Dataset Information

PM_2.5 on the London Underground.

ABSTRACT:

Introduction

Despite the London Underground (LU) handling on average 2.8 million passenger journeys per day, the characteristics and potential health effects of the elevated concentrations of metal-rich PM_2.5 found in this subway system are not well understood.

Methods

Spatial monitoring campaigns were carried out to characterise the health-relevant chemical and physical properties of PM_2.5 across the LU network, including diurnal and day-to-day variability and spatial distribution (above ground, depth below ground and subway line). Population-weighted station PM_2.5 rankings were produced to understand the relative importance of concentrations at different stations and on different lines.

Results

The PM_2.5 mass in the LU (mean 88??g?m^-3, median 28??g?m^-3) was greater than at ambient background locations (mean 19??g?m^-3, median 14??g?m^-3) and roadside environments in central London (mean 22??g?m^-3, median 14??g?m^-3). Concentrations varied between lines and locations, with the deepest and shallowest submerged lines being the District (median 4??g?m^-3) and Victoria (median 361??g?m^-3 but up to 885??g?m^-3). Broadly in agreement with other subway systems around the world, sampled LU PM_2.5 comprised 47% iron oxide, 7% elemental carbon, 11% organic carbon, and 14% metallic and mineral oxides. Although a relationship between line depth and air quality inside the tube trains was evident, there were clear influences relating to the distance from cleaner outside air and the exchange with cabin air when the doors open. The passenger population-weighted exposure analysis demonstrated a method to identify stations that should be prioritised for remediation to improve air quality.

Conclusion

PM_2.5 concentrations in the LU are many times higher than in other London transport Environments. Failure to include this environment in epidemiological studies of the relationship between PM_2.5 and health in London is therefore likely to lead to a large exposure misclassification error. Given the significant contribution of underground PM_2.5 to daily exposure, and the differences in composition compared to urban PM_2.5, there is a clear need for well-designed studies to better understand the health effects of underground exposure.

SUBMITTER: Smith JD

PROVIDER: S-EPMC6902242 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

PM<sub>2.5</sub> on the London Underground.

Smith J D JD Barratt B M BM Fuller G W GW Kelly F J FJ Loxham M M Nicolosi E E Priestman M M Tremper A H AH Green D C DC

Environment international 20191128

<h4>Introduction</h4>Despite the London Underground (LU) handling on average 2.8 million passenger journeys per day, the characteristics and potential health effects of the elevated concentrations of metal-rich PM<sub>2.5</sub> found in this subway system are not well understood.<h4>Methods</h4>Spatial monitoring campaigns were carried out to characterise the health-relevant chemical and physical properties of PM<sub>2.5</sub> across the LU network, including diurnal and day-to-day variability a ...[more]

PMID: 31787325

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Project description:The availability of low-cost monitors marketed for use in homes has increased rapidly over the past few years due to the advancement of sensing technologies, increased awareness of urban pollution, and the rise of citizen science. The user-friendly packages can make them appealing for use in research grade indoor exposure assessments, but a rigorous scientific evaluation has not been conducted for many monitors on the open market, which leads to uncertainty about the validity of the data. Furthermore, many previous sensor studies were conducted for a relatively short period of time, which may not capture the changes this type of instrument may exhibit over time (known as sensor aging). We evaluated three monitors (AirVisual Pro, Speck, and AirThinx) in an occupied, non-smoking residence over a 12-month period in order to assess the sensors, the built-in calibrations, and the need for additional data to achieve high accuracy for long deployments. Two units of each type of monitor were evaluated in order to assess the precision between units, and a personal DataRAM (pDR-1200) with a filter was placed in the home for about 20% of the sampling period (e.g., about a week each month) to evaluate the accuracy over time. The average PM2.5 mass concentration from the periods of colocation with the pDR were 5.31 μg/m3 for the gravimetric-corrected pDR (hereafter pDR-corrected), 5.11 and 5.03 μg/m3 for the AirVisual Pro units, 13.58 and 22.68 μg/m3 for the Speck units, and 7.56 and 7.57 μg/m3 for the AirThinx units. The AirVisual Pros exhibited the best accuracy compared to the filter at about 86%, which was slightly better than the nephelometric component of the pDR compared to the filter weight (84%). The accuracies of the Speck (-174 and -405%) and AirThinx (42 and 40%) monitors were much lower. When the 1-minute averaged PM2.5 mass concentrations were categorized by air quality index (AQI), the pDR-corrected matched the AirVisual Pro, Speck, and AirThinx bins about 97, 40, and 87% of the time, respectively. The Pearson correlation coefficients (R2) between the unit pairs and the pDR were 0.90/0.90, 0.50/0.27, and 0.92/0.93 for the AirVisual Pro, Speck, and AirThinx units, respectively. The R2 between units of the same type were 0.99, 0.17, and 1.00 for the AirVisual Pro, Speck, and AirThinx, respectively. All of the monitors could achieve better accuracy by adding filter corrections and post-processing to correct for known biases in addition to the manufacturer's correction routine. Monthly calibrations yielded the highest accuracies, but nearly as high of accuracies could be achieved with only one or two calibrations for the Air Visual Pro and the AirThinx for many applications. In general, this type of new low-cost monitor shows exciting potential for use in scientific research. However, only one of the three monitors exhibited high accuracy (within 20% of the true mass concentration) without any post processing or additional measurements, so an evaluation of each monitor is essential before the data can be used to confidently evaluate residential exposures.

Dataset Information

PM_2.5 on the London Underground.

Introduction

Methods

Results

Conclusion

Publications

PM<sub>2.5</sub> on the London Underground.

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Dataset Information

PM2.5 on the London Underground.

Introduction

Methods

Results

Conclusion

Publications

PM&lt;sub&gt;2.5&lt;/sub&gt; on the London Underground.

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OmicsDI is part of the ELIXIR infrastructure

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PM_2.5 on the London Underground.

PM<sub>2.5</sub> on the London Underground.