Characterization of PM and Microclimate in a Shanghai Subway Tunnel, China

Available online at www.sciencedirect.com

ScienceDirect Procedia Engineering 102 (2015) 1226 – 1232

The 7th World Congress on Particle Technology (WCPT7)

Characterization of PM and Microclimate in a Shanghai Subway Tunnel, China Ting Qiao a, Guangli Xiu a*, Yi Zheng b, Jun Yang c, Lina Wang a a

State Environmental Protection Key Laboratory of Risk Assessment and Control on Chemical Process, East China University of Science & Technology, Shanghai 200237, China b Technical Center of Shanghai Shentong Metro Group Co., Ltd., Shanghai 201103, China c Shanghai An-He Environmental Testing Technique Co., Ltd., Shanghai 201611, China

Abstract A real-time monitoring campaign was conducted from November 11th to November 15th, 2013 in a Shanghai subway tunnel, consisting of temperature (T), relative humidity (RH) and PM1, PM2.5 and PM10. The objective was to characterize PM and microclimate in the subway tunnel. Results indicated that median values of T, RH, PM1, PM2.5 and PM10 were 29.4ć, 29.6%, 42 μg/m3, 46 μg/m3 and 58 μg/m3, respectively. Air quality in the tunnel was comparatively good, with 76% of PM2.5 and 91% of PM10 reaching relative standards. Independent samples t-test verified that PM1, PM2.5 and PM10 presented significant statistical differences between peak hours and off-peak hours (p<0.05). Notable weekly variation emerged during monitoring periods, which of all particles was as following: Friday > Thursday > Monday, Tuesday > Wednesday. Ratios of PM1/PM10 and PM2.5/PM10 were 0.49–1.00 and 0.56–1.00, respectively, which were high in outage and low in operation of trains. This phenomenon might result from plenty of coarse particles generated by mechanical grinding in the process of train driving. © Published by Yi Elsevier Ltd. This is anLina openWang. accessPublished article under CC BY-NC-ND license © 2015 2014The TingAuthors. Qiao, Guangli Xiu, Zheng, Jun Yang, by the Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and peer-review under responsibility of Chinese Society of Particuology, Institute of Process Engineering, Selection and peer-review under responsibility of Chinese Society of Particuology, Institute of Process Engineering, Chinese Academy of Sciences (CAS). Chinese Academy of Sciences (CAS) Keywords: Subway; Tunnel; Microclimate; PM1; PM2.5; PM10

1. Introduction

Domestic and foreign researche[9] have discovered that PM concentration in subway environment is higher than that of outdoor environment. Epidemiological study[10] has found out that airborne particles had a certain relationship with plenty of adverse health impacts, such as respiratory and cardiovascular diseases. Furthermore, Karlsson et al demonstrated that subway PM was approximately eight times more genotoxic than street PM and resulted in four times oxidative stress in cultured human lung cells[11]. Du et al figured out that subway riders were exposed to the highest PM, Mn, Fe, and Ca concentrations by comparison with non-subway riders and taxi drivers[12]. Despite time spent in Metro system was comparative short, a rough estimate of the additional exposure caused by commuting via the subway in Helsinki manifested that the exposure to PM and metals increased a lot[3]. Tunnels, ventilation, and frequency of trains were suggested to be three important determinants of high levels of particulate matter in subway environments[13]. As a result, further work is needed to definitely characterize PM1, PM2.5 and PM10 in subway tunnels. Since the first line of Shanghai Railway Transit put into service in 1993, fourteen lines have been put * Corresponding author. Tel.:+0-216-425-1927 ; fax: +0-216-425-1927. E-mail address: [email protected]

1877-7058 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license

(http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and peer-review under responsibility of Chinese Society of Particuology, Institute of Process Engineering, Chinese Academy of Sciences (CAS)

