PM10-bound polycyclic aromatic hydrocarbons: Concentrations, source characterization and estimating their risk in urban, suburban and rural areas in Kandy, Sri Lanka

Atmospheric Environment 45 (2011) 2642e2650

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PM10-bound polycyclic aromatic hydrocarbons: Concentrations, source characterization and estimating their risk in urban, suburban and rural areas in Kandy, Sri Lanka A.P. Wickramasinghe a, *,1, D.G.G.P. Karunaratne a, R. Sivakanesan b a b

Department of Chemical and Process Engineering, Faculty of Engineering, University of Peradeniya, Sri Lanka Department of Biochemistry, Faculty of Medicine, University of Peradeniya, Sri Lanka

a r t i c l e i n f o

a b s t r a c t

Article history: Received 4 January 2011 Received in revised form 24 February 2011 Accepted 26 February 2011

Kandy, a world heritage city, is a rapidly urbanized area in Sri Lanka, with a high population density of w6000 hab km
2. As it is centrally located in a small valley of 26 km2 surrounded by high mountains, emissions from the daily flow of >100,000 vehicles, most are old and poorly maintained, get stagnant over the study area with an increased emphasis on the associated health impacts. Particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) are considered to be major pollutants in vehicular emissions; while PAHs account for the majority of mutagenic potency of PM. The purpose of the current study is to determine the 8 h average concentrations of ambient PM10 PAHs at twenty sites distributed in the urban, suburban and rural Kandy. Samples on glass micro fibre filters were collected with a high volume air sampler from July/2008 to March/2009, prepared through standard procedures and analyzed for PAHs by high performance liquid chromatography with ultraviolet visible detection. Further, the type and strength of possible anthropogenic emission sources that cause major perturbations to the atmosphere were assessed by traffic volume (24 h) counts and firewood mass burnt/d at each sampling site, with the subsequent societal impact through quantitative cancer risk assessment. The results can serve as a base set to assess the PAH sources, pollution levels and human exposure. Mean total P concentrations of 16 prioritized PAHs ( PAHs) ranged from 57.43 to 1246.12 ng m
3 with 695.94 ng m
3 in urban heavy traffic locations (U/HT), 105.55 ng m
3 in urban light traffic locations, 337.45 ng m
3 in suburban heavy traffic stations, 154.36 ng m
3 in suburban light traffic stations, 192.48 ng m
3 in rural high firewood burning area and 100.31 ng m
3 in rural low firewood burning area. The mean PM10 concentration was 129 mg m
3 (55e221 mg m
3); which is beyond the WHO air quality standards. Polycyclic aromatic hydroP carbon signature and the spatial variation of PAHs concentration with the type and strength of sources were applied to identify the sources of emission. A very similar and consistent source apportionment was obtained, which revealed that in the urban and suburban areas automobile emissions are the predominant daytime P source of PAHs, but in suburbs with a low regression co-efficient between PAHs and traffic volume indicating the impact of factors other than traffic volume. While domestic firewood burning is the major in rural areas, its P commercial use has played a significant role in U/HT sites, with strong correlation to PAHs. Current human exposure to PAHs can give rise to an increased cancer risk in Kandy in the coming decades, as denoted by the excess lifetime lung cancer risk of 3.31  10
3. Ó 2011 Elsevier Ltd. All rights reserved.

Keywords: Polycyclic aromatic hydrocarbons (PAHs) Particulate matter (PM) Source apportionment Vehicular emissions Urban air quality Cancer risk

1. Introduction Particulate matter (PM) is believed to be the most hazardous of ambient pollutants; attributable to the complexity in particle size

* Corresponding author at: Veterinary Research Institute, Gannoruwa, Peradeniya, Kandy KY 20400, Sri Lanka. Tel.: þ94 779311926; fax: þ94 812234305. E-mail address: [email protected] (A.P. Wickramasinghe). 1 Veterinary Research Institute, Gannoruwa, Peradeniya, Sri Lanka. 1352-2310/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2011.02.067

and chemical composition. The particles with an aerodynamic diameter <10 mm (PM10) can deposit and accumulate in the respiratory system representing a significant threat to human health, which has been a field of continuous research and evidence for the risk involved (U.S. EPA, 1996; WHO, 2000; Hauser et al., 2001). Further, greater mutagenic and cytotoxic effects were detected in connection with smaller particle size fractions in bioassays (Hsiao et al., 2000; Kawanaka et al., 2004) and polycyclic aromatic hydrocarbons (PAHs) were responsible for the majority of

A.P. Wickramasinghe et al. / Atmospheric Environment 45 (2011) 2642e2650

mutagenic potency (Hannigan et al., 1998). Since many of these PAH compounds have been classified as possible or probable carcinogens (IARC, 1983), for example benzo[a]pyrene (B[a]P) has been directly linked to lung cancer through its selective adducts along a tumor suppressor gene (Denissenko et al., 1996), there is widespread interest in analyzing and evaluating the PAHs in atmospheric environments.

