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. Author manuscript; available in PMC: 2016 Dec 1.
Published in final edited form as: Environ Int. 2015 Sep 16;85:104–110. doi: 10.1016/j.envint.2015.09.003

Urinary Polycyclic Aromatic Hydrocarbon Metabolites as Biomarkers of Exposure to Traffic-Emitted Pollutants

Jicheng Gong a,f, Tong Zhu b, Howard Kipen c, David Q Rich d, Wei Huang e, Wan-Ting Lin f, Min Hu b, Junfeng (Jim) Zhang a,f,*
PMCID: PMC4765327  NIHMSID: NIHMS723700  PMID: 26382649

Abstract

1-nitro-pyrene has been considered a compound specific to diesel combustion emission, while 1- and 2-nitro-napthalene are mainly produced through photochemical conversion of naphthalene released to the atmosphere. Metabolites of these compounds may serve as biomarkers of exposure to traffic related pollutants. We collected urine samples from 111 healthy and nonsmoking subjects within (i.e., during the Beijing Olympics) and outside (i.e., before and after the Olympics) a traffic control regime to improve Beijing’s air quality. Urines were analyzed for the sum of 1&2-amino-naphthalene (metabolites of 1- and 2-nitro-naphthalene) and 1-amino-pyrene (a metabolite of 1-nitro-pyrene), using an HPLC-fluorescence method. Within the same time periods, PM2.5 mass and constituents were measured, including elemental carbon, sulfate, nitrate, PAHs, carbon monoxide, nitrogen dioxide, sulfur dioxide, ozone, and particle number concentrations. The associations between the urinary metabolites and air pollutants were analyzed using linear mixed-effects models. From the pre- to during-Olympic period, 1&2-amino-naphthalene and 1-hydroxy-pyrene decreased by 23% (p=0.066) and 16% (p=0.049), respectively, while there was no change in 1-amino-pyrene (2% increase, p=0.892). From during- to post-Olympic period, 1&2-amino-naphthalene, 1-amino-pyrene and 1-hydroxy-pyrene concentrations increased by 26% (p=0.441), 37% (p=0.355), and 3% (p=0.868), respectively. Furthermore, 1&2-amino-naphthalene and 1-hydroxy-pyrene were associated with traffic related pollutants in a similar lag pattern. 1-amino-pyrene was associated more strongly with diesel combustion products (e.g. PN and elemental carbon) and not affected by season. Time-lag analyses indicate strongest/largest associations occurred 24–72 hours following exposure. 1&2-amino-naphthalene and 1-hydroxy-pyrene can be used as a biomarker of exposure to general vehicle-emitted pollutants. More data are needed to confirm 1-amino-pyrene as a biomarker of exposure to diesel combustion emissions. Controlling creatinine as an independent variable in the models will provide a moderate adjusting effect on the biomarker analysis.

Keywords: PAH metabolites, biomarkers, diesel exhaust particles, exposure assessment, traffic-emitted pollutants

1. Introduction

Nitrated polycyclic aromatic hydrocarbons (nitro-PAHs) are known for their mutagenic and carcinogenic toxicities (Talaska et al., 1996). The major sources of atmospheric nitro-PAHs include direct emissions from the incomplete combustion of fossil fuels, especially diesel (Feilberg et al., 2001; Bamford and Baker 2003), and the formation through photochemical reactions between parent PAHs and the hydroxyl radical during daytime and the nitrate radical during nighttime (Atkinson and Arey 1994; Arey and Arkinson 2003). Particle-bound PAHs can also be formed through the heterogeneous reactions between PAHs and N2O5/NO3/NO2 on the surface of particles (Zimmermann et al., 2013). A wide variety of nitro-PAHs have been detected in diesel exhaust particles and airborne particles from biomass burning in urban environments (Dimashki et al., 2000; Marino et al., 2000; Bamford and Baker 2003; Wang et al., 2011). Therefore, people can be exposed to nitro-PAHs through the inhalation of airborne particles from diesel and biomass combustion.

Post inhalation, nitro-PAHs can be metabolized to amino-PAHs that are ultimately excreted through urine (Poirier and Weisburger 1974; Nachtman and Wei 1982; van Bekkum et al., 1998). Therefore, it is biologically plausible to use urinary amino-PAHs as biomarkers of nitro-PAH exposure. A study by Laumbach et al. (2009) observed higher urinary 1-amino-pyrene concentrations among human volunteers following a one-hour exposure to a diesel exhaust mixture at 300 µg/m3 PM10 (particulate matter with an aerodynamic diameter smaller than 10 µm) in an exposure chamber, compared to those exposed to clean air (Laumbach et al., 2009). This study supports earlier publications that demonstrated 1-nitro-pyrene as one of the nitro-PAH isomers to diesel combustion (Schuetzle et al., 1982; Paputapeck et al., 1983; Zwirner-Baier and Neumann 1999; Bamford and Baker 2003). In a more recent study, Neophytou et al. (2014) found associations between urinary amino-PAHs with vehicle exhaust-related PM2.5 (particulate matter with an aerodynamic diameter smaller than 2.5 µm) (Neophytou et al., 2014). Existing studies have also reported increases in urinary 1-amino-pyrene in underground miners following a work shift using diesel-powered machinery (Seidel et al., 2002). However, few studies have examined whether urinary amino-PAHs are associated with diesel traffic exposure in urban residents.

During the 2008 Beijing Olympics, aggressive air pollution control measures were implemented to reduce traffic emission and improve Beijing’s air quality (Wang et al., 2009a). The air pollution control measures included the introduction of new vehicular emission standards, restrictions on diesel-powered vehicles in Beijing’s urban areas, limited operation of local industrial and commercial combustion facilities and enforcement of alternate day driving that removed approximately half of the vehicles (∼1.5 million) from the local roads each day (Wang et al., 2009a; Rich et al., 2012). Various studies found substantial reductions in traffic-emitted air pollutants, including nitro-PAHs, during the Olympic period compared to before and after the Olympics (Wang and Xie 2009; Wang et al., 2009a; Wang et al., 2011; Rich et al., 2012). Taking advantage of this unique opportunity, we conducted a study to measure urinary 1&2-amino-naphthalene and 1-amino-pyrene in a panel of Beijing residents (Zhang et al., 2013). By assessing the association between the urinary amino-PAHs and exposure to traffic-emitted air pollutants, we aim to evaluate the validity of using 1&2-amino-naphthalene and 1-amino-pyrene as internal markers of exposure to nitro-PAHs in traffic-emitted pollutants. Because 1-hydroxy-pyrene as a major metabolite of pyrene has been often used as a biomarker of PAH exposure, we also aim to examine the association between urinary 1-hydroxy-pyrene and traffic-emitted pollutants (Strickland and Kang 1999; Hu et al., 2006).

