3 reported in Hanoi by Luong et al. 259

(2017). The value is higher than PM2.5 concentrations in Bangkok and Manila (18 – 50 and 43 – 260

44 μg/m3, respectively), but lower in Bejing (104 – 168 μg/m3) (Kim Oanh et al., 2006). 261

262

Table 2: Statistic description of PM2.5 ambient concentrations (μg/m3) corresponding to the 263

monitoring periods at different households 264 265

Time period 5-7 Jan 2016

7-9 Jan 2016

9-13 Jan 2016

13-16 Jan 2016

16-18 Jan 2016

18-20 Jan 2016

5-20 Jan 2016

Mean 78.5 64.8 57.2 52.7 51.6 98.1 65.9 SD 9.5 7.3 13.2 18.3 4.9 29.2 22.3 Max 93.2 77.5 82.1 87.6 62.4 144.7 145.9 Min 64.3 52.7 42.1 29.0 46.0 59.5 29.0

266 267 Time-series of PM2.5 and PN concentrations in Hanoi during the monitoring period are presented 268

in Figure 5. It can be seen that at most times PM2.5 and PN peaks in concentration do not coincide, 269

which indicates that PM and PN have different sources, and in particular that there are other than 270

traffic-related emission sources that contribute to the level of PM2.5 in Hanoi. This was further 271

supported by correlation analysis, which demonstrated lack of correlation between PN and PM2.5 272

(R2 < 0.1). Regarding the levels of UFPs represented by the PN concentrations, the clear difference 273

14

between rush and off-peak hours suggested that traffic emissions in Hanoi is an important source 274

of UFPs in the outdoor environment. 275

15

276

277

278

Figure 5: Time-series concentrations of PM2.5 and PN during the monitoring period of this study. 279

16

It is important to note that although the mean ambient PM2.5 concentrations in Hanoi (60 – 70 280

μg/m3) was higher than those reported for urban areas of developed countries (PM2.5 concentrations 281

from 8.4 – 26.2 μg/m3) such as the United States, Spain or Switzerland (ARB, 2016; FOEN, 2013; 282

Querol et al., 2008). However, the levels of outdoor PN concentrations were similar to those 283

measured in the countries mentioned above, with the mean PN from 0.6 - 3 x 104 p/cm3 as reported 284

by Bhangar et al. (2011), Meier et al. (2015), and Reche et al. (2014). 285

This finding confirms that PM concentrations are not indicative of the PN concentrations in the 286

same area, as suggested by Mullen et al. (2011). Direct measurement of PN required to provide 287

information about population exposure to UFPs. 288

289

4. Conclusions 290

For the first time, concentrations of PN, both indoor and outdoor, were measured at different 291

households in Hanoi. Overall, the daily mean concentrations of outdoor PN (3.2 x 104 p/cm3) were 292

significantly higher than indoor PN (1.8 x 104 p/cm3). Our results also suggested that the indoor PN 293

concentrations were influenced by the outdoor PN concentrations due to the general practice of 294

opening windows for natural ventilation. The levels of both outdoor and indoor PN concentrations 295

measured in this study were not higher than those reported in some cities in developed countries, 296

suggesting a relatively lower risk from UFP in Hanoi compared to the risk of PM2.5, whose daily 297

concentration is consistently higher than the WHO recommended level of 25 μg/m3. Until now, the 298

epidemiological data only supported a suggestive causal relationship between exposure to UFPs and 299

adverse health effects (Baldauf et al., 2016). Association between short-term exposure to UFPs and 300

mortality as well as hospital admission were found in the newest European study (Lanzinger et al., 301

2016; Stafoggia et al., 2017) but the significance was lost when the impact of other air pollutants 302

such as PM2.5 was included. Therefore, it is recommended to continue the monitoring of UFPs and 303

related pollutants (e.g., PM2.5, CO) to better characterize air quality trends and potential exposures 304

(Baldauf et al., 2016), and consequently to separate the effects of UFPs from those of PM2.5. It is 305

17

noted that the findings of this exploratory study were based on short term monitoring and should be 306

extended to confirm all the hypotheses. 307

308

Acknowledgments 309

Phong Thai is funded by a QUT Vice Chancellor Research Fellowship. Mandana Mazaheri was 310

supported by a Collaborative Research Development Grant, funded by the Institute of Health and 311

Biomedical Innovation (IHBI) at QUT. 312

313

References 314 315 Abt E, Suh HH, Allen G, Koutrakis P. Characterization of indoor particle sources: A study conducted in the 316

metropolitan Boston area. Environmental Health Science Perspectives 2000; 108: 35‐44. 317 Apte JS, Kirchstetter TW, Reich AH, Deshpande SJ, Kaushik G, Chel A, et al. Concentrations of fine, ultrafine, 318

and black carbon particles in auto‐rickshaws in New Delhi, India. Atmospheric Environment 2011; 319 45: 4470‐4480. 320