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Although PAHs can be formed through natural sources as well, the anthropogenic PAH sources, mainly the incomplete combustion or pyrolysis of organic material, such as fuel oil, petroleum gas, coal and wood, and tobacco smoking are by far the largest contributors of PAHs to the environment (Grimmer, 1993). PAHs emitted in gaseous form may be condensed into the particulate phase mostly with PM2.5 (Sirce et al., 1987) and may later accumulate on larger

Fig. 1. The location of sampling points in Kandy.

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particle sizes (Miguel et al., 2004); and thus could be present in both particulate (p-PAHs) and gaseous form (g-PAHs). Since the composition of PAHs in any phase changes significantly according to their emission sources, that feature can be used to identify possible emission sources (Barale et al., 1991; Venkataraman et al., 1994) which in turn serves as the basis for exposure regulations through emission control and for public health measures. Kandy, the second capital city in Sri Lanka, is well famed for the temple of the sacred Tooth Relic of the Lord Buddha and designated as a city of world heritage. With the urban overspill, it experiences ‘inner-city’ and ‘through’ traffic related problems by both volume and density. The geographic features of Kandy, a small plateau surrounded by a line of high mountains, possibly create thermal inversions; hence air get re-circulated in the city’s atmosphere. Thus, urban and suburban areas in Kandy are likely to be highly polluted with contaminants emanating from vehicles and being PAHs is major constituent and product of incomplete combustion of fuel, PAHs pollution is of higher concern. Though there is a great possibility for the domestic firewood combustion also to complicate the issue, there are no significant industrial emissions around this city. The importance of each source could have varied among different environmental localities, possibly with the land-use pattern. The current study was implemented with the major objective of assessing the exposure levels of all 16 US EPA prioritized PAHs of respirable PM10 in ambient air, over urban-commercial, suburbanmixed and rural-residential areas in Kandy. The PAH compounds under study were: naphthalene (Nap), acenaphthylene (Acpy), acenaphthene (Acp), fluorine (Flu), phenanthrene (Phe), anthracene(Ant), fluoranthene (Fl), pyrene (Py), benzo(a)anthracene (B[a] An), chrysene (Chry), benzo(b)fluoranthene (B[b]F), benzo(k)fluoranthene (B[k]F), benzo(a)pyrene (B[a]P), dibenz(a,h)anthracene (D [ah]A), benzo(g,h,i) perylene (B[ghi]Pe) and indeno(1,2,3-c,d)pyrene (I[123-cd]P). The reported total number of PAHs, their individual intensity and mass concentration of the given 16 PAHs (abbreviated as SpPAHs onwards) play important roles in exposure and risk assessment, while the PAHs size distribution has an impact on the site and type of pathophysiological lesions in the exposed personnel. Since the carcinogenic PAH concentrations may be taken as an ‘index’ for the biologically active (mutagenic, genotoxic, embryotoxic) components in air particulate samples, their high-quality monitoring data may be useful for related epidemiological studies. Further, the suspected major sources of PAH emissions were quantified by parallel physical assessments and were correlated with PAH results to reveal the source-effect relationship. Moreover, source allocation of PAHs is attempted using established data on source-specific exposure profile. All these applications may be used for further planning and management activities on improving the air quality and human health in Kandy and similar cities. 2. Experimental methodologies 2.1. Site description Kandy is located inland at w500 m above mean sea level and Kandy municipal council (KMC) region expands over w26 km2. According to the state Department of Meteorology, Kandy has on average; day time ambient temperature (T) of 27.6e31.8  C, monthly rainfall of 52.4e398.1 mm and day time relative humidity (RH) of 63e83%, thus tropical climatic condition. Population has grown to >150,000 occupying the same space; density is estimated to be w6000 persons km
2 which is >10 fold of the country’s figure as per National Census and Statistics 2001. In addition, the city attracts around 100,000 persons per day adding to a total city