2. Methods

2.1. Study Design and Subjects

Centered around the air pollution control measures described above, three sampling periods were defined in our study as: the pre-Olympic period (2 June 2008–19 July 2008) where some relatively mild controls were implemented, the during-Olympic period (July 20, 2008–September 19, 2008) where the full-scale control measures were implemented, and the post-Olympic period (September 20, 2008–October 30, 2008) where the majority of the control measures were relaxed. In previous studies, drastic reductions in the concentrations of air pollutants were observed during the Olympic period compared to the pre- and post-Olympic periods (Wang and Xie 2009; Wang et al., 2009a; Wang et al., 2010; Rich et al., 2012). Therefore, our three-period study design (the pre-during-post Olympics) followed a ‘high-low-high’ air pollution changing pattern.

In the current analysis, study subjects included 111 (55 male and 56 female) nonsmoking individuals, 22–27 years of age. The subjects were recruited from the pool of medical residents at the Peking University First Hospital (hereinafter referred to as ‘the hospital’). All study participants worked on the campus of the hospital and resided in dormitories at either the hospital or Peking University Health Sciences Center located within 5 km from the hospital. In each of the three Olympic periods, a spot urine sample was collected from each subject in the morning of the visit (between 8–10am). Each subject was scheduled to visit the clinic the same day of the week for all the three visits unless adverse events such as severe respiratory infectious diseases kept the subjects from timely clinical visits (Zhang et al., 2013). The sample collection in each of the three Olympic period lasted for four weeks. The study protocol was approved by the Institutional Review Board of the University of Medicine and Dentistry of New Jersey as well as the Ethics Committee of the Peking University Health Sciences Center and Peking University First Hospital.

2.2. Air Pollution Monitoring

The air pollution measurements were conducted as described previously (Rich et al., 2012; Zhang et al., 2013). In brief, air samplers and monitors were placed on top of a seven-story building located in the center of the Peking University First Hospital campus. Carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), PM2.5, elemental carbon (EC), sulfur dioxide (SO2), sulfate (SO42−), nitrate (NO3−), and particle number concentrations (PN) in the size range of 13.0–764.8 nm were monitored throughout the three study periods, beginning one week before the start of urine sample collection. Ambient temperature and relative humidity (RH) were monitored continuously and concurrently at the same site. PM2.5 were collected on a 37 mm Teflon filter using a Quad Channel Ambient Particulate Sampler equipped with an impactor that has an aerodynamic cut-off of 2.5 µm (TH-16A, Tianhong Inc. China) at a flow rate of 16.7 L/min. Polycyclic aromatic hydrocarbon concentrations in PM2.5 collected during the pre- and the during-Olympic periods were analyzed from fine particles using a method employing a gas chromatography–mass spectroscopy system (He et al., 2006; Huang et al., 2006). The method details can be found in the Supplementary Materials (Appendix I).

2.3. Urinary amino-PAH measurements

The current study used a modified method to analyze urinary amino-PAHs as described in a previous publication (Laumbach et al., 2009). In brief, 2 ml of urine sample were incubated with 20 µl of β-glucuronidase from Helix pomatia Type H-2 (Sigma-Aldrich, St. Louis, MO) in 2 ml 0.1 M sodium acetate buffer (pH 5.0) at 37°C overnight. The hydrolyzed urine samples were adjusted to pH>10 with the addition of 25 µl of 10 M sodium hydroxide and extracted with 4 ml of ethyl acetate. After mixing on a shaker for 10 min, the samples were centrifuged at 3500 rpm for 10 min. The supernatant was evaporated to dryness under nitrogen in a TurboVap LV evaporator operated at 35°C. The residue was reconstituted in 200 µl of methanol and 20 µl was injected into an HPLC-fluorescence system for the detection of 1&2-amino-naphthalene (as one single peak without resolving 1-AN and 2-AN), 1-amino-pyrene, and 1-hydroxy-pyrene. The chromatographic separation was achieved on a Supelco-Ascentis RP-Amide column (250 × 4.6 mm, 5 µm, Sigma-Aldrich, St. Louis, MO). The mobile phase was 50% acetonitrile (A) and 100% acetonitrile (B), with a linear gradient from 0% B at 0 min to 70% B at 30 min. The fluorescence detector was set up at 254/425 nm (Ex/Em).

The limits of detection were estimated as 3 times the standard deviation of 8 injections of a lower concentration calibration standard (0.25 ng/ml). The recovery of the assay was expressed as the ratio (%) of the concentration measured to the concentration spiked into a real urine sample (two concentrations were spiked including 1 ng and 10 ng). The precision of the assay was expressed as the coefficient of variation (%) of 8 repeated injections. In summary, the limit of detection of the three PAH metabolites were 0.04, 0.02, and 0.04 ng/ml, the recoveries were 84.3%, 88.3%, and 74.1%, and the precision were 6.0%, 10.1%, and 6.0% for 1&2-amino-naphthalene, 1-amino-pyrene, and 1-hydroxy-pyrene, respectively. The representative chromatograms of unspiked and spiked urine samples were provided in the Supplementary Materials (Figure S8).

2.4. Statistical analysis

Linear mixed-effects models were used to estimate the changes in urinary amino-PAH levels across the three sampling periods (pre-, during-, and post-Olympic period). Since the concentrations of the three urinary metabolites of PAHs followed a log-normal distribution, we used their log-transformed concentrations as the dependent variables in these mixed-effects models. Period was set as a categorical fixed effect, and individual subjects were treated as a random effect. A compound symmetry covariance structure was applied in the models as it provided the best fit (with the smallest values of Akaike Information Criterion) to the repeated observation data (Zhang et al., 2013). We also controlled for ambient temperature, relative humidity, gender, and the day of week as covariates in the models. To control for the family-wise type I error rate at a 0.05 level, a Bonferroni correction was applied. With 6 between-period comparisons (3 biomarkers by 2 between–period changes), each individual 2-sided test was considered statistically significant relative to a 0.008 significance level.

