Fifty-four road dust samples were collected from principal roads (n = 37) and residential roads (n = 17) nationwide in Japan from March 2010 to November 2012. Sixteen polycyclic aromatic hydrocarbons (PAHs) and ignition loss (IL) were determined. The total PAH contents ranged from 62 to 6,325 ng g−1 with a geometric mean of 484 ng g−1. The IL ranged from 0.8 to 17% with a mean of 6%. The PAH contents were correlated with the IL contents, and the IL contents were dependent on the population density. From the PAH pattern analysis, the PAHs from road dust are considered to be mainly from diesel emissions.

INTRODUCTION

Increased runoff of toxic substances from urban areas has become a serious problem. There are many types of toxic substances that enter urban runoff, including metals, pharmaceuticals, personal care products and unintentionally created organic substances. One important class of pollutants is polycyclic aromatic hydrocarbons (PAHs). PAHs are a group of organic compounds composed of two or more fused benzene rings, many of which have been shown to be carcinogenic and mutagenic (Dipple 1985; Vinggaard et al. 2000; Xue & Warshawsky 2005). PAHs primarily originate from the incomplete combustion of fossil fuels, which results in their emission into the atmosphere and subsequent deposition into aquatic environments. In our previous studies (Iwasaki et al. 2009; Kojima et al. 2010; Ozaki et al. 2012), PAHs were extensively investigated in the Hiroshima Bay area, Japan. The results showed that considerable differences were apparent between atmospheric and sediment PAH loadings in the bay. The estimated atmospheric deposition of PAHs was considerably lower than the deposition estimated for sediments in the bay. To understand this difference, it is important to investigate the behavior of road dust, because road dust deposition is an important pathway for pollutants from air to enter water (Rogge et al. 1993; Aryal et al. 2005, 2013; Murakami et al. 2005; Liu et al. 2007; Hassanien & Abdel-Latif 2008; Zhang et al. 2008). For example, if PAH concentration patterns in road dust are different from those measured in the atmosphere, the PAHs in road dust would then be assumed to have originated from sources other than just the atmosphere. Some mechanically generated dust particles deposit more readily by gravitational sedimentation and are not easily re-suspended in the atmosphere (Rogge et al. 1993). It is difficult to measure this pathway using typical bucket sampling for atmospheric deposition, so direct sampling of road dust may provide a way to better understand this potential pathway.

In this study, road dust on major and residential roads across Japan was collected and PAH concentrations were measured. From the results, PAH concentration patterns were compared with those from vehicle emissions and atmospheric particles.

MATERIALS AND METHODS

Samplings

The road dust was collected nationwide in Japan: 54 samples were collected from Hokkaido, the most northern prefecture, to Okinawa, the most southern, from March 2010 to November 2012 (Table 1). The number of principal road samplings was 37, while 17 samples were obtained on residential roads. The samples were collected during the daytime (10:30–19:00). In order to avoid any direct effects from rainfall, a sample was collected on a dry day after more than 2 days from the antecedent rainfall (two samples were less than 48 hours). The samples were collected at the edge of the roads using a brush made of swine bristles. All roads in the sample were asphalt-covered. The area of the samples were in the range 0.18–5.15 m2 and the resultant collected particle mass was 10–200 g per sample. Traffic density data were obtained from the road traffic census (Ministry of Land, Infrastructure, Transport and Tourism of Japan 2010). The traffic density of the sampled principal road was in the range of 4,507–67,935 vehicles day−1. The climate data were obtained from the AMeDAS data set (Japan Meteorological Agency n.d.).