population of >250,000 during the course of the day. Building establishments have also expanded, limiting the forest coverage and the ground level free space in and around the city. The estimated current 24 h traffic flow entering and leaving the city through four main entrance roads is 1,06,000; hence result in exceptionally high strength of vehicular emissions over a limited land area of w 4 km2 in the main city core. A total of twenty sampling sites were selected (Fig. 1) as to be representative of the whole study area for accurate and generalized exposure data of the targeted population. As per the ‘Guidance on Exchange of Information’ for measuring Ambient Air Pollution given in 97/101/EC and 2001/752/EC, they were basically classified into three major categories based on the local environmental features including type of area where they are located, land use pattern and demographical characteristics: ‘Urban-Commercialized areas’ [U-C],8 sites; ‘Suburban-Mixed areas’ [S-M], 7 sites; and ‘Rural- Residential areas’ [R-R], 5 sites. They were further classified on the type of possible main sources of emission as ‘Traffic’ [T] or ‘Background stations’ [B], according to the data on the prevailing sources in a particular area. While the traffic data were obtained from surveys conducted by the Faculty of Engineering of University of Peradeniya and also traffic counts under the current study, the required information on the other two main sources of PAH emission, i.e. total firewood combustion (kg d
1) and open burning of waste (number of households), were collected through ‘Interviewer-Administered Questionnaire’ in the surrounding area of w50 m in radius at each sampling location and are summarized in Table 1. Additional meta-data (e.g. 24 h traffic volume, firewood mass/d) were used for inter-comparisons of the stations as defined by the Table 1 and related assessments of air quality. The air quality in [U-C] and [S-M] areas were predominantly affected by road transport and they were defined as Urban Heavy Traffic [U/HT] (>15,000 vehicles d
1), Urban Light Traffic [U/LT] (2000 < vehicles d
1 <15,000), Suburban Heavy Traffic [S/HT] (>15,000 vehicles d
1) and Suburban Light Traffic [S/LT] (2000 < vehicles d
1 <15,000). The vehicular traffic in the [R-R] area, relative to those in [U-C] and [S-M] areas were very low or negligible; hence come under background stations. Although the daily average domestic firewood combustion in [R-R] zone was

Table 1 24 h Traffic flow, along the adjacent road at each traffic station and quantitative firewood use (kg d
1) within the area of w50 m radius at each site. Type and characteristics of area

24 h traffic volume

Firewood combustion (kg d
1)

Definition code

1/U-C 2/U-C 3/U-C 4/U-C 5/U-C 6/R-R 7/R-R 8/R-R 9/U-C 10/S-M 11/R-R 12/U-C 13/S-M 14/S-M 15/S-M 16/S-M 17/U-C 18/R-R 19/S-M 20/S-M

23,000 69,83 25,376 30,208 18,000 NGa NGa NGa 25,061 6155 NGa 21,018 5039 23,832 37,337 23,950 20,637 NGa 5116 30,341

309 0 0 358 220 18.3 65.6 17.51 43.7 0 81.6 0 32.3 40.1 28.3 88.81 97.3 144.3 47.6 25

1/U-C/T[HT]/HF 2/U-C/T[LT] 3/U-C/T[HT] 4/U-C/T[HT]/HF 5/U-C/T[HT]/HF 6//R-R/B[LOF] 7/R-R/B[HF] 8/R-R/B[LOF] 9/U-C/T[HT]/LOF 10/S-M/T[LT] 11/R-R/B[HF] 12/U-C/T[HT] 13/S-M/T/[LT]/LOF 14/S-M/T[HT]/LOF 15/S-M/T[HT]/LOF 16/S-M/T[HT/HF 17/U-C/T[HT]/HF 18/R-R/B[HF] 19/S-M/T[LT]/LOF 20/S-M/T[HT]/LOF

a

NG; negligible.

A.P. Wickramasinghe et al. / Atmospheric Environment 45 (2011) 2642e2650

higher than that in [S-M] area, quantitatively the highest firewood use was observed in some [U-C] sites. The combustion of waste was significant in all residential zones. All the background sampling sites were further sub defined primarily on quantitative firewood use; Rural Background-High Firewood [R/B/HF] (>50 kg d
1) and Rural Background-Low Firewood [R/B/LOF] (15e50 kg d
1). The meteorological condition prevailed during sampling were as follows; the ranges of T, RH and wind speed were 24.5e33.07  C, 45.57e85% and 0.31e2.32 ms
1, respectively, with the lower end of T and RH ranges deviated more compared to the general values stated above in 2.1. 2.2. Air sampling Eight hours (from 9 a.m.) samplings for PM10 bound PAHs in ambient air were performed at the twenty selected locations (with 95% of week days sampling) with a high volume sampler (HVS) e Respirable Dust Sampler e (Envirotech Model APM 460) equipped with a 10 mm cut-off cyclone, from July/2008 to March/2009. Sample collection, preparation and analysis for PAHs were performed according to the modified and optimized procedure developed by Wickramasinghe and Karunaratne (2008) based on US EPA Compendium Method TO-13A (U.S. EPA, 1999) and PM10 measurement was done based on the standard procedure of European Committee for Standardization (CEN), standard EN 12341:1998; a gravimetric filter-based method. The sampler was located at least 2 m from any obstacle and at a 1.5 m sampling height to simulate the human breathing zone. Motor brushes and the manometer of the HVS were set prior to sampling and the sample module loading was done in a controlled environment. The particulate matter fraction of the ambient air was retained on the glass micro fibre filter paper (Whatman EPM 2000; 20.3  25.4 cm). Preceding sampling, the filters were cleaned by thermal treatment (at 400  C for 8 h) and weighed in an analytical balance after 24 h conditioning in a darkened desiccator at constant temperature (23e25  C) and RH conditions (40e50%); wrapped in pre-treated aluminum foil and sealed in sample bag until field use. The operational flow rates were recorded 0.5 or 1 hourly for the average value. The loaded filters were folded in half twice, identified, wrapped and transported to the laboratory under the cold chain. They were similarly conditioned and weighed for gravimetric determination of PM10 mass concentration prior to the extraction procedure. 2.3. Sample preparation and analysis of PAHs Filter papers were processed on the following day of sampling by the Soxhlet extraction with dichloromethane for 18 h, concentrated until dryness within 15e20 min using a rotary evaporator, final solvent exchange with 1 ml of acetonitrile and subjected for clean-up methods. Extracts were purified using prior deactivated and conditioned solid phase extraction cartridges (Supelclean ENVI-18; Base: Silica; Retention Mechanism: Reversed Phase Polymerically bonded Octadecyl [17% C]) to minimize subsequent matrix interferences. The High Performance Liquid Chromatographic equipment [HPLC] (Agilent, Germany: HP 1100 Series Chemstation) was equipped with Quaternary Gradient Pumping system (Flow Precision < 0.3% RSD; Flow range Set points from 0.001 to 10.0 ml min
1 in 0.001 ml min
1 increments; Composition precision < 0.20% SD at 0.2 and 1 ml min
1), Manual Injector, Column, UVeVis Absorption Detector (Double-beam photometer with Deuterium lamp; Linearity >2AU upper limit), and Recorder/Data System. The determination of PAHs was accomplished by Reversed Phase High Performance Liquid Chromatography with ultraviolet

