Establishing a conceptual model for photochemical ozone pollution in subtropical Hong Kong.

Photochemical ozone (O3) formation is related to its precursors and meteorological conditions. A conceptual model of O3 air pollution is developed based on the analysis of data obtained at Tung Chung (TC) in Hong Kong. By comparing meteorological parameters between O3 and non-O3 episode days, it was found that high temperatures, strong solar radiation, low wind speeds and relative humidity, northeasterly and/or northwesterly prevailing winds were favorable for the O3 formation, while tropical cyclones were most conducive to the occurrence of O3 episodes. Backward trajectories simulation and graphical illustration of O3 pollution suggested that super-regional (i.e. central and eastern China) and regional (i.e. Pearl River Delta, southern China) transport was another factor that contributed to high O3 levels in Hong Kong. The photochemical O3 formation, generally VOC-limited in Hong Kong, was controlled by a small number of volatile organic compounds (VOCs). Furthermore, the positive matrix factorization (PMF) simulation suggested that solvent usage and vehicular emissions are the major contributors to ambient VOCs in Hong Kong. Finally, this paper presents recommendations for further O3 research and implementation of O3 control strategies.

Introduction

Ozone (O3), a major component of photochemical smog which impairs visibility and human health, is formed by a complex series of chemical reactions involving volatile organic compounds (VOCs) and nitrogen oxides (NO) in the presence of sunlight (Seinfeld and Pandis, 2006; Zheng et al., 2010). In most urban areas, ambient concentrations of photochemically formed O3 are related to its precursors, while favorable meteorological conditions are required for the occurrence of high O3 concentrations (Ding et al., 2004; Guo et al., 2009). In Hong Kong, high O3 concentrations or “O3 episodes” are commonly observed in late summer and autumn, and are closely associated with local photochemical production and long-range transport (Guo et al., 2009; Wang et al., 2009).

In order to understand the factors that influence photochemical O3 formation, conceptual models of O3 air pollution have been developed in recent years for different regions. A conceptual model is a qualitative explanation of the formation and accumulation of O3 in a given area based on the chemical characteristics of the ambient atmosphere, as well as the physical transport and removal process observed in given locations (Tom et al., 2006; Pun et al., 1998). Pun et al. (1998) developed a conceptual model to investigate the O3 formation in San Joaquin Valley in the USA and found that the high O3 concentrations observed resulted from both the transport of O3 and precursors from upwind locations, and the local production of O3 in urban areas within the valley. Tom et al. (2006) developed a conceptual description of the nature of the O3 air quality problem in the O3 transport region (OTR), including Connecticut, Delaware, the District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont and north Virginia in USA and concluded that a severe O3 episode in the OTR can contain elements of long-range air pollution transport from outside the OTR, regional scale transport within the OTR from channeled flows in nocturnal low level jets, and local transport along coastal shores due to bay, lake, and sea breezes.

To formulate and implement effective control strategies for O3 pollution, the major objective of this study is to develop a conceptual model for the formation, transport and accumulation of O3 in subtropical Hong Kong by integrated data analysis at Tung Chung (TC) between 2005 and 2010. We chose the TC site because only at this site the most comprehensive dataset including real-time O3, CO, NO, SO2, VOCs and meteorological parameters has been systematically collected so far. In addition to the influence of local emission sources, the sampling site is also affected by polluted continental air masses from the highly industrialized PRD region of mainland China (Guo et al., 2009; Zhang et al., 2007). Thus, this site is capable of monitoring air pollutants transported from the inland PRD region and is suitable for assessing their impact on local air quality. A variety of aspects, including meteorological conditions, source apportionments of O3 precursors, O3-precursor relationships, and the characteristics of air masses in Hong Kong are evaluated. The conceptual model in this study tries to answer the following questions: (1) what meteorological conditions are favorable to photochemical O3 formation? (2) Does regional transport have an important influence on high O3 levels? (3) Is the O3 formation limited by VOCs, or NOx, or both, and therefore which sources of precursors are the most important ones to be controlled? (4) What are the main sources of O3 precursors i.e. VOCs and NO?

Methodology

Description of sampling site

Tung Chung (TC, 22.30°N, 113.93°E, Fig. 1 ) is a newly-developed residential town located on northern Lantau Island, about 3 km south of the Hong Kong International Airport at Chek Lap Kok with Hong Kong urban center 20 km to the southwest and Macau 38 km to the northeast. The TC site is adjacent to highway and railway lines that connect the airport with other islands of Hong Kong. The potential impact of the airport, highway and railway lines on VOC and NO levels at the sampling site was demonstrated to be insignificant (AOAQS, 2011; Guo et al., 2007; So and Wang, 2004). In addition to the influence of local emission sources, TC is also affected by polluted continental air masses from the highly industrialized Pearl River Delta (PRD) region, south China. As such, the TC site is an ideal location to assess the O3 pollution in Hong Kong.

Fig. 1

Location of the sampling site and the surrounding region.

Sampling data

In this study, real-time VOC data collected from 2005 to 2010 was provided by the Hong Kong Environmental Protection Department (HKEPD). The on-line VOC analyzer (Syntech Spectras GC 955, Series 600/800, Netherland) includes two sampling systems and two column separating systems: GC1 for the 16 C2–C5 hydrocarbons, and GC2 for the 14 C6–C10 hydrocarbons. Details can be found in HKEPD (2012). In this study, the GC system was operated continuously, with samples collected and analyzed every 30 min. Furthermore, in order to maintain the consistency for the input of different models, the 30-min data was averaged into hourly values.