Furthermore, we performed analyses to examine associations between the three urinary biomarkers and the traffic pollutants using linear mixed-effects models with a single pollutant. In these models, the period effect was replaced by the measured concentrations of individual air pollutants. The other covariates, random-effect variables, and the covariance structure were the same as described earlier in this section. Concentrations of the traffic pollutants were averaged over various time periods before the time when urine samples were collected, categorized as lag 0 (0–23 h), lag 1 (24–47 h), lag 2 (48–71 h), and lag 3 (72–95 h). Each model estimated the association of each PAH metabolite with one pollutant at one lag day. Spearman correlation analysis was performed among the traffic pollutants to detect potential colinearity.

2.5. Different creatinine adjustment methods

Considering the diluting effect on urine samples, the PAH metabolites were adjusted for creatinine in the period effect analysis and their associations with the air pollutants. We used three creatinine adjustments on the PAH metabolites, including (1) creatinine-unadjusted: no adjustment for creatinine was made on the PAH metabolite data, (2) creatinine-standardized: the concentrations of the PAH metabolites were standardized by dividing the levels of creatinine, and (3) creatinine-independent: creatinine was controlled in the mix-effect models as an independent variable. These two ways of the creatinine adjustment were performed since we observed in a previous study that creatinine-standardized biomarker data showed less significant results than creatinine-unadjusted outcome, which may indicate a potential over adjustment for creatinine in a study designed to examine the within-subject effects (Gong et al., 2013).

3. Results

3.1. Changes in Air pollutant Concentrations by Period

The changes in air pollutant concentrations across the three Olympic periods have been reported in previous publications (Huang et al., 2012; Rich et al., 2012; Gong et al., 2013). In summary, we observed a 13–60% reduction in the mean concentration of major traffic-related pollutants (Table 1) during the extensive traffic control period. Furthermore, ozone concentrations showed a non-significant increasing trend (24%), which may be due to the reduction in NO emission from the traffic sources since NO is a major scavenger of ozone in the atmosphere. Similar to the other traffic-emitted pollutants, pyrene and the total PAHs decreased from the pre- to during-Olympic period by 37% (p<0.01) and 38% (p<0.01), respectively.

Table 1.

Period-specific means and percent changes in the air pollutants among the three Olympic periods

Pre-Olympics During-Olympics Post-Olympics During-Pre
Olympics		 Post-During
Olympics
GMa (95% CI) GM (95% CI) GM (95% CI) % change 95% CI % change 95% CI
PM2.5, µg/m3 98.9 (70.2, 127.7) 71.9 (42.3, 101.5) 85.3 (55.2, 115.3) −27 (−64, 9) 19 (−66, 103)
EC, µg/m3 2.2 (1.6, 2.8) 1.4 (0.8, 2.1) 3.4 (2.7, 4.0) −36* (−70, −2) 133** (35, 232)
PN, cm−3 16480 (13979, 18980) 12853 (10131, 15575) 19477 (16797, 22157) −22* (−42, −2) 52** (15, 88)
CO, ppm 1.23 (0.97, 1.49) 0.64 (0.37, 0.91) 0.81 (0.54, 1.08) −48** (−73, −24) 27 (−114, 168)
NO2, ppb 25.6 (18.4, 32.8) 14.6 (7.3, 22.0) 41.4 (33.9, 48.9) −43* (−76, −10) 183** (49, 317)
ozone, ppb 31.8 (24.5, 39.2) 39.6 (32.0, 47.1) 15.1 (7.5, 22.8) 24 (−13, 62) −62** (−85, −39)
SO2, ppb 7.5 (5.2, 9.7) 3.0 (0.4, 5.6) 6.8 (4.4, 9.2) −60** (−97, −23) 129 (−224, 482)
sulfate, µg/m3 26.5 (15.0, 37.9) 23.0 (10.5, 35.5) 13.7 (1.5, 25.8) −13 (−73, 47) −41 (−133, 52)
nitrate, µg/m3 18.3 (11.1, 25.4) 9.3 (1.5, 17.2) 17.6 (9.9, 25.2) −49* (−96, −1) 88 (−165, 342)
temperature, °C 25.2 (23.5, 27.0) 27.8 (26.0, 30.0) 16.7 (14.9, 18.5) 10 (−0.4, 20) −40* (−48, −31)
relative humidity, % 65.6 (57.8, 73.5) 64.9 (56.9, 73.0) 49.5 (41.4, 57.7) −1 (−18, 16) −24* (−42, −6)
Pyrene, ng/m3 3.2 (2.6, 3.7) 2.0 (1.4, 2.6) 0.8 (0.3, 1.4) −37** (−57, −16) −59 (−138, 199)
Total PAH, ng/m3 74.6 (62.9, 86.4) 46.4 (33.4, 59.3) 26.4 (14.0, 38.8) −38** (−58, −18) −43 (−121, 34)
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a

GM: Geometric mean

*

p value < .05,

**

p value < .01

3.2. Changes in Urinary Biomarker Concentrations by Period

Geometric means (GM) of the three PAH metabolites by period are shown in Table 2. For the creatinine-unadjusted values, from the pre- to during-Olympic period, the concentrations of urinary 1&2-amino-naphthalene, 1-amino-pyrene and 1-hydroxy-pyrene decreased by 29% (p=0.016), 10% (p=0.497) and 30% (p=0.003). From the during- to post-Olympic period, 1&2-amino-naphthalene and 1-amino-pyrene increased by 11% (p=0.737) and 10% (p=0.789) without reaching statistical significance. While the concentration of 1-hydroxy-pyrene continued to decrease by 23% (p=0.328) from the during- to the post-Olympic period without reaching statistical significance. With adjustment for creatinine using both methods, the reductions in 1&2-amino-naphthalene and 1-hydroxy-pyrene from the pre- to the during-Olympic period were in lower levels compared to the result using the method unadjusted for creatinine. Furthermore, we observed an increase in 1-amino-pyrene from pre- to during-Olympic period with adjustment for creatinine. The Spearman correlation coefficients among the three PAHs metabolites were 0.402 (p<0.0001) between 1&2-amino-naphthalene and 1-amino-pyrene, 0.425 (p<0.0001) between 1-amino-pyrene and 1-hydroxy-pyrene, and 0.639 (p<0.0001) between 1&2-amino-naphthalene and 1-hydroxy-pyrene, indicating a moderate correlation between each two of the three urinary PAH metabolites.

Table 2.

