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Transportation Research Part D 13 (2008) 19–26

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Contributions of roadside vehicle emissions to generalair quality in Hong Kong

J. Lau a,*, W.T. Hung a, C.S. Cheung b, D. Yuen b

a Department of Civil and Structural Engineering, The Hong Kong Polytechnic University, Hong Kongb Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong

Abstract

Data for 7-year from three roadside, three urban background, and one rural monitoring stations are employed to lookat the contribution of roadside vehicle emissions to the general air quality in central Hong Kong. It is found that within theurban core of Hong Kong, variations in concentrations of various gaseous pollutants are heavily influenced by variationsin local traffic volume. The daily patterns of NO2, NOx, and particulates concentrations at roadside and background sta-tions are similar while no common daily concentration pattern of SO2 can be found. Concentration at nearby roadside andbackground stations are closely correlated for all pollutants investigated. Daily variations of NO2, NOx, and particulatesconcentrations at roadside and urban background stations follow the traffic pattern of the area closely. Similarities existbetween traffic volume and SO2 concentration, but they are less clear. For each of the pollutants, traffic volume and con-centration in the urban background are positively correlated.� 2007 Elsevier Ltd. All rights reserved.

Keywords: Vehicle emission; Urban centre area; Local pollution source; Background air quality

1. Introduction

There are constant debates on the effectiveness of controlling vehicle emissions in improving air quality inHong Kong. Some argue that the major polluters are industries across the boundary to the north of HongKong in the Pearl River Delta Region. This study explores the contribution of vehicle emissions to localair quality. Hourly traffic and concentration patterns in different parts of the urban area of Hong Kong areused to examine the effect traffic has on daily variation of pollutant concentration. Air quality data obtainedfrom a rural monitoring station, where no vehicular traffic is present, is used for comparison purposes.

2. Data collation

The urban area of Hong Kong is densely populated (over 40,000 inhabitants/km2) and street canyons arecommonplace. The Hong Kong Government has set up three roadside air quality monitoring stations in urban

1361-9209/$ - see front matter � 2007 Elsevier Ltd. All rights reserved.

doi:10.1016/j.trd.2007.10.004

* Corresponding author.E-mail address: 06901833r@polyu.edu.hk (J. Lau).

20 J. Lau et al. / Transportation Research Part D 13 (2008) 19–26

areas and numerous general air quality stations throughout the territory. We have selected these three road-side stations and three other adjacent general stations for our study. One rural station at Tap Mun, located15 km away from the nearest build-up area is selected for background comparisons. The locations of the sta-tions are seen in Fig. 1 and the characteristics of the air monitoring stations are in Table 1 (Hong Kong Envi-ronmental Protection Department, 2006b).

The local annual average daily traffic volume near the roadside stations ranges from 25,000 to 50,000 vehi-cles (Hong Kong Transport Department, 2006). The air sampling points at roadside stations are situated at nomore than 5 m away from the vehicle carriageway and no more than 5 m above ground. To assess backgroundpollution around each roadside station, air pollutant concentration data from three urban background sta-tions, chosen because of their proximity to a roadside station, are collected. These general air monitoring sta-tions are located at rooftops of buildings in residential or mixed residential/commercial areas and measurepollution levels the urban population is generally exposed to. Data collected from Tap Mun, a rural air qualitymonitoring station situated in an outlying island, reflects the background pollution level in Hong Kong.

All stations measure concentrations of NO2, respiratory suspended particulates (RSP), and SO2 while NOx

concentration is measured at all stations except that at Eastern. The concentration data, expressed as hourlyaverages, was gathered between January 1999 and December 2005, with the exception of Mong Kok, wheredata collection began in January 2001. To identify the effect traffic has on variations of pollutants, hourly aver-ages at each station are calculated for each pollutant. The hourly averages for a particular hour of the week areobtained by taking the average of concentration at that hour of the week. This follows Mayer (1999) and allowsfor comparison of hourly concentration levels for each hour of the week at different monitoring stations.

3. Comparison of roadside and background pollution

Fig. 2a shows that, in the urban area of Hong Kong, NO2 concentration reaches a daily peak in late after-noon with the lowest concentration found in the early morning. NO2 concentrations at the urban background

Fig. 1. Location of monitoring stations.