Table 1

Sampling points with measured 16 PAHs and IL

ID Sampling date GPS coordinate (WGS84) Location (city) Route Principal road? [Y/N] Traffic dens. [vehicles day−1Weather conditions Temp. [°C] Antecedent rainfall [mm] Antecedent dry period [hour] 16 PAHs [ng g−1IL [−] 
100329-34-01 2010/03/29 15:00 34.393886, 132.456894 Hiroshima NR route 54 36,228 Fine 11.5 16.5 100 142 0.018 
100506-13-01 2010/05/06 15:00 35.707593, 139.766967 Tokyo PR Route 453 21,207 Fine 24.4 83.5 168 388 0.108 
100517-13-02 2010/05/17 10:30 35.650348, 139.753609 Tokyo NR Route 15 45,109 Fine 23.2 16.5 123 1653 0.135 
100517-13-03 2010/05/17 12:00 35.64351, 139.810503 Tokyo TM highway 46,280 Fine 24.4 16.5 124 1340 0.100 
100517-13-04 2010/05/17 14:00 35.690699, 139.798037 Tokyo TM Route 483 24,113 Fine 25.5 16.5 126 365 0.070 
100520-43-01 2011/05/20 12:00 32.814272, 130.726407 Kumamoto Kumamoto PR Route 337 18,392 Fine 28.3 6.5 217 139 0.074 
100806-09-01 2010/08/06 00:00 36.343941, 139.459554 Ashikaga  Fine 8.5 77.0 188 
100806-09-02 2010/08/06 00:00 36.343941, 139.459554 Ashikaga  Fine 8.5 78.0 1802 
100806-09-03 2010/08/06 00:00 36.315319, 139.492282 Ashikaga  Fine 8.5 79.0 121 
100823-27-01 2010/08/23 10:35 34.842100, 135.567308 Osaka Osaka PR Route 46 17,974 Fine 36.2 17.0 222 690 0.041 
100903-25-01 2011/09/03 14:00 35,047416, 135.918055 Kusatsu Shiga PR Route 559 Fine 36.0 7.0 116 1099 0.073 
100933-26-01 2011//09/03 15:40 34.995972, 135.742611 Kyoto NR Route 9 57,356 Fine 35.0 135.5 531 6325 0.173 
100903-26-02 2011/09/03 14:15 34.991722/135.752805 Kyoto NR Route 1 43,186 Fine 35.5 135.5 530 3204 0.141 
100911-01-01 2010/09/11 08:30 43.342032, 142.360067 Furano  Fine 19.3 30.0 119 625 0.041 
101028-01-01 2010/10/28 23:00 42.633959, 141.602955 Tomakomai NR Route 36 27,795 Cloudy 1.9 11.0 44 417 0.008 
101116-43-01 2010/11/16 06:00 32.797331, 130.704788 Kumamoto  Fine 4.4 7.5 97 373 0.063 
110105-34-01 2011/01/05 10:00 34.489615, 133.39797 Fukuyama NR Route 1 44,115 Cloudy 3.5 15.5 349 494  
110105-34-02 2011/01/05 10:00 34.507927, 133.410158 Fukuyama Hiroshima PR Route 379 17,585 Cloudy 3.5 15.5 349 330 0.034 
110105-34-03 2011/01/05 10:00 34.516211, 133.440714 Fukuyama  Cloudy 3.5 15.5 349 184 
110120-34-04 2011/01/20 20:00 34.403156, 132.752094 Higashihiroshima NR Route 2 25,598 Fine 0.6 3.5 404 691 0.055 
110120-34-05 2011/01/20 20:00 34.421673, 132.75201 Higashihiroshima NR Route 375 15,581 Fine 0.6 3.5 404 282 0.055 
110120-34-06 2011/01/20 20:00 34.414628, 132.742653 Higashihiroshima  Fine 0.6 3.5 404 238 0.025 
110128-24-01 2011/01/28 12:20 34.767305, 136.130503 Iga  Cloudy 6.0 55 668 197 0.029 
110128-27-01 2010/01/28 16:50 34.842100, 135.567300 Ibaragi Osaka PR Route 17,974 Fine 6.5 11.0 906 705 0.047 
110128-27-02 2011/01/28 09:25 34.789416, 135.57975 Ibaragi Osaka PR Route 4,507 Fine 6.5 11.0 899 1510 0.034 
110128-28-01 2011/01/28 15:30 34.90625, 135.409777 Kawanishi Hyogo PR Route Fine 4.5 13.0 905 701 0.072 