In addition, built-in computerized programmes of quality control systems, i.e. auto-linearization and auto-calibration, and calibration with span gas were used. Before sampling, the analyzers were calibrated weekly by injecting certified calibration gas (NPL span gas, National Physical Laboratory). In addition, the quality of the real-time data was assured by comparison with the canister samples analyzed by the University of California at Irvine (UCI) (Colman et al., 2001). The accuracy and precision of the measurements were obtained using the following methods: the accuracy of GC was based on weekly span checks, monthly calibration and annual auto-linearization using NPL gas. The precision of GC was based on quarterly precision check results (the 95% probability limits for the integrated precision based on the weekly precision check results of the latest 3 months). The detection limits of the above VOCs varied compound by compound, ranging from 0.002 to 0.787 ppbv. The accuracy of the measurements was 1–10% for the above VOCs, whereas the precision was 2.5–20%.

Furthermore, other trace gases, including O3, CO, SO2, NO–NO2–NO and meteorological parameters were also obtained from HKEPD (http://epic.epd.goc.hk/ca/uid/airdata).

Procedures for developing a conceptual ozone model

Fig. 2 illustrates three steps for developing a conceptual ozone model. The first step is to generalize the meteorological conditions, air mass transport characteristics, and precursor levels on O3 episode days by analyzing the measurement data: first, we identified the O3 episodes, especially multi-day O3 episodes from 2005 to 2010; second, we analyzed and compare the meteorological conditions on O3 and non-O3 episode days; third, we investigated the characteristics of air masses on O3 and non-O3 episode days; fourth, we analyzed the source contributions of VOCs and investigated the O3-precursor relationships. Based on the generalized requirements for an O3 episode day in step 1, we proposed a conceptual model for O3 pollution which considers atmospheric chemical and physical processes, emission sources of O3 precursors and meteorological parameters during O3 episode events (step 2). Once the conceptual model is established, O3 episode events will be forecast by looking into the meteorological conditions, air mass transport and abundance and sources of precursors (step 3). The proposed conceptual model will be evaluated by case studies.

Fig. 2

Procedure for developing the O3 conceptual model in Hong Kong.

Simulation tools for the conceptual model development

Backward trajectories simulation

Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSLPIT 4.9, http://ready.arl.noaa.gov/HYSPLIT.php), developed by National Oceanic and Atmospheric Administration (NOAA) Air Resource Laboratory, was applied to air masses at TC at every 3 h with the start time of 0000 LT (local time) at the ending point of 200 m above sea level. Furthermore, the trajectories were classified into different groups by using Hierarchical Clustering Method (Ward, 1963). Details can be found in Guo et al. (2009).

Positive matrix factorization (PMF) model

PMF model v 3.0 was applied to investigate the VOC source apportionments in this study. PMF is a multivariate factor analysis tool that decomposes a matrix of speciated data into two matrices, factor contributions and factor profiles, which can be interpreted by an analyst as to what sources are represented based on observations at the receptor site. A detailed description of this model can be found in Guo et al. (2011).

Observation-based model (OBM)

The OBM uses concentrations of O3 and its precursors (i.e. VOCs, CO and NO), as well as meteorological data measured as a function of time at given sites. Detailed description of the OBM model can be found in Ling et al. (2011). Briefly, the relative incremental reactivity (RIR) functions simulated by the OBM model can be used to evaluate the sensitivity of O3 photochemical production to the changes in the concentration of its individual precursors in the given areas.

Photochemical trajectory model incorporated with master chemical mechanism (PTM-MCM model)

The PTM is a ground-level Lagrangian box model, simulating complex chemical reactions within a well mixed boundary layer air parcel, which extends from the Earth’s surface up to the top of a diurnally varying boundary layer. The chemical mechanism employed in the PTM is an extended version of MCM v3.1, which is a near-explicit chemical mechanism describing the detailed degradation of a large number of emitted organic compounds and the resulting generation of O3 and other secondary pollutants under conditions appropriate to the atmospheric boundary layer. Furthermore, a photochemical O3 creation potential (POCP) index is used to describe the relative contribution of VOCs to O3 formation at the regional scale in the PTM model. The detailed model description and the initial concentrations for the majority of VOCs in the model can be found in Cheng et al. (2010a).

Conceptual model development for the O3 pollution

What meteorological conditions are favorable to photochemical O3 formation?

