Characterizing temporal and spatial patterns of urban PM10 using six years of Finnish monitoring data

Data from the Finnish Meteorological Institute's Air Quality Monitoring Data Management System (ILSE) for 1998–2003 were used to examine the temporal and spatial patterns of urban PM10 in Finland. Long term means of PM10 at 24 Finnish urban stations vary between 11 and 24 ug m–3. The seasonal variation of PM10 at all stations was dominated by the spring maximum. A strong influence of traffic on the urban PM10 concentrations is shown. However the highly synchronized day-to-day variation at a variety of sites across the country highlights the role of large scale weather patterns also in the formation of spring episodes. Every year, most often in August, September and October, there were also 1–5 irregular regional PM10 episodes, lasting from one day to six days and most likely caused by long-range transported particles. During these regional events, the PM10 concentrations may well reach the typical spring peak concentration levels.

Authors

Publication Details

Journal
Boreal Environment Research Journal Archive
Published
2024-12-12
DOI
https://doi.org/10.60910/3caj-0g47
Citations
11
Primary Topic
Air Quality and Health Impacts
Type
article
Field-Weighted Citation Impact
0.31
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article

Characterizing temporal and spatial patterns of urban PM10 using six years of Finnish monitoring data

Pia Anttila, Timo Salmi
11 citations
Boreal Environment Research Journal Archive
Air Quality and Health Impacts
0.31
article

Characterizing temporal and spatial patterns of urban PM10 using six years of Finnish monitoring data

Pia Anttila, Timo Salmi
article en
11 citations

Abstract

Data from the Finnish Meteorological Institute's Air Quality Monitoring Data Management System (ILSE) for 1998–2003 were used to examine the temporal and spatial patterns of urban PM10 in Finland. Long term means of PM10 at 24 Finnish urban stations vary between 11 and 24 ug m–3. The seasonal variation of PM10 at all stations was dominated by the spring maximum. A strong influence of traffic on the urban PM10 concentrations is shown. However the highly synchronized day-to-day variation at a variety of sites across the country highlights the role of large scale weather patterns also in the formation of spring episodes. Every year, most often in August, September and October, there were also 1–5 irregular regional PM10 episodes, lasting from one day to six days and most likely caused by long-range transported particles. During these regional events, the PM10 concentrations may well reach the typical spring peak concentration levels.

Boreal Environment Research Journal Archive
Openalex Percentile: Top 43%
Air Quality and Health Impacts
0.31
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