Period-specific means and percent changes in the PAH metabolites among the three Olympic periods

Pre-Olympics During-Olympics Post-Olympics During-Pre
Olympics		 Post-During
Olympics
GMa (95% CI) GM (95% CI) GM (95% CI) % change 95% CI % change 95% CI
Creatinine-unadjusted
  1&2-amino-naphthalene, pg/µl 0.34 (0.26, 0.45) 0.24 (0.19, 0.32) 0.27 (0.17, 0.42) −29 (−46, −6) 11 (−39, 103)
  1-amino-pyrene, pg/µl 0.11 (0.076, 0.16) 0.099 (0.070, 0.14) 0.11 (0.063, 0.19) −10 (−34, 22) 10 (−46, 124)
  1-hydroxy-pyrene, pg/µl 0.37 (0.28, 0.48) 0.26 (0.20, 0.33) 0.20 (0.13, 0.30) −30* (−44, −11) −23 (−54, 30)
Creatinine-standardizedb
  1&2-amino-naphthalene, pg/µg creatinine 0.48 (0.36, 0.65) 0.47 (0.36, 0.63) 0.61 (0.38, 0.97) −2 (−27, 31) 28 (−32, 142)
  1-amino-pyrene, pg/µg creatinine 0.16 (0.11, 0.22) 0.19 (0.14, 0.27) 0.25 (0.15, 0.42) 22 (−9, 63) 31 (−33, 153)
  1-hydroxy-pyrene, pg/µg creatinine 0.53 (0.44, 0.63) 0.50 (0.42, 0.60) 0.46 (0.35, 0.60) −5 (−19, 12) −9 (−37, 32)
Creatinine-independentc
  1&2-amino-naphthalene, pg/µl 0.31 (0.23, 0.41) 0.24 (0.19, 0.31) 0.30 (0.20, 0.47) −23 (−41, 2) 26 (−30, 127)
  1-amino-pyrene, pg/µl 0.096 (0.067, 0.14) 0.098 (0.071, 0.14) 0.13 (0.080, 0.22) 2 (−24, 37) 37 (−30, 167)
  1-hydroxy-pyrene, pg/µl 0.30 (0.25, 0.37) 0.25 (0.21, 0.31) 0.26 (0.19, 0.36) −16 (−30, 0) 3 (−31, 54)
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a

GM: Geometric mean. Marker was log-transformed, and geometric means (median) and 95% confident intervals were provided.

b

Standardizing the PAH metabolites with creatinine by dividing the concentrations of the metabolites with that of creatinine.

c

Controlling creatinine as an independent variable in the mixed-effects models.

*

p<.008

3.3. Associations between Urinary Biomarkers and Traffic-related Air Pollutants

Percent changes in the PAH metabolites associated with interquartile range increases in all pollutants are shown in Figure 1A–C. The results were obtained through mixed-effects models with creatinine controlled as an independent variable. A consistent pattern was found for the changes in the associations between 1&2-amino-naphthalene and the pollutants (except CO and ozone), showing that the percent changes increased from lag 0 to lag 2 and then started to decrease at lag 3, and the largest percent changes at lag 2 were statistically significant (Figure 1A). Associations between 1&2-amino-naphthalene and CO were significant across lag 0 to 4, with the largest percent changes appearing at lag 1.

Figure 1.

Figure 1

Figure 1

Figure 1

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Percent changes in urinary concentrations of (A)1&2-amino-naphthalene, (B) 1-amino-pyrene, and (C) 1-hydroxy-pyrene associated with one interquartile range changes in CO (0.65 ppm), SO2 (5.4 ppb), NO2 (18.7 ppb), O3 (25.4 ppb), PM2.5 (76.8 µg/m3), PN (6572 cm−3), EC (1.4 µg/m3), sulfate (28.0 µg/m3), nitrate (18.7 µg/m3), PYR (pyrene, 1.9 ng/m3), and TPAH (41.1 ng/m3) from lag 0 to lag 4. The results were from the mixed-effects models controlling for temperature, relative humidity, gender, day of week, and creatinine. The label of x axis, lag day, means that the percent changes in the PAH metabolites were shown by pollutant from lag 0 to lag 4. Circles indicate the mean percent changes in the PAH metabolites and the vertical error bars indicate the 95% confident interval of the mean changes.

Figure 1B shows that the percent changes in 1-amino-pyrene was associated with the changes in air pollutants from lag 0 to 3 in a similar pattern similar comparing to 1&2-amino-naphthalene. The percent changes in 1-amino-pyrene associated with NO2, PN, and EC increased from lag 0 to lag 2 and decreased from lag 2 to 3, while the percent changes associated with CO, PM2.5, sulfate, and nitrate increased from lag 0 to lag 1 and then decreased from lag 1 to lag 3. The percent changes in 1-amino-pyrene associated with changes in SO2, NO2, PM2.5, PN, EC, sulfate, and nitrate were statistically significant at lag 1 and lag 2, while none of the changes were statistically significant in the associations between 1-amino-pyrene and CO, SO2, pyrene, or total PAHs.

Figure 1C shows that the percent changes in 1-hydroxy-pyrene associated with NO2, EC, pyrene and the total PAHs increased from lag 0 to lag 2 and then decreased at lag 3, while the changes associated with CO, PM2.5, sulfate, and nitrate showed the largest values at lag 1. We observed significant percent changes in 1-hydroxy-pyrene associated with changes in all the measured air pollutants except ozone.

Due to negative correlations of ozone with the other pollutants (Table 3), ozone expectedly showed negative or non-significant associations with 1&2-amino-naphthalene, 1-amino-pyrene, and 1-hydroxy-pyrene at various lags. The creatinine-standardized and creatinine-unadjusted results of percent changes in the PAH metabolites associated with the changes in air pollutants were showed in the Supplementary Materials (Figure S1–S6).

Table 3.