Table 1Characteristics of monitoring stations

Station (abbreviation) Station characteristics Samplingheight (m)

Altitude abovesea level (m)

Nearest roadsidestation (Dist. in km)

Causeway Bay (CB) Roadside: next to a busy roadway located in a streetcanyon

3 6.5

Central (C) Roadside: sandwiched between two roads in a busyintersection located in a street canyon

4.5 8.5

Mong Kok (MK) Roadside: located in the middle of a road, next to abusy intersection located in a street canyon

3 8.5

Central-Western (CW) Urban background: residential area; building locatedalong a hill slope

18 78 C (1.5)

Eastern (E) Urban background: residential area; building locatedat the foot of a hill

15 28 CB (4)

Sham Shui Po (SSP) Urban background: mixed residential and commercial;no hills in the area; building located next to busyintersection

17 21 MK(1.3)

Tap Mun (TM) Rural; no vehicular traffic 11 26

J. Lau et al. / Transportation Research Part D 13 (2008) 19–26 21

stations exhibit nearly identical daily patterns, similar that found in Bangkok (Zhang and Kim Oanh, 2002).The daily pattern of NO2 concentration at TM, the rural station, remains low and varies little on different daysof the week. The roadside and urban background patterns are less congruent to those found in Namdeo andBell (2005), in which variations in concentrations at roadside and background stations are linked to variationsin traffic volume.

Fig. 2b shows that the hourly average NOx, which contains NO and NO2, concentration at the urban sta-tions exhibits a similar daily pattern as NO2, except that there is a morning peak in NOx concentration onweekdays. The afternoon peak and daily minimum concentrations are at approximately the same time asNO2. In general, concentrations at roadside and urban background stations exhibit similar patterns. Concen-tration at TM station remains low throughout the week and the daily pattern of NOx is similar to that of NO2.Similar results are found in Ketzel et al. (2003).

The ratio between hourly average NO2 and NOx concentrations is the lowest at roadside stations and thehighest at TM (Fig. 2c). The low ratio of NO2 to NOx at roadside stations is because the majority of NOx

emitted from motor vehicles, and detected at the roadside stations, comes in the form of NO (Carslaw andBeevers, 2004). As the NO emitted from vehicles disperses towards the background station, part of it is con-verted to NO2; thus increasing the NO2/NOx ratio. The high NO2/NOx ratio at TM shows that a majority ofNOx is in the form of NO2, implying that the influence of traffic is minimal.

Fig. 3 shows the hourly average RSP concentration at each of the stations. The daily pattern at most of theurban stations are similar—on any day of the week, there are two peaks in concentration, one occurring in themorning and the other in late afternoon. At TM, the concentration is generally higher in the morning andthere is little difference between concentrations at this station and at E. At all stations, hourly concentrationis lowest in the early morning. Similar results are found in Namdeo and Bell (2005).

The difference between RSP concentrations at roadside and urban background stations can be largelyattributed to differences in organic and elemental carbon concentrations, whose largest contributor is motorvehicles (Qin et al., 1997). Meanwhile, there is a clear difference between concentrations of elemental andorganic carbon at the urban background and rural stations while differences in concentration of other typesof fine particulate at the two stations are smaller (Hagler et al., 2006), suggesting that the difference in con-centration at different types of stations is mainly due to vehicle emissions.

Fig. 4 shows the hourly average SO2 concentration at the monitoring stations. Compared to the other pol-lutants considered, and the results of Jo and Park (2005), hourly variations in SO2 at different stations is lessuniform. Concentrations remain low at all stations. Weekday and night time concentrations at the urban sta-tions exhibit similar patterns. The hourly concentration at TM follows the same pattern for every day of theweek the concentration is at its highest level during the late morning hours and remains steady for the rest ofthe day.

Fig. 2. Hourly average: (a) NO2 concentration, (b) NOx concentration, (c) NO2/NOx ratio at roadside, urban background, and ruralstations.

22 J. Lau et al. / Transportation Research Part D 13 (2008) 19–26

Fig. 2 (continued)

Fig. 3. Hourly average concentration of RSP at roadside, urban background, and rural stations.

J. Lau et al. / Transportation Research Part D 13 (2008) 19–26 23

Fig. 4. Hourly average concentration of SO2 at roadside, urban background, and rural stations.

24 J. Lau et al. / Transportation Research Part D 13 (2008) 19–26

The small difference between roadside and background SO2 concentration may be because during the studyperiod, vehicle emissions accounted for less than 2% of SO2 emitted in Hong Kong, compared to over 25% forboth NOx and RSP, with contributions from motor vehicles falling to less than 0.25% after the introduction ofultra-low sulphur diesel fuel in late 2000 (Hong Kong Environmental Protection Department, 2006a). Theroadside-background difference is smaller than that found in Jo and Park because vehicle emissions are a lar-ger source of SO2 in Daegu than in Hong Kong (Nguyen and Kim, 2006).