General characteristics of meteorological conditions conducive to O3 formation

In this study, an O3 episode day was defined when the highest hourly O3 concentration of a given day exceeded 200 μg m−3 (∼102 ppbv) based on the Ambient Air Quality Standard in China (China's Grade II standard, http://english.mep.gov.cn/standards_reports/standards/). In addition, a multi-day O3 episode referred to a period of at least 3 consecutive O3 episode days. Table 1 identifies multi-day O3 episodes and selected non-O3 episodes at TC from 2005 to 2010. A total of 10 multi-day O3 episodes were observed from 2005 to 2010 at TC. The non-O3 episodes were selected as the days with the hourly maximum O3 concentration lower than 102 ppbv in the same month as that for multi-O3 episodes. To provide the representative characteristics of non-O3 episode days, investigate the influence of different factors and improve the statistical significance, non-O3 episode days were selected as many as possible for comparison. Table 2 shows statistical descriptions of air pollutants together with meteorological parameters for O3 and non-O3 episode days. Fig. 3 illustrates the mean diurnal variations of O3 and meteorological parameters, including solar radiation, temperature, relative humidity, wind speed, and wind direction at TC on O3 and non-O3 episode days from 2005 to 2010. Much higher concentrations (p < 0.01) of O3 and some primary pollutants, i.e. SO2 and CO, were observed on the O3 episode days. However, NO level was comparable on both O3 episode and non-O3 episode days (p > 0.05), while higher NO2 (p < 0.01) was observed on O3 episode days. In addition, temperature and solar radiation were higher on the O3 episode days than non-O3 episode days (p < 0.01), while the relative humidity and wind speed were lower (p < 0.01), indicating that meteorological parameters had significant impact on O3 levels. Indeed, inspection of all the 10 multi-day O3 episodes found that high O3 levels were closely associated with high temperature (>28 °C at daytime), strong solar radiation (>700 W m−2 at daytime), low wind speed (<2 m s−1 at daytime) and relative humidity (<70% at daytime).

Table 1

Ozone episode and non-ozone episode days in 2005–2010.

Ozone episode	Period	Non-ozone episodea	Periodb
2005 Episode 1	18/19/20 Jul 2005	2005 Non-episode 1	Jul 2005
2005 Episode 2	2/3/4 Oct 2005	2005 Non-episode 2	1–15 Oct 2005
2006 Episode 1	3/4/5 Nov 2006	2006 Non-episode 1	1–15 Nov 2006
2007 Episode 1	15–21 Sep 2007	2007 Non-episode 1	Sep 2007
2007 Episode 2	5/6/7 Oct 2007	2007 Non-episode 2	Oct 2007
2007 Episode 3	24/25/26 Oct 2007
2008 Episode 1	10–16 Sep 2008	2008 Non-episode 1	Sep 2008
2009 Episode 1	6–9 Oct 2009	2009 Non-episode 1	Oct 2009
2009 Episode 2	22–24 Oct 2009
2010 Episode 1	28–31 Aug 2010	2010 Non-episode 1	Aug 2010

Days with low ozone concentration (<200 μg m−3), used for comparison with ozone episode day (>200 μg m−3).

Ozone episode days excluded if applicable.

Table 2

Statistical description of air pollutants and meteorological parameters during the O3 episode events and the selected non-O3 episode daysb (mean ± 95% confidence interval).

	O3 (ppbv)	NO (ppbv)	SO2 (ppbv)	CO (ppbv)	Temperature (°C)a	NO2 (ppbv)	Wind speed (m s−1)a	Solar radiation (W m−2)a	Humidity (%)a
O3 episodes	40.4 ± 2.4	11.5 ± 0.9	13.6 ± 0.7	793.1 ± 0.1	34.1 ± 2.6	37.9 ± 1.1	3.7 ± 0.2	764 ± 32	77.1 ± 1.9
Non-O3 episodes	25.6 ± 0.6	12.5 ± 0.6	7.7 ± 0.4	570.1 ± 5.6	31.2 ± 1.1	21.5 ± 0.4	4.7 ± 0.2	705 ± 29	81.1 ± 1.1

Daily average maximum value.

The selected non-O3 episode days were presented in Table 1.

Fig. 3

Mean diurnal variations of wind speed and wind direction, solar radiation, relative humidity, temperature and O3 on the O3 and non-O3 episode days.

On a regional scale, a high-pressure system over China may transport polluted continental air masses to Hong Kong, resulting in high O3 concentrations. Fig. 4 shows the mean sea level pressure and wind field on 1000 hpa for East Asia from 23 October to 1 December 2007, when five O3 episode days were observed (Guo et al., 2009). It is clear that there was an intensive high-pressure system over northern China, while Hong Kong was in the front of the high-pressure ridge. Due to the influence of the high-pressure system, the prevailing synoptic winds in Hong Kong were from the northeast, which might lead to high O3 levels. Indeed, on 24−26 October, an O3 episode event was found at TC. Furthermore, the diurnal patterns on the O3 episode days observed in 2005−2010 (Fig. 3) showed a clear diurnal shift in wind speed and direction at TC − southeasterly/northeasterly at lower speeds at night and northerly/northwesterly at higher speeds during daytime when the O3 levels were usually high, confirming that synoptic winds were associated with high O3 concentrations. Previous studies demonstrated that the prevailing north and northeast winds brought VOC-laden air and O3 from inland PRD region to Hong Kong (Guo et al., 2009; Wang et al., 2009).

Fig. 4

The mean sea level pressure and wind field on 1000 hpa for the East Asia from 22 October to 1 December 2007 (from Guo et al., 2009).

Impact of tropical cyclones

Fig. 5 presents the mean sea level pressure and wind field for O3 and non-O3 episodes in Hong Kong between 2005 and 2009. Fig. 6 shows the typical synoptic charts on the nine O3 episode events. It is remarkable that the nine severe O3 episode events from 2005 to 2009 were all influenced by tropical cyclones over the East and South China Sea. The tropical cyclones were also found to be most conducive to the occurrence of high O3 episodes from 1994 to 2003 (Lee et al., 2002; Huang et al., 2005). When a tropical cyclone was formed and its center was over the East and the South China Sea, it intensified the inflow in the lower atmospheric layer and the outflow in the upper atmosphere, which caused stagnation and subsidence air over Hong Kong, forming an inversion layer. Such an inversion layer is not favorable to the dispersion of air pollutants. Nevertheless, it should be noted that though all tropical cyclones over the East and the South China Sea caused high O3 levels, it does not mean that all the O3 episode days in Hong Kong were induced by tropical cyclones. Under stable meteorological conditions which include high temperature, strong solar radiation, and calm winds, high O3 levels could also be observed. Huang et al. (2005) counted that about 62% of O3 episodes from 1999 to 2003 resulted from cyclonic weather patterns.