doi:10.1016/j.proeng.2015.01.250

Ting Qiao et al. / Procedia Engineering 102 (2015) 1226 – 1232

into operation until now, with 329 stations and 538 km total mileage. Despite the relatively short amount of time spent in public transportation microenvironments, indoor air quality in such environments was a key area of concern. As a result, the impacts of air pollutants on human health in the subway environment should be paid extra attention to. Ye et al conducted a field study in Shanghai subway, who discovered that higher PM concentration might be a major problem for passengers on subway platforms (PM1=231±152μg/m3, PM2.5=287±177μg/m3, PM10=366±193μg/m3)[14]. So far, researches on PM in Shanghai subway environment have focused on compartments[15], platforms[16] and concourses[17], with few studies about air pollutants in tunnels. Apart from input of outdoor air pollutants, internal sources of subway should not be neglected, mainly composing of mechanical deterioration between conductor rails, electrodes, brake pads, rails and wheels. The most pivotal approach to improve subway air quality is to understand the characteristics of PM and the contribution of specific internal sources. Therefore, the objective of this study was to have a preliminary command of PM variation in the subway tunnel. The real-time monitoring site was fixed in a Shanghai subway tunnel. The microclimate was also characterized in the meanwhile through detecting temperature and relative humidity. PM1, PM2.5 and PM10 were simultaneously monitored to investigate the difference among particles of different dimensions. 2. Materials and Methods 2.1. Sampling Site A real-time monitoring campaign (sampling from Nov 11 th to Nov 15th, 2013), consisting of temperature (T), relative humidity (RH) and particulate matter (PM), was conducted in the tunnel adjacent to a Shanghai subway station. The subway station locates in downtown area, a transfer junction of three lines. Its passenger traffic remains high annually, which is one of the main transfer stations in Shanghai Railway Transit. It is an underground station, with a mechanical ventilation system. The fixed sampling site was situated about 10m far away from the open space of platform of the subway station. 2.2. Sampling Methods PM sampler was a DustTrak DRX 8534 Aerosol Detector (TSI, Inc., Shoreview, MN, USA). The apparatus combines the principle of a photometer and an optical particle counter (short as OPC), thus can simultaneously measure mass concentration and size distribution. The quality of this equipment is 1.3kg, with its dimension 12.5cm×12.1cm ×31.6cm. Sampling interval was designed to be 5 min and flow rate were set at 3.0 L/min. Mass concentration of PM1, PM2.5 and PM10 were recorded at the same time. Two HOBO U10–003 Temperature/Relative Humidity Recorders (Oneset, Inc., Irvine, CA, USA) were also employed, with its weight of 28 g, dimension of 6.0 cm× 4.7 cm× 1.9 cm and record interval of 5 min. A DustTrak and two HOBOs were placed in a metal box and then fixed on the wall of the tunnel. The metal box was 1 m high apart from the ground, with its sampling port straight facing with the direction trains come. Outdoor PM1 was sampled by PQ200 Ambient Fine Particle Sampler (BGI, Inc., Waltham, MA, USA) on the rooftop of Eighth Laboratory Building in East China University of Science and Technology. No stationary sources can be found around the sampling site. Sampling interval and flow rate were set at 24 h and 16.7 L/min, respectively. Historical meteorological data of Shanghai Hongqiao Airport (32.2°N, 121.3°E, altitude 3m) was adopted in this study, which was released by Weather Underground (http://www.wunderground.com/history/airport/). 2.3. Statistical Approach Based on the non-normal distribution of PM concentration (p<0.05) by Shapiro-Wilk Statistical test, median value was adopted to describe the average value. Nevertheless, most results in literatures are expressed by mean values. Consequently, median and mean values are employed meanwhile for later comparison with PM concentration in different sampling sites. SPSS software (version 13.0) was applied for the statistical analysis. The concentration difference between rush hours and non-rush hours was analyzed for its statistical significance with independent samples t-test. One-way ANOVA and Duncan’s multiple comparison analysis methods were introduced for demonstrating the difference in PM concentration levels among different monitoring days.

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3. Results and Discussion 3.1. Microclimate in the Tunnel Microclimate mainly includes temperature, relative humidity and wind speed, while monitor of wind speed was not involved in this study since ventilation system had not been installed in the tunnel of that subway station. Monitoring results are definitely shown in Table 1. Temperature thresholds adopted maximum temperature of summer and minimum of winter in subway tunnels stipulated by (GB50157–2003). When train compartments have installed with air conditioners, maximum value in summer is 35ć without Platform Screen Doors (short as PSDs). At the same time, minimum value in winter regulated is 5ć. It is important to note that the monitored Metro line hasn’t equipped with PSDs. As standards of RH and PM concentration in subway tunnels have not implemented, relevant standards are applied in this paper. RH (40%–80%) specified in (GB/T 18883–2002) are adopted as a standard value. From Table 1, it could be found that 100% data of temperature reached relevant standards in the Shanghai subway tunnel. Yet, not all the data of RH in the monitoring periods ranged within the regulated scope. RH outside the subway station varied from 32% to 93% during Nov 11 th to 15th. Therefore, the noncompliance of RH might be ascribed to poor internal condition of the tunnel, which might be associated with uninstallation of PSDs. The PSD system can provide highly effective controls on heating, ventilation, and air–conditioning[18]. As a fact of matter, RH of indoor air has direct or indirect influence on body health and comfort. When RH fell down to 40%, the infection rate of upper respiratory tract would increase. If RH had kept lower than 30% for a long time, discomfort and skin irritation would be given rise to, such as prurigo, erythema, etc [19],[20]. Therefore, installation of PSDs with an improved ventilating system should take into account as one option to seek for air quality maintenance in such a huge Metro system as Shanghai subway system. Temperature in tunnels increased when trains started operating, and then slightly decreased but still maintained at a relative high level. After cease operating, temperature descended to the ambient temperature. On the other hand, the variation of RH was just opposite to that of temperature. As ventilation system was not involved in tunnels, temperature values in this paper were all higher than those recorded in literatures[21],[22]. RH was similar to values (39%–66.2%)[14] that Ye et al monitored in Shanghai railway station, slightly lower than values (60%–86%)[3] Aarnio et al detected in the Helsinki subway system, which might be connected with different climates of Shanghai and Helsinki. Table 1