Spearman correlation coefficients among air pollutants

PM2.5 EC CO NO2 PN ozone SO2 sulfate nitrate pyrene
PM2.5 1
EC 0.67b 1
CO 0.69b 0.58b 1
NO2 0.42b 0.80b 0.53b 1
PN 0.11 0.56b 0.27b 0.63b 1
ozone 0.12 −0.30b −0.13 −0.58b −0.33b 1
SO2 0.74b 0.71b 0.58b 0.64b 0.40b 0.02 1
sulfate 0.90b 0.40b 0.57b 0.12 −0.21 0.35b 0.63b 1
nitrate 0.92b 0.65b 0.69b 0.51b 0.10 −0.12 0.64b 0.78b 1
pyrene 0.76b 0.75b 0.69b 0.61b 0.41b −0.10 0.69b 0.63b 0.71b 1
Total PAHs 0.81b 0.82b 0.66b 0.59b 0.41b −0.13 0.65b 0.66b 0.74b 0.93b
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PN: particle number concentrations

a

p value < .05

b

p value < .01

4. Discussion

The current study reported comparable levels of urinary 1&2-amino-naphthalene and 1-amino-pyrene with other studies. Grimmer et al. (2000) reported the urinary levels of 1&2-amino-naphthalene in humans, and found that the sum of the two urinary metabolites was 189.7 and 591.2 ng/day in non-smokers and smokers. In the current study, assuming a typical daily urine volume of 1 liter, the daily excretion doses of 1&2-amino-naphthalene observed in healthy adults (non-smokers) were approximate 340, 240, and 270 ng/day in the pre-, during-, and post-Olympic periods, respectively. The doses observed in the current study were between the levels of non-smokers and smokers observed in Grimmer et al (2000) study. Laumbach et al. (2009) measured urinary 1-amino-pyrene levels in subjects after 1-hr exposure to ∼300 µg/m3 diesel exhaust particles, and found that the concentrations of urinary 1-amino-pyrene in subjects with exposure to diesel exhaust particles and to the clean air were 324.0±442.4 and 234.4±852.9 pg/mg creatinine (Laumbach et al., 2009). These results were comparable to the creatinine-standardized data of the current study (Table 2). In another study, Scheepers et al. (1995) used ELISA method to measure urinary 1-amino-pyrene from railroad workers and found that the 1-amino-pyrene levels approximately ranged from 3 −13 µmol/mol creatinine (5.8–25.0 pg/µg creatinine), which was about one to two orders of magnitude higher that what we reported in our study (Scheepers et al., 1995).

As the parent compound of 1-amino-pyrene, 1-nitro-pyrene comes primarily from direct emissions of diesel combustion, and it is one of the most abundant nitro-PAHs in diesel exhaust (Bamford and Baker 2003; Reisen and Arey 2005). During the Olympics, heavy-duty vehicles, which typically consume diesel, had been strictly forbidden to enter the urban area (within the 5th ring road) of the city, which led to significant reductions in the diesel exhaust emissions (Wang et al., 2009a). Since diesel truck traffic has been associated with the black carbon concentrations in Beijing (Westerdahl et al., 2009), the 73% reduction in black carbon during the Olympic period observed by Wang et al. (2009b), indicates a reduction in diesel exhaust emissions during the Olympic period.(Wang et al., 2009b).

However, we did not consistently observe lower concentrations of urinary 1-amino-pyrene during the Olympic period through the creatinine-unadjusted and adjusted methods (Table 2). Even though a 10% reduction in 1-amino-pyrene was obtained by using creatinine-unadjusted method, it was not statistically significant. After the adjustment for creatinine, the reduction in 1-amino-pyrene disappeared from the pre- to the during-Olympic period. Therefore, our data were not sufficient to associate the period changes in the urinary 1-amino-pyrene to the period changes in exposure to 1-nitro-pyrene. Similar result was reported by Neophytou et al. (2014) that there was no significant associations of urinary 1-amino-pyrene and any of the microenvironment exposure measures, including PM2.5, elemental and organic carbons, in their study (Neophytou et al., 2014). More data are needed to confirm the eligibility of using urinary 1-amino-pyrene as a biomarker of exposure to 1-nitro-pyrene.

Different from 1-nitro-pyrene, 1-nitro-naphthalene and 2-nitro-naphthalene are two major products of gas-phase photochemical reactions between naphthalene and the hydroxyl radical (daytime) or the nitrate radical (night time) in the atmosphere (Arey et al., 1987; IARC 1989; Atkinson and Arey 1994; Reisen and Arey 2005). Therefore, ambient concentrations of 1-nitro-naphthalene and 2-nitro-naphthalene are dependent on atmospheric concentrations of naphthalene and photochemical reaction activity. As a major source of ambient naphthalene, the vehicle emissions were reduced from the pre-Olympics to the during-Olympics, followed by a 31% reduction in ambient naphthalene (Wang et al., 2011). Furthermore, He et al. (2010) found that hydrogen peroxide, an important precursor of the hydroxyl radical, was significantly decreased from the 29th of July (before the Olympics) to the 15th of August (during the Olympic full-scale control period) (He et al., 2010). Both of the above findings were favorable to a low level of ambient naphthalene and free radical gas-phase reaction activities. In fact, Wang et al. (2011) reported a 28% (p=0.002) reduction in 2-nitro-naphthalene concentration during the Olympic period compared to the non-Olympic period (Wang et al., 2011). In the current study, we observed reductions in urinary 1&2-amino-naphthalene (regardless adjustments for creatinine) from the pre- to the during-Olympic period, consistent with reduced concentrations of nitro-naphthalene from which 1&2-amino-naphthalene were derived inside the human body. After the Olympics when all the traffic control measures were relaxed, the concentration of 1&2-amino-naphthalene went up to the level in the pre-Olympic period (Table 2). This finding suggests that 1&2-amino-naphthalene might be a biomarker of exposure to both general traffic-emitted pollutants and secondary sources. A similar conclusion was obtained by Neophytou et al. (2014) as well, whose findings suggested associations of 1&2-amino-naphthalene with more general measures of traffic-related air pollution (Neophytou et al., 2014).

As the most abundant metabolite of pyrene, 1-hydroxy-pyrene may be used as a biomarker of exposure to airborne pryrene or the total PAHs when dietary and other sources of PAHs are not important (Strickland and Kang 1999). In the current study, we observed significant reductions in urinary 1-hydroxy-pyrene (using the creatinine-independent method) from the pre- to the during-Olympic period, following the changes in air pollutants (Table 1). It may suggest urinary 1-hydroxy-pyrene as a biomarker of exposure to general traffic-emitted pollutants. After the Olympics, the level of 1-hydroxy-pyrene remained the same as in the during-Olympic period. It is notable that in the post-Olympic period when the traffic control measures were relaxed, the traffic emissions increased as reflected by increased atmospheric concentrations of CO, NO2, PN, etc. (Table 1). Meanwhile, the concentration of PM2.5-bound pyrene continued to decrease by −59% from the during- to the post-Olympics. Therefore, it may also suggest that urinary 1-hydroxy-pyrene may serve as a biomarker of exposure to ambient pyrene.