Fig. 5

Mean weather conditions for multi-day ozone episodes (a), and non-ozone episodes (b) (shaded: sea level pressure, hpa; vector: wind, m s−1; meteorological data was output from WRF simulation in 3-h intervals).

Fig. 6

Synoptic charts for the nine O3 episode events (source: http://envf.ust.hk/dataview/hko_wc/current/).

Does regional transport have an important influence on high O3 levels?

Analysis of synoptic wind patterns above suggested the influence of regional transport of air pollutants at TC. In order to determine whether the air masses originated from local, regional and super-regional sources, 24-h backward trajectories were developed using the NOAA-HYSPLIT 4.9 model with the Global Data Assimilation System (GDAS) meteorological data for 3-h intervals at the ending point of 200 m above sea level. These air masses were classified into local, regional (from PRD region), oceanic and super-regional air masses according to their source origins (i.e. longitude and latitude). In addition, cluster analysis was applied to segregate the calculated trajectories into a number of groups for each month from 2005 to 2010 using the hierarchical Ward's method with a square Euclidean measure (Ward, 1963). In total, 55 cluster groups were obtained. Based on their pathways, air masses arriving at TC were classified into four categories for each month from 2005 to 2010. In order to characterize the four types of air masses, two cases are presented here. Taking September 2005 and June 2010 as examples (Fig. 7 ), in September 2005, four categories were described: (i) air masses originating from inland China, passing over Guangdong province and finally arrived at TC (track 1); (ii) air masses originating in the Hong Kong area (track 2); (iii) air mass originating in the South China Sea (track 3) with fast movement; and (iv) air masses originating from the eastern China coast, passing over the coast of eastern Guangdong with very slow movement (track 4). Hence, tracks 1 and 4 were identified as super-regional transport; track 2 was identified as local transport while track 3 originated from the South China Sea. In June 2010, four categories were obtained as well: (i) air masses originating from eastern China coast, passing over the coast of eastern Guangdong with very slow movement (track 1); (ii) air masses originating from the PRD region (track 2) with slow movement; (iii) air mass originating from South China Sea (tracks 3 and 4) with fast movement. Track 1 was identified as super-regional transport, while track 2 was classified as regional transport. The trajectory results confirmed that the air masses were of different origins during different periods.

Fig. 7

Backward trajectories for September 2005 and June 2010.

Table 3 presents the average values of different pollutants of the four types of air masses from 2005 to 2010. SO2, NO and TVOCs showed higher concentrations in the local and regional air masses, and lower concentrations in the oceanic air masses, most likely due to the dilution of cleaner air from the ocean. However, O3 had the highest concentration in the super-regional air masses, followed by regional, oceanic and local air masses. The relatively higher O3 levels in super-regional and regional air masses indicated that long-range transport contributed significantly to the increase of background O3 levels in Hong Kong. Indeed, Wang et al. (2009) found that long-range transport made a significant contribution to the increase in “total ozone” in urban Hong Kong, and about 81% of the O3 increase in Hong Kong was due to the O3 increase in the background air. On the other hand, the lower O3 level (p < 0.01) in the local air masses was due to the titration of NO at TC. To better understand the NO titration for local air masses, the “total ozone” O (i.e. O3 + NO2) was further examined. The mean concentration of O was 49.5 ± 2.4 ppbv (mean ± 95% confidence interval) for local air masses, while it was 44.5 ± 0.5 ppbv and 54.7 ± 0.5 ppbv for regional and super-regional air masses, respectively. This confirmed that lower O3 concentration in local air masses was attributed to high emissions of NO in urban Hong Kong (Guo et al., 2009; Wang et al., 2009). Further inspection found that over the six years, the transport regime at TC was dominated by the air originating from super-regional transport (about 65% to the total air masses), followed by oceanic air (29%), regional transport (5%) and local emissions (1%). Due to the influence of Asian monsoon circulations, most of the oceanic air arrived at TC in summer, bringing in clean marine air, while super-regional and regional transport were often observed in autumn and winter, leading to the movement of precursor-laden air from the Asian continent to Hong Kong. The high frequency of air masses from super-regional and regional transport is another factor that contributes to high O3 levels in autumn in Hong Kong, confirmed by the highest O3 mixing ratio in the super-regional air masses (Table 3). Indeed, a study conducted at TC in October−December 2007 also found that high O3 levels were attributed to regional and super-regional transport (Guo et al., 2009; Cheng et al., 2010a).

Table 3

Average values of SO2, NO, O3, CO and TVOCs in the four major types of air masses at TC from 2005 to 2010.

