# Critical factors influencing PM 10 and PM 2.5 pollution episodes and their associated particle chemical composition and mixing state in a coastal multisources area

A. Deguine, Andebo Abesha Waza, Soulemane Halif Ngagine, Pascal Flament, Patrick Augustin, Fabrice Cazier, Hervé Delbarre, Dorothée Dewaele, Elsa Dieudonné, Marc Fourmentin, et al.

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## ► To cite this version:

A. Deguine, Andebo Abesha Waza, Soulemane Halif Ngagine, Pascal Flament, Patrick Augustin, et al. Critical factors influencing PM 10 and PM 2.5 pollution episodes and their associated particle chemical composition and mixing state in a coastal multisources area. Workshop LEFE/CHAT on theoretical physical chemistry and atmospheric chemistry, Jul 2025, Marseille, France. hal-05170076

HAL Id: hal-05170076

https://hal.science/hal-05170076v1

Submitted on 18 Jul 2025

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Distributed under a Creative Commons Attribution 4.0 International License
## Context

Air pollution by particulate matter (PM) remains a major public health issue in Europe, particularly in coastal urban and industrial regions where multiple emission sources coexist. The Great Dunkirk Area (GDA), located on the northern French coast, is a densely industrialized zone influenced by traffic, shipping, industry, and marine air masses. Despite regulatory efforts, this region still experiences frequent pollution episodes involving PM₁₀ and PM₂.₅, with complex spatial and temporal behaviors.

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## Objectives

Understanding the **origin**, **chemical composition, and evolution** of airborne particles during pollution events to improve **air quality management** in multi-source coastal environments.

## Classification of pollution day and event

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## Chemical composition during PEs

## Occurrence of PDs and Pollution Event (PE) (2018-2021)

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<table><thead><tr><th rowspan="2">AQMS</th><th colspan="5">PM<sub>10</sub> PDs</th><th colspan="5">PM<sub>2.5</sub> PDs</th></tr><tr><th>2018</th><th>2019</th><th>2020</th><th>2021</th><th>Total</th><th>2018</th><th>2019</th><th>2020</th><th>2021</th><th>Total</th></tr></thead><tbody><tr><td>I</td><td>12</td><td>28</td><td>11</td><td>15</td><td>66</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td></tr><tr><td>U</td><td>14</td><td>19</td><td>7</td><td>3</td><td>43</td><td>90</td><td>74</td><td>61</td><td>61</td><td>286</td></tr><tr><td>S</td><td>14</td><td>13</td><td>20</td><td>3</td><td>50</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td></tr><tr><td>R</td><td>5</td><td>10</td><td>3</td><td>3</td><td>21</td><td>77</td><td>64</td><td>43</td><td>48</td><td>232</td></tr><tr><td>Total PDs</td><td>21</td><td>32</td><td>24</td><td>15</td><td>92</td><td>90</td><td>74</td><td>61</td><td>61</td><td>286</td></tr></tbody></table>

* 81% of PM₂.₅ pollution days (PDs) show regional plume extension, reaching the remote station (R) located at Campagnelès-Boulonnais, which is a rural station 67 km far from GDA.

* In contrast, only 23% of PM₁₀ PDs have regional extension, most are **local**, driven by nearby sources

* 72% of PM₁₀ PDs affected the **industrial station (I)**, indicating a strong influence of **industrial point and fugitive sources** (chimneys, shipping, storage)

* PM₂.₅ levels at the **remote station (R)** are similar to urban levels, showing **wide dispersion** and influence of **secondary aerosols** and **long-range transport**

* Extreme PM peaks reached ~95 µg/m³ (PM₁₀) and ~75 µg/m³ (PM₂.₅), representing episodic pollution events with health risks. These events are tied to atmospheric dynamics and source activities

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### Fine fraction (0.1–1 µm):

* Higher in **S-rich** particles (secondary origin; avg. ~15.5%)

* Higher in **carbonaceous** (avg. ~28.8%).

* Richer in **Ca-rich** particles (primary origin; avg. ~15.7%)

## Impact of dynamic conditions on mixing states during a PE

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### Synoptic and mesoscale meteorology critically shaped particle dispersion

* A high-pressure system led to stagnation on PE1-D1.

* A moving anticyclone from Iceland brought fresh air into the region on PE1-D2.

* This air mass change was accompanied by a low-level jet (LLJ) enhancing vertical mixing and reducing stability.

### Sea breeze effects modulated local stability

* On PE1-D1, a sea breeze developed mid-day, stabilizing the atmosphere and reducing vertical mixing.

* On PE1-D2, strong synoptic winds overrode these local effects, creating a more turbulent and unstable atmosphere.

* During the first part of the pollution event (PE1-S1 to S3) under **stagnant, local** conditions, aerosols are **more externally mixed** (lower χ values, ~ 0.5–0.6) due to multiple distinct emission sources

* In the second part (PE1-S4 to S7), as the plume becomes **regional and dispersive**, particles undergo **aging and mixing**, leading to higher χ values (~ 0.9) and **more internally mixed** aerosols

* Atmospheric aging during transport, especially under **recirculation or regional plume conditions**, increases the **internal mixing** of aerosols

## Conclusions

* PM₂.₅ pollution plumes are frequently regional in extent, while PM₁₀ plumes are more local

* A highly heterogeneous composition of particles is observed on pollution days.

* During pollution days, particle composition and mixing state evolve rapidly under the influence of small-scale meteorological dynamics

* Sea breezes and recirculation periods strongly impact pollutant dispersion and ageing in coastal area

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