The associations between the PAH metabolites and the individual air pollutants further confirm the findings we obtained from the period-specific comparisons discussed above. As shown in Figure 1A, urinary 1&2-amino-naphthalene was significantly associated with the air pollutants from both primary sources, including CO, SO2, NO2, PM2.5, PN, EC, pyrene, and the total PAHs, and secondary sources, such as PM2.5, sulfate, and nitrate. Wang et al. (2011) also reported that the greater formation of nitro-PAHs after the Olympic compared to the Olympic period was the result of both meteorological conditions and increased vehicle emissions (Wang et al., 2011). Figure 1B showed that 1-amino-pyrene was significantly associated with primary pollutants, like NO2, PM2.5, EC, and PN, but not with CO (a good indicator of general vehicle emissions) (Reisen and Arey 2005). In Figure 1C, we found that 1-hydroxy-pyrene was significantly associated with all the measured pollutants except ozone, which was consistent with the findings in the period comparison, and both suggest that 1-hydroxy-pyrene is a good marker of exposure to traffic-emitted pollutants. Notably that the total PAHs showed significant associations with 1&2-amino-naphthalene and 1-hydroxy-pyrene at lag 2, but not with 1-amino-pyrene (Figure 1). Since the total PAH was correlated with both the primary and secondary pollutants (Table 2), these findings suggest that 1&-2-amino-naphthalene and 1-hydroxy-pyrene were biomarkers of exposure to general traffic-emitted and secondary pollutants, while the sources contributing to urinary 1-amino-pyrene was more complicated which might be a mixture of vehicle exhaust in general and other medias that contain 1-nitro-pyrene.

In addition, the lag analysis on the associations between the amino-PAH metabolites and individual air pollutants can provide insights about the kinetics of nitro-PAHs from exposure to excretion in the urine. In Figure 1A and 1B, we consistently found an inverted ‘U’ shape for the changing patterns of the associations between the amino-PAHs and the air pollutants from lag 0 to 3, with the largest changes consistently appearing at lag 1 or lag 2. These observations indicate that the time of the maximum excretion of 1&2-amino-naphthalene and 1-amino-pyrene was likely to occur between 24 to 72 hours after nitro-PAH exposure. Huyck et al. (2010) estimated the time of maximum excretion of urinary 1-amino-pyrene, which was measured from healthy volunteers after a controlled diesel exhaust exposure; and they found that about one third of the subjects had maximum excretion times longer than 24 hours, while the rest had a median time of maximum excretion of 5.37 hours (Huyck et al., 2010).

Ozone was associated with the amino-PAHs in a nearly opposite pattern, in terms of statistical significance, to the associations between amino-PAHs and other traffic-related pollutants (Figure 1A and 1B). Similar findings were also reported in other related studies, which were mainly attributed to the negative correlations between ozone and other traffic-related pollutants (Huang et al., 2012; Rich et al., 2012; Gong et al., 2013). In the current study, we observed that ozone was negatively correlated with NO2 (r=−0.58, p<0.01), PN (−0.33, p<0.01), EC (r=−0.30, p<0.01), and CO (r=0.13, p>0.05) (Table 3).

The current study suggests that creatinine adjustments are necessary in the analysis of urinary biomarkers, since we found that the two creatinine adjustments affected both the between-period comparison of the three metabolites and their associations with the air pollutants in different extents. By using the creatinine-standardized method, the period effects on the three metabolites and their associations with the air pollutants were largely weakened in terms of both the magnitude and the significance (Table 2 and Appendix III). Gong et al. (2013) reported similar findings on urinary malondialdehyde (a biomarker of lipid peroxidation), namely that the period specific changes and associations with air pollutants became non- or less significant after the adjustment for creatinine using creatinine-standardized method (Gong et al., 2013). Both studies suggest that the creatinine-standardized method might result in a decrease in the sensitivity of the statistical analysis by introducing additional errors in studies comparing within-subject effects. In comparison, when creatinine was controlled as an independent variable in the mixed-effects models, the associations between the three metabolites and the air pollutants showed more significant results. Therefore, controlling creatinine as an independent variable in the applied models showed a more moderate adjusting effect than standardizing the biomarker levels by creatinine.

Besides inhalation of PM2.5, there are multiple other sources of nitro-PAH exposure. For example, inhalation of larger ambient particles (PM2.5–10) that contains 1-nitro-pyrene inhalation of gas-phase 1-nitro-pyrene, dermal exposure to the particulate- and gas-phase 1-nitro-pyrene, and ingestion of diet (including water and food) that contains 1-nitro-pyrene. 1-nitro-pyrene in all the exposure routes will result in the formation of 1-amino-pyrene. Although there have been other sources contributing to the measured levels of amino-PAH, these sources appear to be relatively constant within the same individual. Our study design enabled us to observe significant within-individual temporal changes in amino-PAH concentrations driven by anticipated temporal changes in nitro-PAH concentrations as a result of source control during the Beijing Olympics. Though traffic-related nitro-PAH exposure was not measured simultaneously with the urinary amino-PAH measurements, by comparing the period-specific changes of the amino-PAHs and associating them with the primary and secondary pollutants, we found evidence to support the use of 1&2-amino-naphthalene and 1-hydroxy-pyrene as internal markers for exposure to general vehicle-emission sources, and more data are need to support the utilization of 1-amino-pyrene as a biomarker of exposure to diesel-combustion emission.

Through the between-period comparison of the three PAH metabolites and their associations with the traffic-emitted pollutants, the current study found evidence that 1&2-amino-naphthalene and 1-hydroxy-pyrene can be used as biomarkers of exposure to general vehicle-emitted pollutants, and more data are needed to confirm 1-amino-pyrene as a biomarker of exposure to diesel combustion emissions. We also found that controlling creatinine as an independent variable in the applied models will provide a moderate adjusting effect on the biomarker analysis.

Supplementary Material

NIHMS723700-supplement.docx (356.3KB, docx)

Highlights.

  1. Urinary polycyclic aromatic hydrocarbon metabolites were analyzed as exposure markers.

  2. Associations were found between polycyclic aromatic hydrocarbon metabolites and general traffic emissions.

  3. More data are needed for associations between 1-amino-pyrene and diesel exhaust particles.

  4. Adjustment for creatinine is essential in urinary biomarker analyses.

ACKNOWLEDGEMENTS

We acknowledge the study participants for their commitment to the study and to the students and staff members at Peking University and Peking University First Hospital for their assistance with sample and data collection. This study was jointly funded by grants 1R01ES015864, P30ES005022, and 5P30ES007048 from the National Institute of Environmental Health Sciences, 4760-RPFA05-3 from the Health Effects Institute, OITC-G08026056 from the Beijing Environment Protection Bureau, and HB200504-6, HB200504-2 from the Beijing Council of Science and Technology.