2645

visible detection (HPLC/UV) at wavelength of 254 nm; within 14 days of extraction (norm by TO 13A is 40 days); at ambient temperature (w25  C); 20 ml injection manually (with unique rate and art of injection for maximum reproducibility); the chromatographic separation was performed on a C8 column (ZORBAX Eclipse XDB-C8; 250 mm  4.6 mm  5 mm; octylsilyl polymeric bonded phase) with the optimized analytical conditions of an Acetonitrile [ACN]: De-ionized water gradient elution of 50:50, ramp to 100:0 within 45 min at a flow rate of 0.8 ml min
1, and the column was equilibrated with the initial conditions before the next injection. Stock standard solution: EPA 610 PAHs Mixture (Supelco, Bellefonte, PA, USA) with 100e2000 mg ml
1 concentrations of 16 PAHs in methanol: methylene chloride (50:50) was used for the multilevel external calibration of HPLC/UV and all 16 calibration curves were linear with perfect positive relationship where correlation of coefficient (r) was 0.99 for 15 compounds and the least 0.97 for chrysene, which indicated the high accuracy of the quantification of environmental samples. The results of PAH would be precise up to two decimal places. Peak identification was based on Retention Time Window [RTW] for each species: where the retention times were established with five calibration solutions, each at least with five runs and the reproducibility of retention times were between 0.0941 and 0.1962 min and were integrated by Enhanced Auto-Integration software. Quantification was done based on the external standard procedure (which depicts the relationship between the response area and the concentration). 3. Results and discussion 3.1. PM10 and PAHs concentrations The 8 h average concentrations of PM10 and total PAHs bound to PM10 (Sp-PAHs), i.e., the sum of concentrations of individual species, as a breakdown in the major categories of the study area P are given in Table 2. In general, the mean and median values of p
3
3 PAHs were 378.40 ng m and 276.83 ng m respectively, hence a positively skewed frequency distribution. Within the U/HT category, Sp-PAHs along Kandy city’s roadways ranged from 443.53 to 1246.12 ng m
3 (mean 695.94 ng m
3). Compared with overseas cities, concentrations of Sp-PAHs in Kandy were higher than those of most of the coastal cities reviewed such as Naples, Italy (Caricchia et al., 1999), Athens (Mantis et al., 2005), Santiago (Romero et al., 2002) etc.; but are comparable to reported highest roadways data of 50e910 ng m
3 in Mexico City (Marr et al., 2004) and of 912 ng m
3 in Tainan, Taiwan (Sheu et al., 1997). The site 9/U-C/T[HT], located by one of highways with the heaviest traffic congestion, was denoted as the most polluted area

Table 2 P Average concentrations of p-PAHs and PM10 in the major categorized areas in Kandy. Area

Sp-PAHs (ng m
3)

SPM10 (mg m
3)

Overall U/HT U/LT S/HT S/LT R/B/HF R/B/LOF

378.4 (57.43e1246.12)a 695.94 (191.05e1246.12)a 105.55b 337.45 (181.75e505.85)a 154.36 (57.43e263.00)a 192.48 (111.28e291.02)a 100.31 (98.24e102.39)a

129 167 86b 143 104 90 83

a

(55e221)a (92e221)a (117e153)a (82e126)a (55e134)a (65e101)a

Values in parentheses indicate the range. Sampling sites were selected as to be representative of the whole study area, from all environmental localities of U-C, S-M and R-R areas. Over the comparison of the stations based on the possible sources of emissions and additional meta-data, only site 2 was revealed under U/LT category; hence, no range could be calculated. b

A.P. Wickramasinghe et al. / Atmospheric Environment 45 (2011) 2642e2650

Fig. 2. Relationship between concentrations of PM10 and

P

p-PAHs.