		2005	2006	2007	2008	2009	2010
SO2 (ppbv)	La	3.6 (21)b	23.5 (48)		6.9 (45)	10.1 (36)	8.2 (24)
	Ra	12.2 (321)	16.6 (474)	14.5 (22)	9.4 (690)	9.5 (513)	8.1 (497)
	Sa	6.1 (4242)	10.9 (3855)	10.4 (1665)	8.7 (5310)	5.8 (5160)	4.6 (5208)
	Oa	4.3 (2740)	4.4 (2520)		3.4 (1977)	2.5 (1599)	2.4 (2181)
NO (ppbv)	L	26.4	61.3		33.2	25.3	78.3
	R	24.9	29.8	25.2	26.3	24.7	37.2
	S	11.6	13.6	13.2	14.1	11.2	14.7
	O	15.4	10.3		8.5	12.0	8.0
O3 (ppbv)	L	9.0	3.1		9.6	16.7	11.3
	R	19.8	11.0	11.0	14.6	21.7	9.5
	S	25.2	23.3	27.7	25.9	28.0	22.6
	O	15.7	15.7		18.6	16.8	20.4
CO (ppbv)	L	499.3	948.0		704.3	584.9	918.3
	R	813.6	786.7	529.8	845.8	732.0	866.6
	S	769.9	640.4	739.7	809.4	589.2	677.6
	O	650.7	512.3		564.3	440.0	498.6
TVOCs (μg m−3)	L	24.8	38.6		37.8	48.5	72.0
	R	33.5	56.0	15.7	40.7	48.6	75.8
	S	14.5	14.4	18.4	26.8	27.4	29.1
	O	7.8	8.8		5.7	11.8	6.3

L, R, S, O stand for air masses from local, regional, super-regional and oceanic transport.

Data in the bracket means the total number of air masses observed.

Fig. 8 shows a conceptualization of the influence of different air masses on O3 levels at TC. The figure was generated based on the following steps. First, the transport history of air masses was investigated and the air masses were classified for the sampling period. In this study, 24-h backward trajectories were carried out using the HYSPLIT model with the GDAS meteorological data. For each day in the sampling period, eight trajectories were generated corresponding to arrival times at TC of 0000, 0300, 0600, 0900, 1200, 1500, 1800, and 2100 LST at the ending point of 200 m above sea level. These air masses were classified into local, regional, super-regional and oceanic air masses according to their original positions (i.e., latitude and longitude). In addition, the air masses for other hours during the day were classified using the following method: if an air mass at 0300 was identified as regional transport, the air masses at 0200 and 0400 were also considered as regional transport; secondly, the dominant surface winds of different air masses on high O3 days and non-O3 episode days in summer and autumn were identified; Finally, the relative O3 concentrations in different air masses (i.e. local, regional, super-regional and oceanic) with different dominant surface winds were determined. It should be noted that due to the consideration of the statistical power of the trajectory results, a high O3 day is defined as the day with the highest hourly average O3 mixing ratio exceeding 80 ppbv in the figure. In addition, only O3 mixing ratios during daytime (0800−1800, local time) were considered due to the fact that O3 is formed by VOCs and NO reacting in the presence of sunlight. It is noteworthy that O3 episode days usually occur in summer and autumn in Hong Kong. Inspection of the figure found that the dominant surface wind was generally from the northwest during high O3 days, whereas the prevailing winds were generally from the southwest and northeast during summer (May−August) and autumn non-O3 episode days (September−November), respectively. Moreover, the contributions of super-regional, regional, oceanic and local air masses to the average O3 levels were 31–49%, 20–31%, 18–29% and 0–27%, respectively, during summer non-O3 episode days, while they were 29–56%, 19–37%, 15–24% and 0–31%, respectively, on autumn non-O3 episode days. The relatively low contribution of oceanic air may be attributed to the fact that the south/southeast winds from the South China Sea brought in clean oceanic air with less primary pollutants and thus led to lower O3 concentrations (Zheng et al., 2010). On the other hand, during high O3 days, super-regional, regional, and local air masses contributed 28–100%, 0–61% and 0–42% respectively to the O3 mixing ratios in summer, while the respective contributions were 33–100%, 0–56% and 0–39% in autumn. However, no contribution of oceanic air masses was found on high O3 days in summer and autumn. Overall, regional and super-regional air masses made the most significant contributions to the average O3 mixing ratio, followed by local and oceanic air masses, consistent with previous studies (Wang et al., 2009; Zheng et al., 2010). The results further demonstrated that regional and super-regional air pollution had notable influence on the O3 pollution in Hong Kong.

Fig. 8

Graphical illustration of O3 pollution in Hong Kong. The gray, green, blue and red areas represent the relative concentration of O3 from oceanic, regional, super-regional and local emissions, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Is photochemical O3 formation limited by VOCs, or NO or both?

Due to the complex O3 chemistry, photochemical O3 formation could be dominated by either VOCs or NO or both. As such, it is important to understand the mechanisms of O3 formation in a location. Moreover, since O3 is a secondary pollutant, the regional influence should therefore be considered. On a regional scale, Zheng et al. (2010) reported that the O3 production was controlled by VOCs in urban areas and possibly controlled by NO in the northern/northeastern rural areas in the PRD region. Locally, Zhang et al. (2007) and Cheng et al. (2010b) found that the O3 formation throughout Hong Kong was limited by VOCs, especially by reactive aromatics and some carbonyl compounds, and high NO concentrations suppressed O3 production. In this section, measurement data for a total of 115 days (i.e. 17, 15, 13, 27, 23 and 20 days in years 2005−2010, respectively) with the maximum hourly O3 mixing ratios above 80 ppbv were input into the OBM model to investigate the O3-precursors relationship at TC. Fig. 9 presents the average RIR values for different precursors on those 115 high O3 days. It is apparent that O3 production was generally VOC-limited at TC, indicating that reducing VOCs decreased the O3 formation and reducing NO could increase O3 levels. The anthropogenic volatile organic compounds (AVOCs) made the most significant contributions to the O3 formation, except for 2007 and 2009 when biogenic volatile organic compounds (BVOCs) had the highest contributions due to the high isoprene emissions in these two years. Among the top 10 VOC species, the average RIR value of isoprene was the highest, followed by aromatic compounds i.e. toluene and o-xylene, and alkenes i.e. propene and tran-2-butene (Fig. 10 ), revealing that the O3 formation in Hong Kong was controlled by a small number of VOC species.