110128-29-01 2011/01/28 10:50 34.692527, 135.811638 Nara NR Route 24 49,189 Fine 7.5 60 685 332 0.056 
110226-34-01 2011/02/26 17:00 34.414891, 132.454082 Hiroshima NR Route 183 22,995 Fine 12.2 18.0 209 322 0.017 
110414-34-01 2011/04/14 12:00 34.433437, 132.791719 Higashihiroshima Sanyo Highway 41,697 Fine 18.2 20.5 135 436 0.056 
110518-23-01 2011/05/18 19:00 35.170991, 136.889542 Nagoya Aichi PR Route 63 Fine 22.6 3.5 148 1775 0.122 
110521-33-01 2011/05/21 13:00 34.68161, 133.914365 Okayama NR Route53 41,548 Fine 25.6 14.0 217 463 0.023 
110619-34-01 2011/06/19 18:00 34.57526, 133.237542 Fuchu Hiroshima PR Route 218 Cloudy 23.3 6.5 65 378 0.019 
110801-34-01 2011/08/01 19:00 34.411383, 133.203046 Onomichi NR Route 2 15,096 Fine 29.4 13.0 323 740 0.024 
111125-23-01 2011/11/25 11:30 35.09291, 136.92489 Nagoya Aichi PR Route 55 30,150 Cloudy 11.0 59.0 138 2768 0.165 
111202-34-01 2011/12/02 11:00 34.443745, 132.653 Higashihiroshima NR Route 2 24,034 Fine 10.0 58.0 308 610 0.041 
111205-12-01 2011/12/05 23:00 35.723388, 140.075136 Yachiyo NR Route 296 29,984 Fine 6.5 28.0 58 620 0.054 
111215-34-02 2011/12/15 15:30 34.390842, 132.719082 Higashihiroshima Hiroshima PR Route 331 11,193 Fine 8.5 5.0 173 291 0.016 
111215-34-03 2011/12/15 16:00 34.433437, 132.791719 Higashihiroshima Sanyo highway 41,697 Fine 8.1 5.0 173 1044 0.064 
111215-34-06 2011/12/15 17:00 34.428764, 132.848659 Takehara Hiroshima PR Route 351 Fine 7.8 3.0 174 706 0.056 
120106-13-01 2012/01/06 14:00 35.679793, 139.77183 Tokyo NR Route 15 19,155 Fine 9.6 4.0 651 2815 0.158 
120421-34-01 2012/04/21 10:00 34.667322, 132.705226 Akitakata Hiroshima PR Route 54 16,910 Fine 17.0 45.0 245 181 0.020 
120809-32-01 2012/08/09 17:00 35.434163, 133.012011 Matsue NR Route 9 37,823 Fine 26.2 10.5 617 474 0.021 
120809-32-02 2012/08/09 18:00 35.319509, 132.912061 Unnan NR Route 54 10,411 Fine 24.3 21.0 618 391 0.051 
120826-34-01 2012/08/26 19:00 34.39,132.9347 Mihara NR Route 2 18,874 Fine 27.8 33.5 298 490 0.024 
120904-23-01 2012/09/04 18:30 35.16934, 136.911541 Nagoya Aichi PR Route 60 Cloudy 27.5 26.0 413 297 0.059 
120905-23-01 2012/09/05 19:30 35.171486, 136.919585 Nagoya NR Route 153 40,741 Fine 28.8 26.0 438 138 0.042 
12090-23-01 2012/09/06 20:30 35.170594, 136.897443 Nagoya NR Route 19 67,935 Cloudy 28.3 26.0 443 89 0.029 
120910-41-01 2012/09/10 11:00 33.260291, 130.298632 Saga Saga PR Route 29 Cloudy 25.3 16.0 123 157 0.030 
120911-41-01 2012/09/11 15:30 33.250101, 130.294955 Saga NR Route 264 22,183 Fine 25.8 16.0 136 212 0.026 
120917-47-01 2012/09/17 20:30 26.245176, 127.694631 Urasoe NR Route 58 67,013 Fine 27.0 135.5 32 532 0.049 
120919-47-01 2012/09/19 11:30 26.239419, 127.705537 Urasoe Okinawa PR Route 251 Cloudy 25.8 135.5 72 226 0.049 
120922-47-01 2012/09/22 12:00 26.236494, 127.697412 Naha Okinawa PR Route 82 Cloudy 27.7 135.5 140 62 0.021 
121020-34-01 2012/10/20 18:00 34.397167, 133.0895 Mihara NR Route 2 29,359 Fine 16.9 37.0 71 826 0.049 
121110-13-01 2012/11/10 08:30 35.727634, 139.768581 Tokyo   Fine 13.6 41.0 87 927 0.106 