However, 8 h time average PM10 concentrations over the whole study area and especially heavy traffic affected stations in a nearly one year period falls within or beyond the WHO recognized range of 101e169 mg m
3 for ‘Most Polluted World Cities by PM10’ given in World Development Indicators-2007. Hence PM10 concentration in Kandy to exceed the WHO guided annual mean of 20 mg m
3 is of high probability. A significant positive correlation (r ¼ 0.9) was found between the levels of PM10 and Sp-PAHs in the air (Fig. 2). Being PAHs are primary anthropogenic compounds, such correlations indicated that PM10 concentrations had resulted essentially from primary anthropogenic emissions, with marginal inputs consisting of natural aerosol. It was in good agreement with the very high carbonaceous fraction of PM10 as indicated by the colorimetric index of filter papers during this study. Since these results suggested that sources of PM10 and PAHs in the air were largely similar; the control of PM10 was an effective way to decrease the PAHs level in the air. The colorimetric index of filter papers indicated that 75% of the analyzed samples were built on soot with high levels of Sp-PAHs (175.12e1246.12 ng m
3), while 30% at U/HT sites was at the upper extreme (>443.53 ng m
3) and seen as ‘jet black’. It shows that PAHs in urban air are primarily associated with soot particles as

Sampling area Fig. 3. Percentage of PAHs on PM10.

R/B/LOF

R/B/HF

S/LT

S/HT

U/LT

U/HT

0.50% 0.45% 0.40% 0.35% 0.30% 0.25% 0.20% 0.15% 0.10% 0.05% 0.00% Overall

in Kandy in terms of p-PAHs (1246.12 ng m
3)and PM10 (221.70 mg m
3) concentration impressing the reality. The effect of lateral deviation was seen along the same road at 17/U-C as low P p-PAHs of 191.05 ng m
3. The second highest concentrations (1198.16 ng m
3 and 201.66 mg m
3, respectively) were reported in 4/U-C with extra large traffic flow (at the city center), attributed to the usual Saturday heavy traffic due to additional vehicles entering the city for commercial, recreational and religious reasons. Site 4/UC/HT is a one-way road with four lanes while 9/U-C/HT is a twoway road with two lanes. Usually, the counter-flow of the traffic movement creates high air turbulence and facilitates dispersion of pollutants, which can strongly reduce the concentration of PAHs. Nevertheless, at site 9/U/HT the significantly lower vehicle speeds may produce and emit massive amounts of PAHs, while slow vehicular movement and the narrowness of the road, which seen as a ‘traffic tunnel’ can limit air dispersion; hence increased atmospheric PAH concentrations. The large open area at 12/U/HT offer the advantage of pollutant dispersion over the adjacent Kandy Lake; hence low Sp-PAHs. On the other hand, in the U/HT group, perfectly linear co-variations of Sp-PAHs against the quantitative daily firewood use were observed: mean Sp-PAHs in F-VH (w296 kg d
1) stations was 869.85 ng m
3 while that in F-LO and F-H area (w71 kg d
1) was 586.74 ng m
3 which further reduced to 454.89 ng m
3 over stations with no firewood use. Although the proportionate contribution of each source into the Sp-PAHs mass in urban heavy traffic area cannot be decided solely based on the data of the current study, more or less similar significant contribution from both traffic and firewood combustion was observed. The mean Sp-PAHs in S/HT areas (337.45 ng m
3) was much lower to that in U/HT area (695.94 ng m
3). In 13/S-M, Sp-PAHs of 142.67 ng m
3 showed the concurrent effect exerted by both lateral and horizontal gradients on air toxic concentrations relative to the central element. The above results very clearly indicated the incomplete correlation stands between the traffic volume and SpPAHs, while the traffic density may be highly influential, the role of tree borders and spacious surroundings in the vicinity in lowering the Sp-PAHs and PM10 concentrations has been significant; suggesting their implications in ‘Echo’ urban planning and development. Many scientists (Matzner et al., 1981; Matzner, 1984) have observed similar ‘green-life-effect’. The site 16/S-M/T[HT]/HF, located amidst a high dense residential area, has higher Sp-PAHs of 505.85 ng m
3 relative to the low firewood burning sites in the same S-M/HT category; which reflected the influence of domestic pollution. Among the R-R areas, the Sp-PAHs in high firewood group varied from 111.28 to 291.02 ng m
3 (mean: 192.48 ng m
3), while that in low firewood group averaged to100.31 ng m
3 (98.24e102.38 ng m
3); hence the P average p-PAHs levels over background stations in Kandy were exceptionally higher to classical rural areas in other countries. The criteria pollutant PM10 concentration (mg m
3) ranged between 55e221 with a normal distribution and nearly equal mean (129 mg m
3) and median (130 mg m
3) values in overall study area; further with the top range 92e221 mg m
3 in U/HT and secondly 117e153 mg m
3 in S/HT areas. Hence the urban heavy traffic group, attributed principally by automobile emissions and significant contribution from firewood combustion as well, was the most polluted area under study and could be declared as ‘Air Toxic Hot Spots’ in Kandy. Since no ambient air PAH studies in the country and 8 h PM10 studies in Kandy have been carried out so far; no area specific comparative data assessment could be made. In Sri Lanka, under the current National Environmental (Ambient Air Quality) Regulations-1994, PAHs are not regulated, but since 2008 with a new amendment PM10 to be controlled as maximum permissible 24 h mean of 100 mg m
3; which seems to be rather lenient.