Fig. 9

Average RIR (relative incremental reactivity) values for O3 precursors at TC.

Fig. 10

Average RIR values for individual VOC species at TC.

In the PTM-MCM model, another method was applied to evaluate the relative contribution of each VOC to O3 formation, in which the importance of each VOC to O3 production was ranked by POCP-weighted values (Cheng et al., 2010a). The POCP values were calculated by the PTM-MCM model, while the POCP-weighted values were calculated by combining the POCP value and emissions of each VOC (i.e. the emission rate of the VOC in Hong Kong (tonne yr−1) multiplies by its POCP value). The 15 most abundant VOC species accounted for 51.7% of the total VOC emission rates in the PRD region (Cheng et al., 2013). Among these species, isoprene, cis-2-pentene, 1,3,5-trimethylbenzene, acetaldehyde, 1,2,4-trimethylbenzene, 1,2,3-trimethylbenzene and propene had high POCP values, while toluene, benzene, ethene, isoprene had high emission rates, which are accounted for 6.2%, 5.8%, 5.5%, and 5.3% of the total emission rates, respectively.

After taking account into both the POCP and the emission amount of each VOC (POCP-weighted values), isoprene, ethene, toluene, formaldehyde, m-xylene, propene, acetaldehyde, 1,2,4-trimethylbenzene, o-xylene, 1-butene and ethylbenzene became the key precursors to photochemical O3 formation in Hong Kong (Cheng et al., 2013). However, some highly reactive species, such as cis-2-pentene, 1,3,5-trimethylbenzene and 1,2,3-trimethylbenzene, had relatively lower contributions to the O3 formation. This may be due to their low emissions, accounting for 0.1%, 0.5% and 0.4% of the total emission rates, respectively. In contrast, benzene and ethyne accounted for a relatively high percentage of the total VOC emissions (5.8% and 3.3%). Yet they had negligible contribution to the O3 formation because of their low reactivity. This feature suggests that the contribution of a VOC to the O3 formation is determined by the combination of its reactivity and emission.

Despite some variations, the results of both OBM and PTM-MCM models showed that some reactive VOCs including BVOCs i.e. isoprene, and AVOCs i.e. toluene, o-xylene and propene had the highest contributions to the O3 formation. Given that it is difficult to control BVOC emissions, the practical strategy to control O3 pollution is to effectively reduce AVOC emissions. In addition, POCP-weighted values calculated by PTM-MCM model suggest that the optimal strategy should also consider the emission quantity together with reactivity of individual VOCs when it is formulated and implemented.

Which emission sources are responsible for the volatile organic compounds in the atmosphere of Hong Kong?

Since photochemical O3 formation at TC was mostly VOC-limited, investigation of the characteristics of VOC source profiles and apportionments is the prerequisite for the formulation and implementation of O3 control strategies at TC in Hong Kong. Table 4 illustrates the source apportionment of VOCs at TC using the PMF model. It can be seen that the main VOC sources were solvent use (e.g. paint and varnish, adhesives and sealants), and household products, gasoline and diesel vehicular emissions, gasoline evaporation, liquefied petroleum gas (LPG) usage, biomass burning, biogenic emissions, and the petrochemical industry. Solvent usage made the greatest contribution to ambient VOCs at TC (41 ± 6 %, mean ± 95% confidence interval), followed by gasoline and diesel vehicular emissions (31 ± 8%) and a mixed source of gasoline evaporation and LPG usage (22 ± 3%). The results are in line with previous studies (Table 4). For instance, the contributions of vehicular emissions in this study (21–43%) were similar to previous studies (20–48%), except the study conducted by Lau et al. (2010) who reported the vehicular emissions of ∼70% in Hong Kong. In contrast, the percentage contribution of vehicular emissions in 2008–2010 obtained in this study was half that quantified in 2001–2003 (Guo et al., 2006, Guo et al., 2007), perhaps suggesting effective VOC control strategies such as utilizing cleaner diesel for buses in Hong Kong (http://www.epd.gov.hk/epd/english/environmentinhk/air/air_maincontent.html). On the other hand, the contribution of solvent usage in this study (about 30–56%) was consistent with the results found in previous studies (32–45%), and about twice of the study conducted in 2002–2003 (14–24%). The lower contribution of solvent usage to VOC emissions in 2002–2003 may be attributable to lower usage because of much fewer household, commercial and industrial activities caused by the severe acute respiratory syndrome (SARS) events in 2002–2003 in Hong Kong (Guo et al., 2011). Furthermore, results of this study and HKEPD emission inventory (EI) indicated that solvent usage in Hong Kong was still the major contributor to ambient VOCs. In this study, gasoline evaporation and LPG usage were sometimes identified as a mixed source. This mixed source contributed 20.4–27%, similar to the results found in 2001–2003 and 2006–2008 (Guo et al., 2006; Lau et al., 2010), suggesting the emission from LPG usage and gasoline evaporation had less change in recent years. Therefore, these results point out the importance of effectively controlling solvent usage and vehicular emissions in Hong Kong.