ID Sampling date GPS coordinate (WGS84) Location (city) Route Principal road? [Y/N] Traffic dens. [vehicles day−1Weather conditions Temp. [°C] Antecedent rainfall [mm] Antecedent dry period [hour] 16 PAHs [ng g−1IL [−] 
100329-34-01 2010/03/29 15:00 34.393886, 132.456894 Hiroshima NR route 54 36,228 Fine 11.5 16.5 100 142 0.018 
100506-13-01 2010/05/06 15:00 35.707593, 139.766967 Tokyo PR Route 453 21,207 Fine 24.4 83.5 168 388 0.108 
100517-13-02 2010/05/17 10:30 35.650348, 139.753609 Tokyo NR Route 15 45,109 Fine 23.2 16.5 123 1653 0.135 
100517-13-03 2010/05/17 12:00 35.64351, 139.810503 Tokyo TM highway 46,280 Fine 24.4 16.5 124 1340 0.100 
100517-13-04 2010/05/17 14:00 35.690699, 139.798037 Tokyo TM Route 483 24,113 Fine 25.5 16.5 126 365 0.070 
100520-43-01 2011/05/20 12:00 32.814272, 130.726407 Kumamoto Kumamoto PR Route 337 18,392 Fine 28.3 6.5 217 139 0.074 
100806-09-01 2010/08/06 00:00 36.343941, 139.459554 Ashikaga  Fine 8.5 77.0 188 
100806-09-02 2010/08/06 00:00 36.343941, 139.459554 Ashikaga  Fine 8.5 78.0 1802 
100806-09-03 2010/08/06 00:00 36.315319, 139.492282 Ashikaga  Fine 8.5 79.0 121 
100823-27-01 2010/08/23 10:35 34.842100, 135.567308 Osaka Osaka PR Route 46 17,974 Fine 36.2 17.0 222 690 0.041 
100903-25-01 2011/09/03 14:00 35,047416, 135.918055 Kusatsu Shiga PR Route 559 Fine 36.0 7.0 116 1099 0.073 
100933-26-01 2011//09/03 15:40 34.995972, 135.742611 Kyoto NR Route 9 57,356 Fine 35.0 135.5 531 6325 0.173 
100903-26-02 2011/09/03 14:15 34.991722/135.752805 Kyoto NR Route 1 43,186 Fine 35.5 135.5 530 3204 0.141 
100911-01-01 2010/09/11 08:30 43.342032, 142.360067 Furano  Fine 19.3 30.0 119 625 0.041 
101028-01-01 2010/10/28 23:00 42.633959, 141.602955 Tomakomai NR Route 36 27,795 Cloudy 1.9 11.0 44 417 0.008 
101116-43-01 2010/11/16 06:00 32.797331, 130.704788 Kumamoto  Fine 4.4 7.5 97 373 0.063 
110105-34-01 2011/01/05 10:00 34.489615, 133.39797 Fukuyama NR Route 1 44,115 Cloudy 3.5 15.5 349 494  
110105-34-02 2011/01/05 10:00 34.507927, 133.410158 Fukuyama Hiroshima PR Route 379 17,585 Cloudy 3.5 15.5 349 330 0.034 
110105-34-03 2011/01/05 10:00 34.516211, 133.440714 Fukuyama  Cloudy 3.5 15.5 349 184 
110120-34-04 2011/01/20 20:00 34.403156, 132.752094 Higashihiroshima NR Route 2 25,598 Fine 0.6 3.5 404 691 0.055 
110120-34-05 2011/01/20 20:00 34.421673, 132.75201 Higashihiroshima NR Route 375 15,581 Fine 0.6 3.5 404 282 0.055 
110120-34-06 2011/01/20 20:00 34.414628, 132.742653 Higashihiroshima  Fine 0.6 3.5 404 238 0.025 
110128-24-01 2011/01/28 12:20 34.767305, 136.130503 Iga  Cloudy 6.0 55 668 197 0.029 
110128-27-01 2010/01/28 16:50 34.842100, 135.567300 Ibaragi Osaka PR Route 17,974 Fine 6.5 11.0 906 705 0.047 
110128-27-02 2011/01/28 09:25 34.789416, 135.57975 Ibaragi Osaka PR Route 4,507 Fine 6.5 11.0 899 1510 0.034 
110128-28-01 2011/01/28 15:30 34.90625, 135.409777 Kawanishi Hyogo PR Route Fine 4.5 13.0 905 701 0.072 
110128-29-01 2011/01/28 10:50 34.692527, 135.811638 Nara NR Route 24 49,189 Fine 7.5 60 685 332 0.056 