ARB (Air Resources Board). Air Quality Trend Summaries. 321 https://www.arb.ca.gov/adam/trends/trends1.php (accessed on 15 January, 2016). 322

Baldauf RW, Devlin RB, Gehr P, Giannelli R, Hassett‐Sipple B, Jung H, et al. Ultrafine Particle Metrics and 323 Research Considerations: Review of the 2015 UFP Workshop. International Journal of 324 Environmental Research and Public Health 2016; 13: 1054. 325

Bekö G, Kjeldsen BU, Olsen Y, Wierzbicka A, Karottki DG, Toftum J, et al. Ultrafine particles in 60 danish 326 homes: Measurements in the homes and personal monitoring. Indoor Air 2014 ‐ 13th International 327 Conference on Indoor Air Quality and Climate, 2014, pp. 160‐162. 328

Bekö G, Weschler CJ, Wierzbicka A, Karottki DG, Toftum J, Loft S, et al. Ultrafine particles: Exposure and 329 source apportionment in 56 Danish homes. Environmental Science and Technology 2013; 47: 330 10240‐10248. 331

Bhangar S, Mullen NA, Hering SV, Kreisberg NM, Nazaroff WW. Ultrafine particle concentrations and 332 exposures in seven residences in northern California. Indoor Air 2011; 21: 132‐144. 333

Cohen DD, Crawford J, Stelcer E, Bac VT. Characterisation and source apportionment of fine particulate 334 sources at Hanoi from 2001 to 2008. Atmospheric Environment 2010; 44: 320‐328. 335

FOEN 2013: PM10 and PM2.5 ambient concentrations in Switzerland. Modelling results for 2005, 2010 and 336 2020. Federal Office for the Environment, Bern. Environmental studies no. 1304: 83 pp. 337

Franck U, Odeh S, Wiedensohler A, Wehner B, Herbarth O. The effect of particle size on cardiovascular 338 disorders ‐ The smaller the worse. Science of The Total Environment 2011; 409: 4217‐4221. 339

Goel A, Kumar P. Characterisation of nanoparticle emissions and exposure at traffic intersections through 340 fast–response mobile and sequential measurements. Atmospheric Environment 2015; 107: 374‐341 390. 342

He CR, Morawska LD, Hitchins J, Gilbert D. Contribution from indoor sources to particle number and mass 343 concentrations in residential houses. Atmospheric Environment 2004; 38: 3405‐3415. 344

HEI. HEI review panel on ultrafine particles. Understanding the health effects of ambient ultrafine particles. 345 HEI Perspectives 3. HEI, Boston, Massachusset, 2013, pp. 122. 346

Hien PD, Bac VT, Tham HC, Nhan DD, Vinh LD. Influence of meteorological conditions on PM2.5 and 347 PM2.5−10 concentra ons during the monsoon season in Hanoi, Vietnam. Atmospheric 348 Environment 2002; 36: 3473‐3484. 349

18

Kim Oanh NT, Upadhyay N, Zhuang YH, Hao ZP, Murthy DVS, Lestari P, et al. Particulate air pollution in six 350 Asian cities: Spatial and temporal distributions, and associated sources. Atmospheric Environment 351 2006; 40: 3367‐3380. 352

Kumar P, Morawska L, Birmili W, Paasonen P, Hu M, Kulmala M, et al. Ultrafine particles in cities. 353 Environment International 2014; 66: 1‐10. 354

Lanzinger S, Schneider A, Breitner S, Stafoggia M, Erzen I, Dostal M, et al. Ultrafine and fine particles and 355 hospital admissions in central Europe results from the ufireg study. American Journal of Respiratory 356 and Critical Care Medicine 2016; 194: 1233‐1241. 357

Liu ZR, Hu B, Liu Q, Sun Y, Wang YS. Source apportionment of urban fine particle number concentration 358 during summertime in Beijing. Atmospheric Environment 2014; 96: 359‐369. 359

Luong LMT, Phung D, Sly PD, Morawska L, Thai PK. The association between particulate air pollution and 360 respiratory admissions among young children in Hanoi, Vietnam. Science of The Total Environment 361 2017; 578: 249‐255. 362

Marra J, Voetz M, Kiesling H‐J. Monitor for detecting and assessing exposure to airborne nanoparticles. 363 Journal of Nanoparticle Research 2010; 12: 21‐37. 364

Mazaheri M, Clifford S, Jayaratne R, Megat Mokhtar MA, Fuoco F, Buonanno G, et al. School Children’s 365 Personal Exposure to Ultrafine Particles in the Urban Environment. Environmental Science & 366 Technology 2014; 48: 113‐120. 367