Table 4

Comparison of results with previous studies and emission inventories.

Factor	2005	2006	2007	2008	2009	2010	Sep 2002–Aug 2003	Sep 2006–Aug 2007	Fall 2007	2001	2001–2002	2002–2003	2007
Vehicle exhaust	43%	33.60%	32%	20.50%	25.30%	36.90%	69.8 ± 0.7%	69.5 ± 0.9%	48 ± 4%	39–48%	39%	48–65%	20%
Gasoline	21.50%	20.30%	21.50%	11.50%	13.30%	20.80%			21 ± 2%
Diesel	21.50%	13.30%	10.50%	9%	12%	16.10%			27 ± 3%
Gasoline evaporation	17.40%	a23.8%		a20.4%	a27%	a20.5%	4.4 ± 0.2%	5.4 ± 0.2%			14%	21–26%
LPG/natural gas usage			7.80%				18.1 ± 0.6%	27.6 ± 0.8%		11–19%	12%	15%
Paint/varnish/solvents	29.50%	41.30%	41.20%	55.80%	33.20%	48.20%	33.8 ± 0.3%	41.1 ± 0.1%	43% ± 2%	32–36%	35%	14–24%	75%
Industrial						4.40%	2.8 ± 0.1%	2+0.1%		5–9%		8–15%
Biomass/combustion	5.60%	1.32%			14.70%				9 ± 2%
Biogenic	0.10%	0.10%	19.10%	3.30%			2.20%	2.50%					0.2–2%
Aged VOC							27.6 ± 0.5%	23.8 ± 0.5%
Remarks	PMF	PMF	PMF	PMF	PMF	PMF	PMF	PMF	PMF	PCA /APCS	PCA /APCS	PCA /APCS	EIb
References	This study	This study	This study	This study	This study	This study	Lau et al., 2010	Lau et al., 2010	Guo et al., 2011	Guo et al., 2004	Guo et al., 2006	Guo et al., 2007	HKEPD, 2012c

Mixed source of gasoline evaporation and LPG usage.

EI, emission inventory.

HKEPD, 2012, http://www.epd.gov.hk/epd/english/environmentinhk/air/data/emission inve.html.

Application of the conceptual model – model verification

In the sections described above, a conceptual description for O3 pollution in Hong Kong was developed. During O3 episodes, the most frequent weather systems affecting Hong Kong were tropical cyclones over the East and the South China Sea (Scenario 1), followed by regional high-pressure systems (anticyclones) to the north over mainland China (Scenario 2), and low-pressure system (trough) to the south and east over the South China Sea (Scenario 3) (Fig. 11 a–c) (Huang et al., 2006; Guo et al., 2009). In this section, we conducted the model verification for four cases, i.e. 26 October 2007, 15 November 2008 and 04 June 2010 as examples for the high O3 episode scenarios, and 29 July 2010 as an example for non-O3 episode case.

Fig. 11

Weather Charts on (a) 26 October 2007, (b) 15 November 2008, (c) 04 June 2010 and (d) 29 July 2010.

Fig. 12 presents the diurnal variations of meteorological parameters for the four cases. It was found that there were some similarities in weather conditions at TC on the days of 26 October 2007, 04 June and 29 July 2010. First, the temperature and solar radiation were relatively high on these three days, which had daily maximum temperature of 30 °C with solar radiation of 806 W m−2, 29 °C with solar radiation of 805 W m−2, and 33 °C with solar radiation of 888 W m−2, respectively. Second, the relative humidity on these three days was comparable (p > 0.05). However, some differences were also found on these days. Firstly, a tropical cyclone was found over the East China Sea on 26 October 2007 (Fig. 11a). On 04 June 2010, a low-pressure system (trough) to the south and east was over the South China Sea (Fig. 11c), while an intense low-pressure system was found over Northern China and Hong Kong was in the front of the low-pressure ridge on 29 July 2010 (Fig. 11d). Secondly, the wind patterns were different on these three days. On 26 October 2007, the prevailing winds were southeasterly and northeasterly at night and northwesterly during daytime hours, while the dominant winds were southerly on 29 July 2010 with high wind speeds. However, the winds were calm (0.5–2 m s−1) on 04 June 2010 with northerly and westerly winds during daytime hours and easterly winds at night. Thirdly, the backward trajectories analysis revealed that air masses arriving at TC were caused by super-regional transport on 26 October 2007, while the air masses were mainly from the ocean on 29 July 2010 (data not shown), indicating that high O3 levels on 26 October 2007 (hourly peak value: 139 ppbv) and low O3 level (∼20 ppbv) on 29 July 2010 were attributed to the influence of different air masses. Indeed, the OBM modeling results suggested that super-regional transport contributed as high as 50% to the O3 pollution at TC on 26 October 2007. On the other hand, the conditions of high temperature, strong solar radiation, and the low wind speeds on 04 June 2010 created a relatively stable lower tropospheric layer, which was favorable to the O3 formation and accumulation at TC. This was confirmed by the OBM modeling results, which revealed that high O3 levels (i.e. peak value: 132 ppbv) on 04 June 2010 were mainly (90%) controlled by local formation.

