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

Anna Font, Anja Tremper, Chun Lin, Max Priestman, Daniel Marsh, Michael Woods, M. R. Heal, David Green

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number114284
JournalENVIRONMENTAL POLLUTION
Volume262
Early online date12 Mar 2020
DOIs
Publication statusPublished - Jul 2020

Keywords

  • Diesel exhaust
  • Diesel trains
  • Enclosed railway stations
  • Random forest

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