The concentrations and composition of and exposure to fine particles (PM2.5) in the Helsinki subway system

Aarnio, Päivi; Yli‐Tuomi, Tarja; Kousa, Anu; Mäkelä, Timo; Hirsikko, Anne; Hämeri, Kaarle; Räisänen, Mika; Hillamo, Risto; Koskentalo, Tarja; Jantunen, Matti

doi:10.1016/j.atmosenv.2005.05.012

Cited by 279 publications

(204 citation statements)

References 20 publications

Supporting

Mentioning

175

Contrasting

Order By: Relevance

“…The exact fraction cannot be calculated from these data because the DMPS measured particles with D p Ͻ 500 nm and the aethalometer was connected to a PM 2.5 inlet. However, the BC concentrations correlated very weakly with PM 2.5 , as the time series presented by Aarnio et al 13 showed. The very good correlation with V and the bad correlation with PM 2.5 indirectly suggest that BC was mainly in the particle size range D p Ͻ 500 nm.…”

Section: Results and Discussion Subway Station Datamentioning

confidence: 78%

“…The main results of the campaign were presented earlier by Aarnio et al 13 In the campaign, measurements were carried out at two surface stations: one ground-level station and in subway cars. In this paper, the data of the measurements carried out at the underground subway station of Sörnäinen in the center of Helsinki from March 4 -18, 2004, are used.…”

Section: Measurementsmentioning

confidence: 99%

“…The measurement setup was described in detail by Aarnio et al 13 so here only a short summary is presented. The instruments were installed approximately 1 km from the tunnel entrance, on the roof of a maintenance room, approximately 4 m above the platform level.…”

Section: Measurementsmentioning

confidence: 99%

See 2 more Smart Citations

A Simple Procedure for Correcting Loading Effects of Aethalometer Data

Virkkula

Mäkelä

Hillamo

et al. 2007

Journal of the Air & Waste Management Association

Self Cite

437

332

View full text Add to dashboard Cite

A simple method for correcting for the loading effects of aethalometer data is presented. The formula BC CORRECTED ϭ (1 ϩ k ⅐ ATN) ⅐ BC NONCORRECTED , where ATN is the attenuation and BC is black carbon, was used for correcting aethalometer data obtained from measurements at three different sites: a subway station in Helsinki, an urban background measurement station in Helsinki, and a rural station in Hyytiälä in central Finland. The BC data were compared with simultaneously measured aerosol volume concentrations (V). After the correction algorithm, the BC-to-V ratio remained relatively stable between consequent filter spots, which can be regarded as indirect evidence that the correction algorithm works. The k value calculated from the outdoor sites had a clear seasonal cycle that could be explained by darker aerosol in winter than in summer. When the contribution of BC to the total aerosol volume was high, the k factor was high and vice versa. In winter, the k values at all wavelengths were very close to that obtained from the subway station data. In summer, the k value was wavelength dependent and often negative. When the k value is negative, the noncorrected BC concentrations overestimated the true concentrations.

show abstract

Section: Results and Discussion Subway Station Datamentioning

confidence: 78%

Section: Measurementsmentioning

confidence: 99%

See 1 more Smart Citation

A Simple Procedure for Correcting Loading Effects of Aethalometer Data

Virkkula

Mäkelä

Hillamo

et al. 2007

Journal of the Air & Waste Management Association

Self Cite

437

332

View full text Add to dashboard Cite

show abstract

“…Effects of outdoor PM concentrations PM concentrations inside both subway stations and trains are associated with those of ambient PM (Aarnio et al, 2005;Braniš, 2006;Kim et al, Jung et al, 2010). PM levels in ambient air and inside trains were measured to evaluate how the relation between these two was affected before and after installing PSDs (Table 1).…”

Section: Evaluation Of Pm Concentration Between Rush Hour and Non-rusmentioning

confidence: 99%

“…Underground subway stations have different characteristics relative to outdoor conditions, such as confined spaces and the presence of pollution emission sources. Thus, quite a few studies have been conducted to understand the air quality characteristics in subway systems (Aarnio et al, 2005;Adams et al, 2001;Braniš, 2006;Johansson and Johansson, 2003;Karlsson et al, 2006;Kim and Ro, 2010;Raut et al, 2009;Sohn et al, 2008;.…”

Section: Introductionmentioning

confidence: 99%

Installation of platform screen doors and their impact on indoor air quality: Seoul subway trains

Son¹,

Jeon²,

Lee³

et al. 2014

Journal of the Air & Waste Management Association

View full text Add to dashboard Cite

In this study, variations of particulate matter (PM) concentrations in subway trains following installation of platform screen doors (PSDs) in the Seoul subway system were investigated. PM samples were collected in the trains on subway lines 1-8 before and after installation of PSDs. It was found that the mean PM 10 concentration in the trains after PSDs installation increased significantly by 29.9% compared to that before installation. In particular, the increase of PM 10 in line 6 was the highest at 103%. When the relationship between PM 10 and PM 2.5 was compared, coefficients of determination (r 2 ) before and after PSDs installations were 0.696 and 0.169, respectively. This suggests that air mixing between the platform and the tunnel after PSDs installation was extremely restricted. In addition, the indoor/outdoor PM 10 ratio following PSDs installation increased from 1.32 to 2.97 relative to the period with no installed PSDs. Furthermore, this study revealed that PM levels in subway trains increased significantly after all underground PSDs were put in use. Several potential factors were examined that could result in this PM increase, such as train ventilation systems, operational conditions, passenger volume, subway depth, and the length of underground segments.Implications: PM 10 concentrations inside the subway trains increased after PSDs installation. This indicates that air quality in trains was very seriously impacted by PSDs. PM 10 levels were also influenced by the tunnel depth and length of the underground segments. To prevent the adverse effect on human health by PM 10 emitted from the tunnel, an applicable ventilation system to reduce PM 10 is required inside trains and tunnels.

show abstract