Meier R, Eeftens M, Aguilera I, Phuleria HC, Ineichen A, Davey M, et al. Ambient ultrafine particle levels at 368 residential and reference sites in urban and rural Switzerland. Environmental Science and 369 Technology 2015; 49: 2709‐2715. 370

Morawska L, Afshari A, Bae GN, Buonanno G, Chao CYH, Hänninen O, et al. Indoor aerosols: from personal 371 exposure to risk assessment. Indoor Air 2013; 23: 462‐487. 372

Morawska L, He CR, Hitchins J, Mengersen K, Gilbert D. Characteristics of particle number and mass 373 concentrations in residential houses in Brisbane, Australia. Atmospheric Environment 2003; 37: 374 4195‐4203. 375

Morawska L, Ristovski Z, Jayaratne ER, Keogh DU, Ling X. Ambient nano and ultrafine particles from motor 376 vehicle emissions: Characteristics, ambient processing and implications on human exposure. 377 Atmospheric Environment 2008; 42: 8113‐8138. 378

Morawska L, Salthammer T. Fundamentals of Indoor Particles and Settled Dust. Indoor Environment. Wiley‐379 VCH Verlag GmbH & Co. KGaA, 2003, pp. 1‐46. 380

Mullen NA, Liu C, Zhang Y, Wang S, Nazaroff WW. Ultrafine particle concentrations and exposures in four 381 high‐rise Beijing apartments. Atmospheric Environment 2011; 45: 7574‐7582. 382

Perez N, Pey J, Cusack M, Reche C, Querol X, Alastuey A, et al. Variability of Particle Number, Black Carbon, 383 and PM(10), PM(2.5), and PM(1) Levels and Speciation: Influence of Road Traffic Emissions on 384 Urban Air Quality. Aerosol Science and Technology 2010; 44: 487‐499. 385

Pey J, Querol X, Alastuey A, Rodriguez S, Putaud JP, Van Dingenen R. Source apportionment of urban fine 386 and ultra‐fine particle number concentration in a Western Mediterranean city. Atmospheric 387 Environment 2009; 43: 4407‐4415. 388

Pey J, Rodriguez S, Querol X, Alastuey A, Moreno T, Putaud JP, et al. Variations of urban aerosols in the 389 western Mediterranean. Atmospheric Environment 2008; 42: 9052‐9062. 390

Quang T, He C, Morawska L, Knibbs L, Falk M. Vertical particle concentration profiles around urban office 391 buildings. Atmospheric Chemistry and Physics 2012; 12: 5017‐5030. 392

Querol X, Alastuey A, Moreno T, Viana MM, Castillo S, Pey J, et al. Spatial and temporal variations in 393 airborne particulate matter (PM10 and PM2.5) across Spain 1999–2005. Atmospheric Environment 394 2008; 42: 3964‐3979. 395

Reid J, Koppmann R, Eck T, Eleuterio D. A review of biomass burning emissions part II: intensive physical 396 properties of biomass burning particles. Atmospheric Chemistry and Physics 2005; 5: 799‐825. 397

Saksena S, Quang TN, Nguyen T, Dang PN, Flachsbart P. Commuters' exposure to particulate matter and 398 carbon monoxide in Hanoi, Vietnam. Transportation Research Part D‐Transport and Environment 399 2008; 13: 206‐211. 400

Stafoggia M, Schneider A, Cyrys J, Samoli E, Andersen ZJ, Bedada GB, et al. Association between short‐term 401 exposure to ultrafine particles and mortality in eight European urban areas. Epidemiology 2017. 402

Statistic OoG. Statistical Handbook of Vietnam. Hanoi, Vietnam: Statistic Publish House, 2015. 403

19

TEDI. Investment project for Ring Road No3, Hanoi, Vietnam, 2007. 404 Times VE. Vehicles overwhelming Hanoi. Vietnam Economic Times, Hanoi, 2015. 405 Wu Z, Hu M, Lin P, Liu S, Wehner B, Wiedensohler A. Particle number size distribution in the urban 406

atmosphere of Beijing, China. Atmospheric Environment 2008; 42: 7967‐7980. 407

Zhang Q, Avalos J, Zhu Y. Fine and ultrafine particle emissions from microwave popcorn. Indoor Air 2014; 408 24: 190‐198. 409

Kassomenos PA, Vardoulakis S, Chaloulakou A, Paschalidou AK, Grivas G, Borge R, et al. Study of PM10 and 410 PM2.5 levels in three European cities: Analysis of intra and inter urban variations. Atmospheric 411 Environment 2014; 87: 153‐163. 412

