| Title: | Characterization of PM10 sources in a pre-alpine valley with traffic, biomass burning and industrial sources |
|---|
| Authors: | ID Glojek, Kristina (Author)
ID Dinh Ngoc, Thuy Vy (Author)
ID Manousakas, Manousos Ioannis (Author)
ID Jaffrezo, Jean-Luc (Author)
ID Prevot, Andre S. H. (Author)
ID Močnik, Griša (Author) |
|---|
| Files: |  https://btf.unbi.ba/wp-content/uploads/2024/06/THE-BOOK-OF-ABSTRACTS-2024.pdf
|
|---|
| Language: | English |
|---|
| Work type: | Unknown |
|---|
| Typology: | 1.12 - Published Scientific Conference Contribution Abstract |
|---|
| Organization: | UNG - University of Nova Gorica
|
|---|
| Abstract: | The contribution of traffic and wood burning to particulate matter (PM) across the Alps is widely recognized and studied (Herich et al., 2014 and references therein; Glojek et al., 2021). However, studies on valleys with cement production are scarce despite its large PM emissions and potential toxic properties (Kim et al., 2003; Rovira et al., 2018; Ervik et al., 2022; Weinbruch et al., 2023). In this study, we aim to identify and chemically characterize PM10 sources in a pre-alpine valley influenced by cement industry. A comprehensive SA study on the local and regional PM sources and their size-segregated elemental fraction will be presented.
PM10 was sampled daily on quartz filters from November 2020 to November 2021 and analyzed for a large array of chemical species. Equivalent black carbon (eBC) measurements were taken with the Aethalometer AE33. Hourly elemental PM10 and PM2.5 composition was measured in parallel with two Xact 625i from February until May 2021. Positive Matrix Factorization (PMF) was used to determine the sources of PM10 (off-line PMF) with 24-hour time resolution, and of the elemental fraction of PM (on-line PMF) with 1-hour time resolution for the overlapping time period.
A combination of the different PMF models with various instrument data resulted in improved SA in terms of number of identifies sources and their uncertainties. The off-line PMF resolved ten PM10 sources (Fig. 1, left), while the on-line elemental PM10 and the combined elemental PM2.5+coarse PMF recognized 6 and 7 factors, respectively (Fig. 1, right).
Due to large number of samples, we were able to separate between the sources with strong seasonality and sources featuring stability throughout the year. The study disclosed two rarely encountered factors, i.e., chloride-rich (chlorine-rich in case of on-line PMF) and cement dust. We associate these two factors to different processes in the cement plant. The high-resolution on-line PMF enabled us to distinguish between regional and local sources. Furthermore, the size-segregated on-line PMF provided more speciated sources (traffic separation into heavy-duty and light-duty vehicles).
The outputs of the study provide vital information about the influence of cement production on PM10 concentrations and OP in complex environments and are useful for PM control strategies and actions. Further work involves more detailed comparison of offline and online PMF factors and additional sampling and analysis of the samples around the cement industry. |
|---|
| Keywords: | positive matrix factorization, PM10 composition, metals, Xact, HVS digitel |
|---|
| Publication status: | Published |
|---|
| Publication version: | Version of Record |
|---|
| Publication date: | 01.01.2024 |
|---|
| Year of publishing: | 2024 |
|---|
| Number of pages: | str. 28-29 |
|---|
| Numbering: | God. 7, br. 7 |
|---|
| PID: | 20.500.12556/RUNG-9805  |
|---|
| COBISS.SI-ID: | 223801603 |
|---|
| UDC: | 504.5 |
|---|
| ISSN on article: | 2303-5889 |
|---|
| NUK URN: | URN:SI:UNG:REP:BEBV9PNX |
|---|
| Publication date in RUNG: | 24.01.2025 |
|---|
| Views: | 287 |
|---|
| Downloads: | 1 |
|---|
| Metadata: |    |
|---|
|
:
|
Copy citation |
|---|
| | | | Average score: | (0 votes) |
|---|
| Your score: | Voting is allowed only for logged in users. |
|---|
| Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