Footnotes

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CONFLICT OF INTEREST

The authors declare no conflict of interest.

References

  1. Arey J, Arkinson R. Photochemical reactions of PAHs in the Atmosphere. Chichester, England: John Wiley & Sons; 2003. [Google Scholar]
  2. Arey J, Zielinska B, Atkinson R, Winer AM. Polycyclic Aromatic Hydrocarbon and Nitroarene Concentrations in Ambient Air during a Wintertime High-Nox Episode in the Los-Angeles Basin. Atmospheric Environment. 1987;21(6):1437–1444. [Google Scholar]
  3. Atkinson R, Arey J. Atmospheric Chemistry of Gas-Phase Polycyclic Aromatic-Hydrocarbons - Formation of Atmospheric Mutagens. Environmental Health Perspectives. 1994;102:117–126. doi: 10.1289/ehp.94102s4117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bamford HA, Baker JE. Nitro-polycyclic aromatic hydrocarbon concentrations and sources in urban and suburban atmospheres of the Mid-Atlantic region. Atmospheric Environment. 2003;37(15):2077–2091. [Google Scholar]
  5. Dimashki M, Harrad S, Harrison RM. Measurements of nitro-PAH in the atmospheres of two cities. Atmospheric Environment. 2000;34(15):2459–2469. [Google Scholar]
  6. Feilberg A, Poulsen MWB, Nielsen T, Skov H. Occurrence and sources of particulate nitro-polycyclic aromatic hydrocarbons in ambient air in Denmark. Atmospheric Environment. 2001;35(2):353–366. [Google Scholar]
  7. Gong J, Zhu T, Kipen H, Wang G, Hu M, Ohman-Strickland P, Lu SE, Zhang L, Wang Y, Zhu P, Rich DQ, Diehl SR, Huang W, Zhang JJ. Malondialdehyde in exhaled breath condensate and urine as a biomarker of air pollution induced oxidative stress. J Expo Sci Environ Epidemiol. 2013;23(3):322–327. doi: 10.1038/jes.2012.127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. He LY, Hu M, Huang XF, Zhang YH, Tang XY. Seasonal pollution characteristics of organic compounds in atmospheric fine particles in Beijing. Science of the Total Environment. 2006;359(1–3):167–176. doi: 10.1016/j.scitotenv.2005.05.044. [DOI] [PubMed] [Google Scholar]
  9. He SZ, Chen ZM, Zhang X, Zhao Y, Huang DM, Zhao JN, Zhu T, Hu M, Zeng LM. Measurement of atmospheric hydrogen peroxide and organic peroxides in Beijing before and during the 2008 Olympic Games: Chemical and physical factors influencing their concentrations. Journal of Geophysical Research-Atmospheres. 2010;115(D17307) [Google Scholar]
  10. Hu Y, Zhou Z, Xue X, Li X, Fu J, Cohen B, Melikian AA, Desai M, Tang M, Huang X, Roy N, Sun J, Nan P, Qu Q. Sensitive biomarker of polycyclic aromatic hydrocarbons (PAHs): urinary 1-hydroxyprene glucuronide in relation to smoking and low ambient levels of exposure. Biomarkers. 2006;11(4):306–318. doi: 10.1080/13547500600626883. [DOI] [PubMed] [Google Scholar]
  11. Huang W, Wang G, Lu SE, Kipen H, Wang Y, Hu M, Lin W, Rich D, Ohman-Strickland P, Diehl S, Zhu P, Gong J, Tong J, Zhu T, Zhang J. Inflammatory and oxidative stress responses of healthy young adults to changes in air pollution levels during the Beijing Olympics. American Journal of Respiratory and Critical Care Medicine. 2012;186(11):1150–1159. doi: 10.1164/rccm.201205-0850OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Huang XF, He LY, Hu M, Zhang YH. Annual variation of particulate organic compounds in PM2.5 in the urban atmosphere of Beijing. Atmospheric Environment. 2006;40(14):2449–2458. [Google Scholar]
  13. Huyck S, Ohman-Strickland P, Zhang L, Tong J, Xu XU, Zhang JJ. Determining times to maximum urine excretion of 1-aminopyrene after diesel exhaust exposure. J Expo Sci Environ Epidemiol. 2010;20(7):650–655. doi: 10.1038/jes.2010.29. [DOI] [PubMed] [Google Scholar]
  14. IARC. Monographs on the evaluation of carcinogenic risks to humans. Diesel and gasoline engine exhausts and some nitroarenes. International Agency for Research on Cancer. IARC Monogr Eval Carcinog Risks Hum. 1989;46:1–458. [PMC free article] [PubMed] [Google Scholar]
  15. Laumbach R, Tong J, Zhang L, Ohman-Strickland P, Stern A, Fiedler N, Kipen H, Kelly-McNeil K, Lioy P, Zhang J. Quantification of 1-aminopyrene in human urine after a controlled exposure to diesel exhaust. Journal of Environmental Monitoring. 2009;11(1):153–159. doi: 10.1039/b810039j. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Marino F, Cecinato A, Siskos PA. Nitro-PAH in ambient particulate matter in the atmosphere of Athens. Chemosphere. 2000;40(5):533–537. doi: 10.1016/s0045-6535(99)00308-2. [DOI] [PubMed] [Google Scholar]
  17. Nachtman JP, Wei ET. Evidence for enzymatic reduction of 1-nitropyrene by rat liver fractions. Experientia. 1982;38(7):837–838. doi: 10.1007/BF01972302. [DOI] [PubMed] [Google Scholar]
  18. Neophytou AM, Hart JE, Chang Y, Zhang JJ, Smith TJ, Garshick E, Laden F. Short-term traffic related exposures and biomarkers of nitro-PAH exposure and oxidative DNA damage. Toxics. 2014;2(3):377–390. doi: 10.3390/toxics2030377. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Paputapeck MC, Marano RS, Schuetzle D, Riley TL, Hampton CV, Prater TJ, Skewes LM, Jensen TE, Ruehle PH, Bosch LC, Duncan WP. Determination of Nitrated Polynuclear Aromatic-Hydrocarbons in Particulate Extracts by Capillary Column Gas-Chromatography with Nitrogen Selective Detection. Analytical Chemistry. 1983;55(12):1946–1954. [Google Scholar]