Monitoring results in a Shanghai subway tunnel

Content

Range

Median

Average ±SD

Standards

Temperature (ć)

21.8–30.5

29.4

28.9±1.2

5–35

RH (%)

25.2–57.6

29.6

30.9±4.1

40–80

PM1 (μg/m3)

12–183

42

58±45

/

PM2.5 (μg/m3)

13–190

46

61±45

75

14–234

58

71±46

150

3

PM10 (μg/m )

3.2. PM in the Tunnel During monitoring periods, median concentration of PM1, PM2.5 and PM10 were 42 μg/m3, 46 μg/m3 and 58 μg/m3 in the Shanghai subway tunnel, respectively. Specific results were summarized in Table 1. Park et al discovered that the average PM10 mass concentration in Seoul Metro Line complied with the following order: tunnel > platform > waiting room > outside [23]. The threshold of PM10 (150 μg/m3) limited in (GB/T 18883–2002) was adopted as a standard value. In addition, second standard of PM2.5 daily mean value (75 μg/m3) in (GB3095–2012) was employed as a reference, while PM1 has no standards for reference yet. 76% of PM2.5 and 91% of PM10 reached relevant standards, respectively, demonstrating that air quality in the tunnel was comparatively good. PM concentration in this study was quite close to that of Yu et al(PM1=79±51μg/m3) [17] while far below than that of Ye et al(PM1=231±152μg/m3, PM2.5=287±177μg/m3, PM10=366±193μg/m3)[14]. Both experiments were marched in Shanghai Metro system, hence the evident discrepancy might be associated with different sampling appliances. DustTrak 8533 Aerosol Detector adopted by Yu et al employs fully identical principle to 8534. On the other hand, DustTrak 8520 Aerosol Detector used by Ye et al overestimated real PM concentration by 1.4–3.5 times[24]–[29]. Comparison with other sampling

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sites, PM concentration in this study was rather approach to that of Guangzhou(PM 2.5=44±11μg/m3, PM10=55±14μg/m3)[9], Hong Kong(PM2.5=39±9μg/m3, PM10=50±9μg/m3)[8], Taipei (PM2.5=7–100μg/m3, PM10=11–137μg/m3)[7], Mexico (PM2.5=60–93μg/m3, PM10=88–145μg/m3)[30] and Los Angeles (PM2.5=57±11μg/m3, PM10=78±17μg/m3)[5]. While in Seoul Metro System, PM concentration had a broad range, with PM2.5 82–176μg/m3 on the platform[31] and PM10 156–495μg/m3 in the tunnel, 61–205μg/m3 on the platform and 63–196μg/m3 in the concourse[23], respectively. Salma et al pointed out that differences of PM concentration in subway systems might come from different systems technologies (such as power supply, engineering system and braking system), ventilation systems and operating conditions[32]. 3.3. Temporal Variation of PM Concentration in the Tunnel Diurnal variation of PM concentration in a Shanghai subway tunnel was shown in Fig 1. Generally speaking, PM concentration increased when trains went into service, maintaining higher concentration PM

1

200

3

Concentration(μg/m )

250

150 100 50 0

2013/11/12

2013/11/13

2013/11/14

2013/11/15

2013/11/14

2013/11/15

2013/11/14

2013/11/15

Date

PM2.5

200

3

Concentration(μg/m )

250

150 100 50 0

2013/11/12

2013/11/13 Date PM

10

200

3

Concentration(μg/m )