110226-34-01 2011/02/26 17:00 34.414891, 132.454082 Hiroshima NR Route 183 22,995 Fine 12.2 18.0 209 322 0.017 
110414-34-01 2011/04/14 12:00 34.433437, 132.791719 Higashihiroshima Sanyo Highway 41,697 Fine 18.2 20.5 135 436 0.056 
110518-23-01 2011/05/18 19:00 35.170991, 136.889542 Nagoya Aichi PR Route 63 Fine 22.6 3.5 148 1775 0.122 
110521-33-01 2011/05/21 13:00 34.68161, 133.914365 Okayama NR Route53 41,548 Fine 25.6 14.0 217 463 0.023 
110619-34-01 2011/06/19 18:00 34.57526, 133.237542 Fuchu Hiroshima PR Route 218 Cloudy 23.3 6.5 65 378 0.019 
110801-34-01 2011/08/01 19:00 34.411383, 133.203046 Onomichi NR Route 2 15,096 Fine 29.4 13.0 323 740 0.024 
111125-23-01 2011/11/25 11:30 35.09291, 136.92489 Nagoya Aichi PR Route 55 30,150 Cloudy 11.0 59.0 138 2768 0.165 
111202-34-01 2011/12/02 11:00 34.443745, 132.653 Higashihiroshima NR Route 2 24,034 Fine 10.0 58.0 308 610 0.041 
111205-12-01 2011/12/05 23:00 35.723388, 140.075136 Yachiyo NR Route 296 29,984 Fine 6.5 28.0 58 620 0.054 
111215-34-02 2011/12/15 15:30 34.390842, 132.719082 Higashihiroshima Hiroshima PR Route 331 11,193 Fine 8.5 5.0 173 291 0.016 
111215-34-03 2011/12/15 16:00 34.433437, 132.791719 Higashihiroshima Sanyo highway 41,697 Fine 8.1 5.0 173 1044 0.064 
111215-34-06 2011/12/15 17:00 34.428764, 132.848659 Takehara Hiroshima PR Route 351 Fine 7.8 3.0 174 706 0.056 
120106-13-01 2012/01/06 14:00 35.679793, 139.77183 Tokyo NR Route 15 19,155 Fine 9.6 4.0 651 2815 0.158 
120421-34-01 2012/04/21 10:00 34.667322, 132.705226 Akitakata Hiroshima PR Route 54 16,910 Fine 17.0 45.0 245 181 0.020 
120809-32-01 2012/08/09 17:00 35.434163, 133.012011 Matsue NR Route 9 37,823 Fine 26.2 10.5 617 474 0.021 
120809-32-02 2012/08/09 18:00 35.319509, 132.912061 Unnan NR Route 54 10,411 Fine 24.3 21.0 618 391 0.051 
120826-34-01 2012/08/26 19:00 34.39,132.9347 Mihara NR Route 2 18,874 Fine 27.8 33.5 298 490 0.024 
120904-23-01 2012/09/04 18:30 35.16934, 136.911541 Nagoya Aichi PR Route 60 Cloudy 27.5 26.0 413 297 0.059 
120905-23-01 2012/09/05 19:30 35.171486, 136.919585 Nagoya NR Route 153 40,741 Fine 28.8 26.0 438 138 0.042 
12090-23-01 2012/09/06 20:30 35.170594, 136.897443 Nagoya NR Route 19 67,935 Cloudy 28.3 26.0 443 89 0.029 
120910-41-01 2012/09/10 11:00 33.260291, 130.298632 Saga Saga PR Route 29 Cloudy 25.3 16.0 123 157 0.030 
120911-41-01 2012/09/11 15:30 33.250101, 130.294955 Saga NR Route 264 22,183 Fine 25.8 16.0 136 212 0.026 
120917-47-01 2012/09/17 20:30 26.245176, 127.694631 Urasoe NR Route 58 67,013 Fine 27.0 135.5 32 532 0.049 
120919-47-01 2012/09/19 11:30 26.239419, 127.705537 Urasoe Okinawa PR Route 251 Cloudy 25.8 135.5 72 226 0.049 
120922-47-01 2012/09/22 12:00 26.236494, 127.697412 Naha Okinawa PR Route 82 Cloudy 27.7 135.5 140 62 0.021 
121020-34-01 2012/10/20 18:00 34.397167, 133.0895 Mihara NR Route 2 29,359 Fine 16.9 37.0 71 826 0.049 
121110-13-01 2012/11/10 08:30 35.727634, 139.768581 Tokyo   Fine 13.6 41.0 87 927 0.106 