% of PAH in PM10

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U/HT

U/LT

S/HT

S/LT

B(a)An

Overall average

Py

A.P. Wickramasinghe et al. / Atmospheric Environment 45 (2011) 2642e2650

R/B/HF

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R/B/LOF

500

Average Concentration 3 (ng/m )

450 400 350 300 250 200 150 100 50 I(123-cd)P

B(ghi)Pe

D(ah)A

B(a)P

B(k)F

B(b)F

Chry

Fl

Ant

Phe

Flu

Acp

Acpy

Nap

0

16 PAHs in Particulate Phase Fig. 4. Distribution of average concentrations of individual p-PAHs among groups.

observed by Butler and Crossley (1981) too. It was supplemented with the significantly high percentage of PAHs in PM10 mass (0.122%e0.387%) detected, with R/B/LOF and U/HT areas were at the two ends, respectively (Fig. 3). The higher PAH percentage (i.e., U/ HT, R/B/HF, S/HT) may be attributed to high PAH emission rates; hence both active vehicles fleet and wood burning stoves in Kandy were identified as ‘Heavy PAH Polluters’. 3.2. Variation of individual PAHs concentrations The large variation seen among the breakdown of PAHs concentrations (Fig. 4) was expounded by the differences in the sources and strength of emissions, the meteorological conditions and topography influencing the intra and inter matrices dispersion and finally the atmospheric photochemistry which may interfere with the stability of the original PAHs profile. The figure shows that

generally 2e3 ring PAHs were detected in very high concentrations (Nap >Acp > Acpy and Flu) with the MMW Chry and HMW BFs and B[a]P, which referred basically for diesel and then for domestic wood combustion (Li and Kamens, 1993; Tavares et al., 2004). The heaviest PAHs (D[ah]A, B[ghi]Pe, I[123-cd]P) were found to be relatively the least abundant. The highest levels for the most of 16 PAHs were reported in the U/HT group. Benzo(g,h,i)perylene was identified as the most profuse PAH compound over the PAH mix of 3 ring (Acp, Flu, Phe, Ant), 4 ring (Fl, Py, Chry) and 5 ring (B[a]P, D [ah]A, B[ghi[Pe) compounds which have spread more copiously than other PAH species, over the study area. Benzo[a]anthrecene, usually indicative for petrol cars with out or ill-functioning catalytic converters (Manoli et al., 2004), was found in high concentrations at U/HT stations. Very high mean concentrations of indicator carcinogen B[a]P (38.05 ng m
3) from all sources urge for control of PAHs pollution. Importantly, the 100% incidence and

Fig. 5. Percentage contribution of different MW groups of PAHs over the all sampling stations.

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high level (7 ng m
3) of D[ah]A (with the highest carcinogenicity) in residential grouping indicated the gravity of the health hazard enforced.

The molecular composition of the particulate phase was primarily formed by LMW and HMW PAHs; 2e3ring 57% (5e82%), 4ring 18% (0e31%) and 5rings 26% (9e64%) (see Fig. 5). LMW PAHs showed the widest variation over the study area; hence, irrespective of the source of emission the most active fraction has been the 2e3 ring PAHs. In traffic affected areas with no (e.g. U/LT) or low firewood combustion (e.g. S/HT/LOF) the percentage of HMW PAHs was high while in high firewood burning areas (e.g. U/ HT, S/HT/HF, R/B/HF) HMW fraction was relatively low and constant (Fig. 6). This picture would give a deep insight for further research and control strategies.

Acpy-Py% Chry+BFs%

90

% Contribution in particulate phase

3.3. Distribution of p-PAHs on molecular weight basis

Nap% Chry% B(ghi)Pe%

80 70 60 50 40 30 20 10 0

Fig. 6. Average molecular composition of p-PAHs over major areas.