413

414

20

Supporting Materials 415

416 Table S1: Summary of PN number concentrations at six measured sites 417 418 Measured site S1 S2 S5 S6 S3 S4


7-9 Jan 2016

9-13 Jan 2016

13-16 Jan 2016

16-18 Jan 2016

18-20 Jan 2016

Whole period Outdoor PN concentration

Median 44709 31722 22916 20541 21764 29060Mean 47329 33338 35514 21272 25195 31834SD 21570 9570 57471 7753 13556 14634Max 171942 91167 1016967 99544 148335 204044Min 16679 17100 7128 7672 12205 17768

Indoor PN concentration Median 26580 12046 19139 12048 12910 17985Mean 29594 14479 19863 12906 14646 18760SD 15303 7567 8727 6320 6692 5082Max 94047 68384 93441 103165 37240 40748Min 7705 7744 6399 4514 5786 10408

Rush-hour period Outdoor PN concentration


Indoor PN concentrationMedian 39679 15905 21844 13627 20672 22776Mean 40914 10703 23061 13918 21521 23449SD 14905 1836 8126 4536 7493 5540Max 94047 15208 48736 27733 37240 40748Min 13890 7744 10597 4630 7426 12756

Off-peak period Outdoor PN concentration


Indoor PN concentration Median 22411 11509 17690 11595 9946 17236Mean 25932 18144 18972 12587 13147 17561SD 13983 9078 8684 6758 5465 4192Max 94047 68384 93441 103165 28299 36069Min 7705 8441 6399 4514 5786 10408 419 420

21

421

Table S2: Summary of I/O ratio of PN number concentrations at six measured sites 422 423 Measured site S1 S2 S5 S6 S3 S4


7-9 Jan 2016

9-13 Jan 2016

13-16 Jan 2016

16-18 Jan 2016

18-20 Jan 2016

Whole period Mean 0.62 0.45 0.87 0.60 0.60 0.62SD 0.18 0.20 0.35 0.09 0.15 0.12Max 1.89 1.79 2.35 2.02 1.45 1.11Min 0.16 0.11 0.04 0.45 0.08 0.11

Rush-hour period Mean 0.67 0.32 0.79 0.63 0.73 0.64SD 0.15 0.08 0.41 0.07 0.19 0.16Max 1.45 0.62 1.74 1.17 1.45 1.06Min 0.32 0.11 0.06 0.52 0.36 0.15

Off-peak period Mean 0.60 0.58 0.89 0.60 0.57 0.61SD 0.18 0.20 0.33 0.09 0.13 0.11Max 1.89 1.79 2.35 2.02 1.04 1.11Min 0.16 0.33 0.04 0.45 0.08 0.11 424

425

426

22

Fig.S1. Time-series of indoor and outdoor PN number concentrations and their ratios. 427

(a)

Site

S1

(b)

Site

S2

(c)

Site

S6

23

(d)

Site

S3

(e)

Site

S4

428

24

Fig.S2. Locations and monitoring positions. 429

(a)

Site

S1 & S2

(b)

Site

S3

SAMPLING OUTDOOR SITE

NGUYEN HUU THO STREETRING ROAD NO3

46m

44m

120m


SAMPLING INDOOR SITE

NGUYEN HUU THO STREET

46m44

m

SITE 2 SITE 1 SAMPLING OUTDOOR SITE

4TH

3RD

4TH

2ND

5.5m

12m

9m12m

N

S

EW

SITE 1SITE 2

H: 30M

H: 17MH: 56MH: 56M

10m

10m

1ST

2m

NGUYEN KHOAI STREET

N

S

E

W

SAMPLING

NG

UYE

N K

HO

AI S

TREE

T

4TH

OUTDOOR SITE



1ST


2m

10.5

m

12m

SITE 3

75m

75m

25

(c)

Site

S4

(d)

Site

S5

VO CHI CONG STREET

N

S

E

W

SAMPLING

50m

VO C

HI C

ON

G S

TREE

T

4TH

OUTDOOR SITE



1ST


2m

10.5

m

12m

SITE 4

50m

EXP

RES

SW

AY -

NAT

ION

AL R

OA

D N

O1

20m

20m

20m

12m

125m

EXPRESSWAY

GR FL

2ND

8TH

SAMPLING SITE

25m

26.2

m

125m

N

S

E

W



8m

26

(e)

Site

S6

430

431

432

433

434

435

TO H

UU

RO

AD

SAMPLING SITE

100m

+41.0m

+0.0m

12TH

100m

DUONG NOI URBAN AREA

CT7BCT7A

CT7B CT7A

20TH

SAMPLING SITE

N

S

E

W

quang, tran ngoc, thi hue, nguyen,thai, phong,mazaheri ...41 because of their potential to have...

Documents