NR: national route, PR: prefectural route, TM: Tokyo metropolitan.

The samples were dried in a desiccator at room temperature for 48 hours in the dark and sieved, and particles <2 mm were obtained. The samples were stored at −4 °C prior to measurement. Laboratory glassware was cleaned using dichloromethane (DCM) and glass fibers were burned preliminarily at 400 °C for 1 hour. The ignition loss (IL; 600 °C, 4 hours) was measured for the samples (four samples were not measured). For PAH extraction, a sample was extracted with DCM in an ultrasonic water bath and the extract was concentrated to 2 mL with N2 gas. For internal standards, a mixture of acenaphthene-d10, phenanthrene-d10, chrysene-d12, and perylene-d12 was applied. The mixed standard was added in vials to correct peak detection sensitivity for instrumental analysis.

Instrumental analysis

The PAH concentration was analyzed by using a gas chromatograph equipped with a mass spectrometer (GC-17A/MS-QP5050, Shimadzu Corp., Kyoto, Japan) and operated in the single-ion monitoring mode. Injection was split with the detector, and the inlet temperature was set at 280 °C. The initial temperature was 80 °C held for 2 min, ramped at 30 °C min−1 to 210 °C, ramped at 5 °C min−1 to 295 °C, and ramped at 2 °C min−1 to 315 °C with 16 mL min−1 helium as carrier gas. The mass transfer line and ion source were held at 250 °C. Sixteen unsubstituted PAHs were measured (Table 2).

Table 2

List of measured PAHs and their instrumental detection limits

Name Abbreviation IDL (pg) Name Abbreviation IDL (pg) 
Acenaphthylene Acty 0.10 Chrysene Chr 0.10 
Acenaphthene Acen 0.10 Benzo(b)fluoranthene B(b)F 0.14 
Fluorene Flu 0.23 Benzo(k)fluoranthene B(k)F 0.45 
Phenanthrene Phe 0.10 Benzo(e)pyrene B(e)P 0.10 
Anthracene Ant 0.10 Benzo(a)pyrene B(a)P 0.50 
Fluoranthene Flt 0.10 Dibenzo(ah)anthracene D(ah)A 0.74 
Pyrene Pyr 0.10 Benzo(ghi)perylene B(ghi)P 0.38 
Benzo(a)anthracene B(a)A 0.10 Indeno(123-cd)pyrene Ind 0.43 
Name Abbreviation IDL (pg) Name Abbreviation IDL (pg) 
Acenaphthylene Acty 0.10 Chrysene Chr 0.10 
Acenaphthene Acen 0.10 Benzo(b)fluoranthene B(b)F 0.14 
Fluorene Flu 0.23 Benzo(k)fluoranthene B(k)F 0.45 
Phenanthrene Phe 0.10 Benzo(e)pyrene B(e)P 0.10 
Anthracene Ant 0.10 Benzo(a)pyrene B(a)P 0.50 
Fluoranthene Flt 0.10 Dibenzo(ah)anthracene D(ah)A 0.74 
Pyrene Pyr 0.10 Benzo(ghi)perylene B(ghi)P 0.38 
Benzo(a)anthracene B(a)A 0.10 Indeno(123-cd)pyrene Ind 0.43 

IDL: instrument detection limit (pg injected).

Quality control

The detection limit was set at the level of 3 in the SN ratio. Instrument detection limits (IDLs) ranged from 0.1 to 1 pg for each species. Within this level, the coefficient of variation of each of the compounds was less than 20%. The quality of extraction was checked using dried marine sediments (HS-3B, National Research Council of Canada Institute for Marine Biosciences, Ottawa, ON, Canada), and diesel particulate matter (NIST SRM2975). The recovery averaged 50–80% for the marine sediments and 40–60% for the diesel particulate matter for all PAHs, and the repetition error was 5–10%.

