Article

Estimate of main local sources to ambient ultrafine particle number concentrations in an urban area

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Quantifying and apportioning the contribution of a range of sources to ultrafine particles (UFPs, D < 100 nm) is a challenge due to the complex nature of the urban environments. Although vehicular emissions have long been considered one of the major sources of ultrafine particles in urban areas, the contribution of other major urban sources is not yet fully understood. This paper aims to determine and quantify the contribution of local ground traffic, nucleated particle (NP) formation and distant non-traffic (e.g. airport, oil refineries, and seaport) sources to the total ambient particle number concentration (PNC) in a busy, inner-city area in Brisbane, Australia using Bayesian statistical modelling and other exploratory tools. The Bayesian model was trained on the PNC data on days where NP formations were known to have not occurred, hourly traffic counts, solar radiation data, and smooth daily trend. The model was applied to apportion and quantify the contribution of NP formations and local traffic and non-traffic sources to UFPs. The data analysis incorporated long-term measured time-series of total PNC (D≥ 6 nm), particle number size distributions (PSD, D =8 to 400 nm), PM2.5, PM10, NOx, CO, meteorological parameters and traffic counts at a stationary monitoring site. The developed Bayesian model showed reliable predictive performances in quantifying the contribution of NP formation events to UFPs (up to 4 × 104 particles cm−3), with a significant day to day variability. The model identified potential NP formation and no-formations days based on PNC data and quantified the sources contribution to UFPs. Exploratory statistical analyses show that total mean PNC during the middle of the day was up to 32% higher than during peak morning and evening traffic periods, which were associated with NP formation events. The majority of UFPs measured during the peak traffic and NP formation periods were between 30–100 nm and smaller than 30 nm, respectively. To date, this is the first application of Bayesian model to apportion different sources contribution to UFPs, and therefore the importance of this study is not only in its modelling outcomes but in demonstrating the applicability and advantages of this statistical approach to air pollution studies

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Ketersediaan

Informasi Detail

Judul Seri

Atmospheric Research

No. Panggil

ATC PO ANA e

Penerbit

Australia : Elsevier., 2017

Deskripsi Fisik

12 p.

Bahasa

English

ISBN/ISSN

0169-8095

Klasifikasi

PO

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

online resource

Edisi

-

Subjek

Ambient ultrafine particles
Bayesian statistical model
Non-traffic sources
Nucleated particle formation
Urban area

Info Detail Spesifik

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Pernyataan Tanggungjawab

Md Mahmudur Rahmana

Versi lain/terkait

Lampiran Berkas

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