  20. Poirier LA, Weisburger JH. Enzymic reduction of carcinogenic aromatic nitro compounds by rat and mouse liver fractions. Biochem Pharmacol. 1974;23(3):661–669. doi: 10.1016/0006-2952(74)90631-5. [DOI] [PubMed] [Google Scholar]
  21. Reisen F, Arey J. Atmospheric reactions influence seasonal PAH and nitro-PAH concentrations in the Los Angeles basin. Environmental Science & Technology. 2005;39(1):64–73. [PubMed] [Google Scholar]
  22. Rich DQ, Kipen HM, Huang W, Wang G, Wang Y, Zhu P, Ohman-Strickland P, Hu M, Philipp C, Diehl S, Lu SE, Tong J, Gong J, Thomas D, Zhu T, Zhang J. Association between changes in air pollution levels during the Beijing Olympics and biomarkers of inflammation and thrombosis in healthy young adults. The Journal of the American Medical Association. 2012;307(19):2068–2078. doi: 10.1001/jama.2012.3488. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Scheepers PTJ, Fijneman PHS, Beenakkers MFM, Delepper AJGM, Thuis HJTM, Stevens D, Vanrooij JGM, Noordhoek J, Bos RP. Immunochemical Detection of Metabolites of Parent and Nitro Polycyclic Aromatic-Hydrocarbons in Urine Samples from Persons Occupationally Exposed to Diesel Exhaust. Fresenius Journal of Analytical Chemistry. 1995;351(7):660–669. [Google Scholar]
  24. Schuetzle D, Riley TL, Prater TJ, Harvey TM, Hunt DF. Analysis of Nitrated Polycyclic Aromatic-Hydrocarbons in Diesel Particulates. Analytical Chemistry. 1982;54(2):265–271. [Google Scholar]
  25. Seidel A, Dahmann D, Krekeler H, Jacob J. Biomonitoring of polycyclic aromatic compounds in the urine of mining workers occupationally exposed to diesel exhaust. Int J Hyg Environ Health. 2002;204(5–6):333–338. doi: 10.1078/1438-4639-00116. [DOI] [PubMed] [Google Scholar]
  26. Strickland P, Kang D. Urinary 1-hydroxypyrene and other PAH metabolites as biomarkers of exposure to environmental PAH in air particulate matter. Toxicol Lett. 1999;108(2–3):191–199. doi: 10.1016/s0378-4274(99)00089-2. [DOI] [PubMed] [Google Scholar]
  27. Talaska G, Underwood P, Maier A, Lewtas J, Rothman N, Jaeger M. Polycyclic aromatic hydrocarbons (PAHs), nitro-PAHs and related environmental compounds: biological markers of exposure and effects. Environ Health Perspect. 1996;104(Suppl 5):901–906. doi: 10.1289/ehp.96104s5901. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. van Bekkum YM, van den Broek PHH, Scheepers PTJ, Bos RP. Sensitive and selective detection of urinary 1-nitropyrene metabolites following administration of a single intragastric dose of diesel exhaust particles (SRM 2975) to rats. Chemical Research in Toxicology. 1998;11(11):1382–1390. doi: 10.1021/tx980162x. [DOI] [PubMed] [Google Scholar]
  29. Wang M, Zhu T, Zheng J, Zhang RY, Zhang SQ, Xie XX, Han YQ, Li Y. Use of a mobile laboratory to evaluate changes in on-road air pollutants during the Beijing 2008 Summer Olympics. Atmospheric Chemistry and Physics. 2009a;9(21):8247–8263. [Google Scholar]
  30. Wang SX, Zhao M, Xing J, Wu Y, Zhou Y, Lei Y, He KB, Fu LX, Hao JM. Quantifying the Air Pollutants Emission Reduction during the 2008 Olympic Games in Beijing. Environmental Science & Technology. 2010;44(7):2490–2496. doi: 10.1021/es9028167. [DOI] [PubMed] [Google Scholar]
  31. Wang T, Xie SD. Assessment of traffic-related air pollution in the urban streets before and during the 2008 Beijing Olympic Games traffic control period. Atmospheric Environment. 2009;43(35):5682–5690. [Google Scholar]
  32. Wang W, Jariyasopit N, Schrlau J, Jia Y, Tao S, Yu TW, Dashwood RH, Zhang W, Wang X, Simonich SL. Concentration and photochemistry of PAHs, NPAHs, and OPAHs and toxicity of PM2.5 during the Beijing Olympic Games. Environ Sci Technol. 2011;45(16):6887–6895. doi: 10.1021/es201443z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Wang X, Westerdahl D, Chen LC, Wu Y, Hao JM, Pan XC, Guo XB, Zhang KM. Evaluating the air quality impacts of the 2008 Beijing Olympic Games: On-road emission factors and black carbon profiles. Atmospheric Environment. 2009b;43(30):4535–4543. [Google Scholar]
  34. Westerdahl D, Wang X, Pan X, Zhang KM. Characterization of on-road vehicle emission factors and microenvironmental air quality in Beijing, China. Atmospheric Environment. 2009;43(3):697–705. [Google Scholar]
  35. Zhang J, Zhu T, Kipen H, Wang G, Huang W, Rich D, Zhu P, Wang Y, Lu S, Ohman-stricklan P, Diehl SR, Hu M, Tong J, Gong J, Thomas D. Cardiorespiratory Biomarker Responses in Healthy Young Adults to Drastic Air Quality Changes Surrounding the 2008 Beijing Olympics. Res Rep Health Eff Inst. 2013;174:5–174. [PMC free article] [PubMed] [Google Scholar]
  36. Zimmermann K, Jariyasopit N, Simonich SLM, Tao S, Atkinson R, Arey J. Formation of Nitro-PAHs from the Heterogeneous Reaction of Ambient Particle-Bound PAHs with N2O5/NO3/NO2. Environmental Science & Technology. 2013;47(15):8434–8442. doi: 10.1021/es401789x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Zwirner-Baier I, Neumann HG. Polycyclic nitroarenes (nitro-PAHs) as biomarkers of exposure to diesel exhaust. Mutat Res. 1999;441(1):135–144. doi: 10.1016/s1383-5718(99)00041-8. [DOI] [PubMed] [Google Scholar]

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