1200 1000 800 600 400 200 0 1/U/HT 3/U/HT 4/U/HT 5/U/HT 9/U/HT 12/U/HT 17/U/HT 2/U/LT 14/S/HT 15/S/HT 20/S/HT 16/S/HT/HF 10/S/LT 13/S/LT 19/S/LT 7/R/HF 11/R/HF 18/R/HF 6/R/LOF 8/R/LOF

The ratios of individual PAH species have been a common diagnostic tool to identify the origin of PAHs in ambient air (Papageorgopoulou et al., 1999; Guo et al., 2003); but with basic limitations. As PAH ratios have been established mostly for single sourced samples while environmental samples contain PAHs from mixed sources (Yunker et al., 2002), the indicator PAHs of a particular source are unlikely to dominate other contributory sources. Therefore qualitative source apportionment (not quantitatively because of different emission rates) was performed on the average ratio of each PAH measured with respect to Sp-PAHs using specific PAHs {(Nap), (Chry), (B[ghi]Pe)} or PAH groups {(S from Acpy to Py), (Chry þ B[b]F þ B[k] F)}; and the variations in their concentration at all the sampling stations as summarized by U/HT, U/LT, S/HT, S/LT, R/ P B/HF and R/B/LOF areas are given in Fig. 7, as a contrast to p-PAHs concentrations. Fig. 7 shows strong co-variations at the highest proportion between Sp-PAHs and [Nap/Sp-PAHs], [SAcpy- Py/Sp-PAHs] during the overall sampling period in U/HT area. Therefore, emissions from combustion or vaporization of fuel oil (diesel predominant than gasoline and engine oil) were primarily sorted out (Harrison et al., 1996; Tavares et al., 2004); which further suggested the poor maintenance of vehicles. However, as this area has been marked with very high rate of commercial firewood burning too;

Total p-PAHs (ng/m3)

1400

3.4. Identification of source of PAHs

Sampling station Fig. 7. Relative percentages contribution of marker PAH species in the whole study area.

wood smoke may be the major source of naphthalene emissions (U.S.E.P.A., 2006). Further, [Chry þ BFs/Sp-PAHs] and [Chry/SpPAHs] were found to run parallel to each other, indicating both the diesel and firewood emissions, but deviated upwards to co-vary with [Acpy-Py/Sp-PAHs] at non-firewood burning stations to be specific for diesel emissions (Li and Kamens, 1993). The contribution of [B[ghi]Pe/Sp-PAHs], hence gasoline emissions (Combet et al., 1993; Marr et al., 1999) was nearly constant and the least. Furthermore, the relationship between U/HT Sp-PAHs and traffic volume (24 h) was strong (r ¼ 0.8 excluding site 5) and linear, while that with very high level of firewood use (kg d
1) was perfect. Therefore, as per the PAH signature, while the automobile emissions (mainly diesel) have been the principal source for Sp-PAHs over the U/HT category, it has been equally contributed by substantial firewood burning at certain commercial stations. In U/ LT area, the elevated fractions of [Chry þ BFs/Sp-PAHs], [Chry/SpPAHs] and [SAcpy-Py/Sp-PAHs] clearly indicated the diesel emissions; while the gasoline influence, shown by the highest proportion (10%) of B[ghi], was relatively higher. No co-behavior between criterion PAH ratios and Sp-PAHs were found in S/HT areas, indicating the vast difference in the additional factors influencing the production and the atmospheric stability of PAHs, due to the diverse nature of the landscape morphology. Nevertheless, the emissions from diesel engines were the most significant, with minor impact from firewood, which were marked by higher fraction of [SAcpy-Py/Sp-PAHs] and a moderate level of [Chry þ BFs/Sp-PAHs]. Quite similar to S/HT area, no co-variability of specific PAH fractions with Sp-PAHs was seen in S/LT area too;

A.P. Wickramasinghe et al. / Atmospheric Environment 45 (2011) 2642e2650

the contribution of [SAcpy-Py/Sp-PAHs] was higher and variable while that of [Chry þ BFs/Sp-PAHs] was moderate. In both S/HT and S/LT areas, [B[ghi]Pe/Sp-PAHs] level has been low and steady at the base, indicating a low grade of constant gasoline emissions. Accordingly, in all S/T stations although the major sources were identified as diesel engines and firewood stoves, the variability of Sp-PAHs could be totally explained neither by the percentage of specific p-PAHs nor by the correlation with traffic volume. However, with firewood use very strong (r ¼ 0.92) or perfect corelationships were observed in S/HT/LOF and S/LT/LOF areas, respectively. In R/B/HF area the contributions from the [SAcpy-Py/Sp-PAHs] and [Nap/Sp-PAHs] were very high and variable, while the fraction of [Chry þ BFs/Sp-PAHs] has been relatively moderate with the highest percentage Acpy (41e58%). They altogether demonstrated the PAH signature of the firewood burning (Park et al., 2002; U.S.E.P.A., 2006), which was supplemented with the perfect corelationship between Sp-PAHs and quantitative firewood use. In addition, firewood burning was specified as the predominant source of PAH emission through the significant contribution of P P [ Acpy-Py] and [ Chry þ BFs] to Sp-PAHs in R/B/LOF area. In the current study, since the PAH emission profiles have been compared against the quantitative figures of the related sources, it has resulted in a highly realistic and logistic conclusion. Accordingly, in general the major sources of particles bound PAHs in Kandy were identified as diesel emissions, with a significant contribution from firewood combustion; while the gasoline emissions have been very low and constant. Further, the diesel dominance was comparable with the manually differentiated day time traffic data by University of Peradeniya; which found that the total vehicular mass on all assessed main routes has been composed of on average >60% diesel vehicles. 3.5. Quantitative risk estimate All the risk estimates used are uncertain because of various deficiencies in the database. The use of experimental animal data on single PAH substances for purposes other than relative potency rankings is not recommended and the WHO unit risk estimates for humans; 8.7  10
5 per ng m
3 B[a]P as an indicator, thus refers to the total PAH mixture, based on epidemiologic data on lung cancer in coke-oven workers (WHO, 2000), are still the best basis for a quantitative risk estimate (Bostrom et al., 1994). Benzo [a]pyrene was initially favored as an indicator of all urban air pollution, and has been used as an index of exposure to a wider mixture of materials in a number of assessments of the general population (Nisbet et al., 1985). According to epidemiologic approach and assuming a linear dose-response relationship at low exposure levels, the excess lifetime lung cancer risk in different areas in Kandy were calculated (Table 3). A 3310 in million lifetime risk to the public in 2008 would result in an excess lung cancer burden of > 650 deaths over a 70 year

