Publications by authors named "D C Beddows"

There is a body of evidence that ultrafine particles (UFP, those with diameters ≤ 100 nm) might have significant impacts on health. Accordingly, identifying sources of UFP is essential to develop abatement policies. This study focuses on urban Europe, and aims at identifying sources and quantifying their contributions to particle number size distribution (PNSD) using receptor modelling (Positive Matrix Factorization, PMF), and evaluating long-term trends of these source contributions using the non-parametric Theil-Sen's method.

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Article Synopsis
  • Atmospheric new particle formation (NPF) is the natural process of creating tiny particles (sub-10 nm) from gases, observed globally in various environments.
  • Although these particles impact total and ultrafine particle concentrations, there is limited research on their health effects largely due to a lack of specific identifiers in existing data.
  • This study introduces an automated machine learning algorithm that identifies NPF events from particle data across 65 global measurement sites from 1996 to 2023, facilitating future research on NPF.
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Studies revealed airports as a prominent source of ultrafine particles (UFP), which can disperse downwind to residential areas, raising health concerns. To expand our understanding of how air traffic-related emissions influence total particle number concentration (PNC) in the airport's surrounding areas, we conduct long-term assessment of airborne particulate exposure before and after relocation of air traffic from "Otto Lilienthal" Airport (TXL) to Berlin Brandenburg Airport "Willy Brandt" (BER) in Berlin, Germany. Here, we provide insights into the spatial-temporal variability of PNC measured in 16 schools recruited for Berlin-Brandenburg Air Study (BEAR).

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Currently, methodologies for the identification and apportionment of air pollution sources are not widely applied due to their high cost. We present a new approach, combining mobile measurements from multiple sensors collected from the daily walks of citizen scientists, in a high population density area of Birmingham, UK. The methodology successfully pinpoints the different sources affecting the local air quality in the area using only a handful of measurements.

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