Fig. 12

Diurnal variations of meteorological parameters on 26 October 2007, 04 June 2010, 15 November 2008 and 29 July 2010.

On 15 November 2008, there was an intensive high-pressure system over northern China, while Hong Kong was in the front of the high-pressure ridge. Due to the influence of this high-pressure system, more frequent northerly winds with higher speeds (maximum value: 6 m s−1) were observed on 15 November 2008. In addition, the temperature and solar radiation (daily maximum value: 730 W m−2) on 15 November 2008 were lower (p < 0.05) and the relative humidity was comparable to those on 29 July 2010. This implied that the O3 levels could be lower on 15 November 2008 than on 29 July 2010. However, the O3 mixing ratio was actually higher on 15 November 2008 (hourly peak value: 123 ppbv). Further inspection showed that the discrepancy between O3 levels on 15 November 2008 and 29 July 2010 was also attributed to the influence of different air masses. The higher O3 levels on 15 November 2008 were caused by the regional and super-regional transport. Backward trajectory analysis demonstrated that regional and super-regional air masses were frequently observed on 15 November 2008, and the OBM modeling simulations further confirmed that 90% of O3 was caused by regional/super-regional transport on that day.

In summary, the above discussion indicated that tropical cyclone was mostly conducive to the occurrence of high O3 mixing ratios. In addition, meteorological conditions such as high temperature, intense solar radiation, low relative humidity and wind speed were favorable to photochemical O3 formation. Furthermore, polluted continental air masses brought by the northerly winds facilitated the O3 production in Hong Kong. Nevertheless, it should be noted that these conditions were necessary but insufficient for the occurrence of O3 episodes.

Conclusion

A conceptual model of O3 pollution in Hong Kong was developed in this study. Results suggested that tropical cyclone was mostly conducive to the occurrence of high O3 mixing ratios, while conditions such as high temperature, intense solar radiation, low relative humidity and wind speeds and northeasterly and/or northwesterly prevailing winds were favorable to photochemical O3 formation. In addition, super-regional and regional transport had significant influence on high O3 levels in Hong Kong. The simulation of OBM and PTM-MCM models revealed that photochemical O3 formation was generally VOC-limited in Hong Kong, and solvent usage and vehicular emissions made the most significant contributions to ambient VOCs. It should be noted that the relative contributions of local, regional and super-regional air masses to the O3 formation on O3 episode days were extracted from the back trajectory analyses, even when the air movement was stagnant on some O3 episode days, which could lead to uncertainties on the relative contributions.

Implications for ozone control measures

By considering the meteorological conditions, atmospheric chemistry and physics, and source apportionment of O3 precursors, a conceptual description of O3 pollution problem at TC in Hong Kong was presented above. However, some details remain to be thoroughly understood.

A key factor for the occurrence of O3 episodes in Hong Kong is the influence of tropical cyclones which cause subsidence, stagnation air and inversion layer. However, the mechanisms of such influence are not fully understood.

Photochemical O3 formation was generally VOC-limited and related to a small number of VOC species in Hong Kong, and solvent usage and vehicular emissions are the two major VOC sources. It appears that an effective control measure on the emissions of solvent usage and vehicles is an optimal strategy for controlling O3 pollution in Hong Kong. In addition, the optimal strategy should also consider the emission quantity together with reactivity of individual VOCs when it is formulated and implemented.

Many VOC sources are located in the PRD region and regional transport from the inland PRD region has significant influence on the amount of air pollutants in Hong Kong (Tang et al., 2007; Guo et al., 2009). As such, more concurrent field measurements should be conducted in these two closely interactive areas. In addition, air quality control strategies formulated in Hong Kong should consider the emissions from distant sources together with local sources.

In Hong Kong, the combination of the coastline and the mountains gives a terrain with many complex physical features. The role of sea-land breezes in air pollution transport has been well studied previously (Ding et al., 2004). However, there are relatively few studies on mountain-valley breezes in Hong Kong, though it is very important to air pollution transport in Hong Kong.

Although remarkable improvements in the VOC emission inventory and VOC measurements have been made in Hong Kong, significant uncertainties still exist in the source profiles and apportionments of VOC data. Hence, further survey on the VOC emission sources and accurate VOC source profile measurements and analyses are essential to better understand the VOC emissions from different sources in Hong Kong and its surrounding areas i.e. inland PRD region, to provide more reliable results on VOC sources and species which contribute the most to photochemical O3 formation in Hong Kong.

Though photochemical O3 formation is generally VOC-limited in Hong Kong, the influence of other highly reactive chemicals such as HONO, PAN, H2O2 and other reactive oxidants on the O3 formation should not be ignored. Besides VOCs, the characteristics of other precursors, i.e. NO and products, i.e. particles, are required in order to better understand the specific atmospheric chemistry. Flux measurements of O3 and its precursors over different areas, i.e. Hong Kong and inland PRD, under different meteorological conditions, i.e. anticyclones and cyclones, mixing heights and transport processes are also necessary.

Since the conceptual model was developed based on the data collected at one site, i.e. TC, it is suggested that this model should be further confirmed and improved by using data from other sites in Hong Kong.

Disclaimer

The content of this paper does not necessarily reflect the views and policies of the Hong Kong Special Administrative Region (HKSAR) Government, nor does mention of trade names or commercial products constitute an endorsement or recommendation of their use.