250

150 100 50 0

2013/11/12

2013/11/13 Date

Fig 1

Diurnal variation of PM concentration in a Shanghai subway tunnel

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in peak hours. Once subway trains went out of service, PM concentration fell back to a lower level with the disappearance of internal sources in the tunnel. Nevertheless, Nov 14 th went against the regular pattern due to the sudden rise of outdoor PM, definitely shown in Fig 2. Rush hours for the monitored Metro Line are 07:00–09:30 in the morning of weekdays and 17:00–19:30 in the evening of weekdays except Friday. When it encounters with Friday, relative evening peak hours are from 14:00 to 20:30. As seen in Fig 1, diurnal variations of subway PM concentration on Nov 12th (Tuesday) and Nov 13th (Wednesday) were rather consistent with their rush hours, while Nov 14th (Thursday) fits less. Independent samples t–test was conducted for PM concentration between peak hours and off-peak hours, results turned out that PM1, PM2.5 and PM10 presented significant statistical differences (p<0.05). Yet this outcome was just opposite to results of most stations in Taipei rapid transit system studied by Cheng et al, apart from S1–B station[7]. Weekly variation of PM concentration was illustrated in Fig 2. Notable weekly variation emerged during the monitoring periods. Analytical results of one way ANOVA and Duncan’s multiple comparison analysis methods among different particles stating that PM concentration could be classified into four statistically significant levels: First level was Wednesday (Nov 13 th), with lowest PM concentration; second one was Tuesday (Nov 12th) and Monday (Nov 11th), with lower PM concentration; then was Thursday (Nov 14th), with higher PM concentration; last one was Friday (Nov 15th), with highest PM concentration. However, variation of PM concentration throughout whole week couldn’t be obtained due to short monitoring time. The reason for daily mean concentration of Friday higher than that of Monday might be connected with different outdoor concentration. In addition, overhaul proceeded in tunnels every Monday’s and Thursday’s evening might lead to higher concentration. 3.4. Ratios of PM1/PM10 and PM2.5/PM10 in the Tunnel Ratios of PM1/PM10 and PM2.5/PM10 were 0.49–1.00 and 0.56–1.00 in a Shanghai subway tunnel, respectively. PM1/PM10 and PM2.5/PM10 were higher when subway trains went out of service. Plenty of coarse particles have generated since trains starting operation, so that PM1/PM10 and PM2.5/PM10 fell to the minimum. Ratios rose slightly during operation, but still sustained at a low level. PM 2.5/PM10 in Taipei subway station ranged from 0.67 to 0.78[7]; PM2.5/PM10 were 0.76 on the ground and 0.73 underground in Los Angeles station[5]; while ratios of PM2.5/PM10 were 0.79[9] in Guangzhou and 0.72–0.78[8] in Hong Kong subway station, respectively, which were relatively close to the results of this study. Reasons for high ratios of PM1/PM10 and PM2.5/PM10 might be high filtering effect on coarse particles and low removal efficiency on fine particles of ventilation systems[8] and PSD systems[18] in subway stations. Furthermore, fine particles have longer residence time than coarse particles suspended in atmosphere. PM2.5/PM10 in Mexico, Paris, Seoul and Stockholm subway station were 0.56±0.09 [30], 0.29–0.31[31], 0.36[33] and 0.55[34], respectively. PM2.5/PM10 in above four cities were lower than that of this study, which might be associated with the overestimation of fine particles and underestimation of coarse particles by DustTrak 8534 Aerosol Detector[35]. However, different ratios of PM1/PM10 and PM2.5/PM10 in different subway environments were rational, because of different power systems, braking systems, ventilation systems and operating conditions. 200 PM1

160

PM2.5

140

Outdoor PM1

PM10

3

Concentration(μg/m )

180

120 100 80 60 40 20 0

Monday

Tuesday

Wednesday

Thursday

Friday

Date

Fig 2

Weekly variation of PM concentration in a Shanghai subway tunnel

Ting Qiao et al. / Procedia Engineering 102 (2015) 1226 – 1232

4. Conclusions Subway particle aerosols have been real-time monitored from Nov 11th to Nov 15th, 2013 in a Shanghai subway tunnel, focusing on microclimate (consisting of T and RH) in addition to PM10, PM2.5 and PM1. The following main conclusions were drawn: (1)Median values of temperature, RH, PM1, PM2.5 and PM10 in the subway tunnel were respectively 29.4ć, 29.6%, 42 μg/m3, 46 μg/m3 and 58 μg/m3. Air quality in the tunnel was comparatively good, with 76% of PM2.5 and 91% of PM10 reaching relevant standards; (2) Results of independent samples t–test indicated that PM1, PM2.5 and PM10 presented significant statistical differences between peak hours and off-peak hours (p<0.05); (3) Notable weekly variation emerged during monitoring periods, which of all particles was as following: Friday > Thursday > Monday, Tuesday > Wednesday, implying that subway PM concentration was concerned with train frequency, passenger traffic and internal maintenance; (4)Ratios of PM1/PM10 and PM2.5/PM10 in the tunnel were 0.49–1.00 and 0.56–1.00, respectively, which were high in outage and low in operation of trains. This phenomenon might result from plenty of coarse particles generated by mechanical grinding in the process of train driving. Acknowledgements Thanks to personnel and equipment support for this research provided by Shanghai An-He Environmental Testing Technique Co., Ltd. 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