For each roadside-background station pair (CB/E, C/CW, MK/SSP), the hourly averages of NO2, NOx,and RSP concentration at the roadside are higher than the concentration at the corresponding background

Table 2Correlation coefficients between nearby roadside and urban background stations 1999–2005

Correlation N

NO2 CB/E 0.748 49,327C/CW 0.812 55,254MK/SSP 0.865 39,829

NOx C/CW 0.657 55,253MK/SSP 0.714 39,829

RSP CB/E 0.677 56,860C/CW 0.865 53,927MK/SSP 0.939 40,300

SO2 CB/E 0.645 49,459C/CW 0.698 57,073MK/SSP 0.877 39,336

Note: All values are significant at 1% level. N = number of hours where concentration is measured at both stations. Maximum N = 61,368for CB/E and C/CW, 43,824 for MK/SSP.

J. Lau et al. / Transportation Research Part D 13 (2008) 19–26 25

station on any hour of the week (Figs. 2 and 3). Fig. 4 shows that the SO2 concentration is generally higherat each roadside station compared to its nearest background station, but the difference is small.

The correlation coefficients between concentrations at nearby roadside and urban background stations areshown in Table 2. For each roadside-background station pair, pollutant concentration is highly correlated.Among the station pairs, the correlation between MK and SSP stations is the strongest for each pollutantwhile correlation between concentration at the stations CB and E is the weakest. This may be due to the prox-imity of the stations.

4. Relationship between traffic and urban air quality

Hourly variations in pollutant concentrations at roadside stations often follow traffic patterns (Ketzel et al.,2003). To examine the relationship between variations in traffic and concentrations of pollutants, hourly pro-portion of weekly traffic in the area of the roadside stations are plotted against hourly average concentrationsat the urban background stations. The hourly traffic proportion is computed by dividing the hourly traffic vol-ume for each hour of the week by the total weekly traffic volume at a busy street in the area of the roadsidestation. The plots for MK and SSP are shown in Fig. 5 and similar results are found at the other urbanstations.

The figure shows that there is a positive correlation between traffic volume and concentrations of NO2,NOx, and RSP in the urban area. This appears to show that traffic volume strongly influences urban back-ground concentrations of these pollutants. A similar relationship is also found between traffic volume andbackground SO2 concentration, suggesting that urban background SO2 concentration is affected by the vol-ume of traffic in the area. However, as vehicle emission is a minor source of SO2 in Hong Kong, daily variationat background stations may also be affected by other sources such as domestic and industrial fuel combustion(Hong Kong Environmental Protection Department, 2006a,b).

0 0.5 130

40

50

60

70

ppb

NO2

0 0.5 10

100

200

300

400

ppb

NOx

0 0.5 140

50

60

70

80

90

μ g/

m3

RSP

0 0.5 14

6

8

10

12

ppb

SO2

0 0.5 110

20

30

40

50

% of weekly traffic0 0.5 1

0

50

100

150

0 0.5 140

50

60

70

0 0.5 14

6

8

10

12

MK

SSP

Fig. 5. Scatterplots of hourly proportion of weekly traffic and hourly concentrations at urban stations.

26 J. Lau et al. / Transportation Research Part D 13 (2008) 19–26

5. Conclusions

Monitoring data collected over a 7-year period shows that, in the urban centre area of Hong Kong, hourlyNO2, NOx and RSP concentrations at roadside and urban background stations closely follow variations intraffic volume. No common daily pattern of SO2 concentration is present within the area and the relationshipbetween daily patterns of traffic and urban background SO2 concentration is less clear. Concentrations ofNO2, NOx, and RSP are higher at roadside stations than urban background stations, while it is less definitivefor SO2. Concentrations of various pollutants at nearby roadside and urban background stations are posi-tively correlated.

Acknowledgements

The air quality monitoring data used was provided by the Environment Protection Department of HongKong and the traffic volume data by the Transport Department of Hong Kong. The study is supported bya grant from the Research Grant Council of the Hong Kong Special Administrative Region (Project No.CERG517205) and a studentship grant from the Hong Kong Polytechnic University. Comments from twoanonymous reviewers are highly appreciated.

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