RESULTS AND DISCUSSION

Fixed-point observation

In order to determine the variability of each sampling, the variation of different measurements at a fixed sampling point was checked. For this purpose, the road dust was collected at a principal road in the vicinity of the laboratory. The point was on the Saijo bypass of national route 2 (N34.419 E132.722, WGS84). The traffic density was 25,598 vehicles day−1. At the site, samples were taken from three different points (Points A, B, and C) on the edge of the road. The distances between A and B, and B and C were 80 m and 90 m, respectively. The sample was taken six times from 15 October 2012 to 2 November during the daytime (12:00–18:00). Rainfall occurred twice between the second and third samplings, and the fifth and sixth samplings. Figure 1 shows the results of the sum of 16 PAHs, and from the results the contents (ngPAHs ng−1 soil) values were fairly stable for each of the simultaneous samplings of the different sampling points. In the samplings on 19 October 2013 (fourth sampling), all three samples were twice as high as others commonly found. This means PAH contents can vary two-fold, and at the same time, spatial variation is less than 100 m along the road.

Figure 1

16 PAH contents of fixed-point observations.

Figure 1

16 PAH contents of fixed-point observations.

Road samplings

The 16 PAH contents varied by two orders of magnitude (62–6,325 ng g−1) with the geometric mean of 484 ng g−1 (n = 54) (Table 1). The IL organic contents were 0.8–17% (mean: 6%). The 16 PAHs from the principal roads were found to be 525 ng g−1 (geometric mean, n = 37). The 16 PAH content patterns are shown in Figure 2 and the major PAH species found were fluorene, phenanthrene, fluoranthene, pyrene, and benzo(ghi)perylene.

Figure 2

PAH content patterns of road dust (error bars represent standard deviation). (a) All (n = 54). (b) Principal roads (n = 37).

Figure 2

PAH content patterns of road dust (error bars represent standard deviation). (a) All (n = 54). (b) Principal roads (n = 37).

Correlations among the 16 PAHs, IL, traffic density, air temperature, and population density

The correlation between the contents of all 16 PAHs and IL is shown in Figure 3. Ignition loss, which represents the organic matter present, was well correlated with PAH contents, suggesting that IL and PAHs had the same source or sources. A similar observation was made for road runoff samples (Aryal et al. 2015). The slope value (2.0 × 104 ng 16 PAHs g−1 IL) indicates that the average PAH contribution to total organic matter was defined by IL. Taking a closer look at the correlation, the 16 PAH contents seem to increase from the IL by more than 10%, and do not simply follow a linear relationship. From this observation, PAH content divided by organic matter (ng 16 PAHs g−1 IL) is considered to be a better index for the pollution status. No significant correlation was, however, observed with socioeconomic indices such as traffic or population density. Further research is needed for this.

Figure 3

IL vs. 16 PAH contents.

Figure 3

IL vs. 16 PAH contents.

The correlations between 16 PAH contents and traffic density, 16 PAH contents and air temperature, and 16 PAH contents and antecedent rainfall for principal roads are shown in Figure 4. No significant correlations were apparent. Data shown in Figure 4 appear to include some outliers. As such, a Spearman's correlation t-test should be preferred instead of a Pearson's t-test. From the t-test, no significant correlation was measured. Traffic activity and population density (average for 10 × 10 km2; the data were acquired from the National Land Numerical Information download service (Japanese Ministry of Land and Infrastructure n.d.) could also have a strong influence on PAH content, but no significant correlation was identified. Instead of using PAH contents, the IL contents were found to be correlated with population density (Figure 5). This suggests that these indices were a better estimator of the road dust pollution. IL is easier to measure than PAHs and the population density likely reflects average vehicle activities better than measures like traffic density obtained at a measured site.

Figure 4

Traffic density, air temperature, and antecedent dry period vs. 16 PAH contents.

Figure 4

Traffic density, air temperature, and antecedent dry period vs. 16 PAH contents.

Figure 5

Population density vs. IL.

Figure 5

Population density vs. IL.

PAH pattern analysis

Principal component analysis (PCA) and cluster analysis were conducted for the PAH contents pattern normalized to the sum of the 16 PAHs. Two principal components (PC1 (25%) and PC2 (18%)) were identified (Figure 6(a)). In addition, plots of the two principal component scores are presented with the classifications of the plots by cluster analysis where they were classified into two groups. They were also classified into two separate groups by population density (Figure 6(b)). Population density was segmented as being greater than or less than 2,000 people per km2, which was similar to the median value of all the sampling points (1,828 per km2). The PCA or cluster analysis classification did not simply correspond with socioeconomic factors such as the population density. In the plots for low population density, the data were more widely scattered than those for high population density for the PC1 score (p = 0.7% from the F-test). This suggests that there were many emission sources in an urban area and the total load is an averaged mixture of a number of sources in higher population density areas. In lower population density areas, on the contrary, the number of emission sources would be limited and this possibly caused the PAH pattern observed. More research would be required to confirm this suggestion.