Table 3 Estimated excess life-time lung cancer risk according to WHO risk estimate. Category

Theoretic excess life-time lung cancer risk per ng of B[a]P/m3

Overall U/HT U/LT S/HT S/LT R/B/HF R/B/LOF

3.31  10
3 4.58  10
3 3.17  10
3 1.84  10
3 1.77  10
3 2.67  10
3 ND

2649

period or w10 annual deaths among residents in Kandy. There is very little guidance internationally on how to interpret the theoretic risks for air. However, according to the WHO (1996) guideline (1.0  10
5 for genotoxic carcinogens in drinking water), >300 fold higher overall risk level would never be considered as acceptable. With even traffic volume but with different topographical characters, the reported excess lung cancer rate in urban areas was 2.5 fold higher than that in suburban area. The risk ratio (RR) of 1.04 between heavy traffic versus light traffic in suburbs was not as distinguished as that in urban area (1.45). In R/B/HF area, relatively a higher risk was reported than in suburban traffic area; while the surrogate B[a]P was not detected in R/B/LOF areas. 4. Conclusion Ambient concentrations of PM10 bound PAHs were determined in urban, suburban and rural areas within Kandy, Sri Lanka, over a period of nine months. The investigated urban heavy traffic sites, connected with branched or deviated streets and are usually P bordered by high storey buildings, had the highest p-PAH concentrations which ranged from 443.53 to 1246.12 ng m
3 (mean: 695.94 ng m
3) along Kandy city’s roadways and increased with assessed traffic volume and also the noticeable traffic density. These levels were comparable with reported roadway data of 50e910 ng m
3 in the mega city-Mexico (Marr et al., 2004) and of 912 ng m
3 in Tainan, Taiwan (Sheu et al., 1997). In addition, while the mean PM10 concentration in overall study area was 129 mg m
3, in U/HT category it expanded up to 221 mg m
3. Hence, the urban heavy traffic group was the most polluted area under study and could be declared as ‘Air Toxic Hot Spots’ in Kandy. It was followed by the suburban- mixed heavy traffic station with high influence of surrounding firewood emissions. With similar traffic volume, P suburban areas were reported with >2 fold lower p-PAHs concentration than in urban areas; but the suburbs were with less traffic congestion and further spacious surroundings and tree borders in suburbs could disperse and adsorb the pollutants. P Compared to U/HT area, >3 fold lower p-PAHs concentration was reported in R/B areas, which further reduced with lowered firewood use. The differences in characteristics of types and strengths of emissions were primarily responsible for the spatial variations observed in the PAHs profiles among sampling sites. Speciated measurements suggest that in urban and suburban areas automobile emissions, mainly diesel engines, are the predominant daytime source of PAHs, with a significant contribution from firewood combustion as well in the U/HT area, while rural areas have been affected by domestic firewood burning; all were in well accord with the physically quantified sources of emissions. Thus, PAH profiles or the relative abundance of the different species in particulate emissions from different combustion sources proves as reliable source signatures where inorganic marker elements are not available. These results have important implications in PAH pollution control and public health. Increased collaborative efforts are needed between transport sector and public and regulatory bodies for the development of low-cost and effective emission control strategies. Epidemiological studies in revealed priority areas should be combined if feasible to clearly establish the role of urban air pollution on the health and well-being of people. Acknowledgement This study was partially supported by the University research grant RG/2007/25/E of University of Peradeniya, Sri Lanka. We are indebted to Prof. R. Shanthini (University of Peradeniya) for the

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guidance and support extended throughout the project. Mr. Mahen Wijeratne provided the PAH standard solution.

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