Air quality in enclosed railway stations: Quantifying the impact of diesel trains through deployment of multi-site measurement and random forest modelling

TY - JOUR

T1 - Air quality in enclosed railway stations: Quantifying the impact of diesel trains through deployment of multi-site measurement and random forest modelling

AU - Font, Anna

AU - Tremper, Anja

AU - Lin, Chun

AU - Priestman, Max

AU - Marsh, Daniel

AU - Woods, Michael

AU - Heal, M. R.

AU - Green, David

PY - 2020/7

Y1 - 2020/7

N2 - Concentrations of the air pollutants (NO 2 and particulate matter) were measured for several months and at multiple locations inside and outside two enclosed railway stations in the United Kingdom – Edinburgh Waverly (EDB) and London King's Cross (KGX) – which, respectively, had at the time 59% and 18% of their train services powered by diesel engines. Average concentrations of NO 2 were above the 40 μg m −3 annual limit value outside the stations and were further elevated inside, especially at EDB. Concentrations of PM 2.5 inside the stations were 30–40% higher at EDB than outside and up to 20% higher at KGX. Concentrations of both NO 2 and PM 2.5 were highest closer to the platforms, especially those with a higher frequency of diesel services. A random-forest regression model was used to quantify the impact of numbers of different types of diesel trains on measured concentrations allowing prediction of the impact of individual diesel-powered rolling stock.

AB - Concentrations of the air pollutants (NO 2 and particulate matter) were measured for several months and at multiple locations inside and outside two enclosed railway stations in the United Kingdom – Edinburgh Waverly (EDB) and London King's Cross (KGX) – which, respectively, had at the time 59% and 18% of their train services powered by diesel engines. Average concentrations of NO 2 were above the 40 μg m −3 annual limit value outside the stations and were further elevated inside, especially at EDB. Concentrations of PM 2.5 inside the stations were 30–40% higher at EDB than outside and up to 20% higher at KGX. Concentrations of both NO 2 and PM 2.5 were highest closer to the platforms, especially those with a higher frequency of diesel services. A random-forest regression model was used to quantify the impact of numbers of different types of diesel trains on measured concentrations allowing prediction of the impact of individual diesel-powered rolling stock.

KW - Diesel exhaust

KW - Diesel trains

KW - Enclosed railway stations

KW - Random forest

UR - https://www.scopus.com/pages/publications/85081662707

U2 - 10.1016/j.envpol.2020.114284

DO - 10.1016/j.envpol.2020.114284

M3 - Article

SN - 0269-7491

VL - 262

JO - ENVIRONMENTAL POLLUTION

JF - ENVIRONMENTAL POLLUTION

M1 - 114284

ER -