Figure 6

PCA and cluster analysis results.

Figure 6

PCA and cluster analysis results.

Isomer ratio analysis of parent PAHs has been widely applied to identify their emission sources (Yunker et al. 2002; Feng et al. 2006). In this study, five widely applied isomer ratios were calculated (Figure 7). The results are shown with those from other emission sources and under different environmental conditions (vehicle emissions, biomass burning residues, atmospheric particles in cold season, and atmospheric deposition) measured and collected in our previous studies (Ozaki et al. 2006, 2012; Fukushima et al. 2012). These results show that Ant/(Ant + Phe) was 0.1–0.2, Flt/(Flt + Pyr) was 0.4–0.6, B(a)A/(B(a)A + Chr) was 0.2–0.5, B(a)P/(B(a)P + B(e)P) was 0.2–0.5 and Ind/(Ind + B(ghi)P) was 0.1–0.6. In comparison to the different emission sources it was difficult to identify just one source.

Figure 7

Isomer ratio analysis, where FPM is fine particulate matter (<7 μm), CPM is coarse particulate matter (>7 μm) and Deposit. is atmospheric deposition.

Figure 7

Isomer ratio analysis, where FPM is fine particulate matter (<7 μm), CPM is coarse particulate matter (>7 μm) and Deposit. is atmospheric deposition.

Using the data sets above, the value of the ratio was statistically compared for each ratio and each emission source using an unpaired t-test with Cohen's d as follows (Cohen 1988): 
formula
 
formula
where the subscripts 1 and 2 indicate different environmental sources or conditions, and are the mean values, n1 and n2 are the data numbers, and the s1 and s2 are the standard deviations.

As the d value increases, the difference between the two data sets increases (Thalheimer & Cook 2002, 2008). Using the criteria of Thalheimer & Cook (2002, 2008), differences in the data sets for road dust and other sources were compared for each isomer ratio (Table 3). In Table 3, the darker colors indicate greater similarities. Diesel was identified to be the most similar to road dust.

Table 3

Comparison of the different emission sources to the road dusts for each isomer ratio by Cohen's d

 
 

Finally, to consider the variability of the ratios within the road dust data set, every ratio was compared to that measured in the surrounding environment. For comparison, each ratio was compared to population density (Figure 8) because population density was the only parameter for which a significant correlation was identified (Figure 5). No significant correlation was found (t-test with Bonferroni correction). But when two outliers were excluded, significant correlations were identified for Ant/(Ant + Phe) and B(a)A/(B(a)A + Chr). One possible explanation for this observation is the sample freshness. Anthracene and benzo(a)anthracene are less stable than their isomers phenanthrene and chrysene, respectively (Yunker & MacDonald 1995). Therefore, the Ant/(Ant + Phe) and B(a)A/(B(a)A + Chr) ratios could decrease in samples with longer residence times on the roadside. The residence time of ground surface dust would be longer in rural areas and this difference could affect the ratio. These two ratios could provide an indication of PAH residence time on the ground.

Figure 8

Population density and isomer ratios. The correlation results for Ant/(Ant + Phe) and B(a)A/(B(a)A + Chr) were obtained after the two data points were excluded as outliers (cross marks).

Figure 8

Population density and isomer ratios. The correlation results for Ant/(Ant + Phe) and B(a)A/(B(a)A + Chr) were obtained after the two data points were excluded as outliers (cross marks).

CONCLUSIONS

PAH concentrations and patterns were identified for road dust samples collected from principal roads throughout Japan. PAH contents were correlated with the contents of organic matter, and the organic matter contents were dependent on the population density. Although the PAH contents fluctuated, the ignition loss content is suggested to be a possible index of PAH pollution in road dust. From the PAH pattern analysis, road dust PAHs in Japan were similar in composition to those produced from diesel emissions. For future studies, the combination of total organic matter and PAH pattern analysis would be a promising technique for clarifying the deposition mechanism of urban non-point source pollution. It would also be important to compare road dust composition with atmospheric and water samples using this technique.

ACKNOWLEDGEMENTS

We would like to offer our special thanks to Dr Keiko Wada, Dr Michio Murakami, and Dr Hidetoshi Kumata for collaboration in the sampling campaign.

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