Major air pollutants seasonal variation analysis and long-range transport of PM10 in an urban environment with specific climate condition in Transylvania (Romania)
The air quality decrease, especially in urban areas, is related to local-scale conditions and to dispersion of air pollutants (regional and long-range) as well. The main objective of this study was to decipher the seasonal variation of PM 10 , NO, NO 2 , NO x , SO 2 , O 3 , and CO over a 1-year peri...
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| Veröffentlicht in: | Environmental science and pollution research international 2020-10, Vol.27 (30), p.38181-38199 |
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| creator | Bodor, Zsolt Bodor, Katalin Keresztesi, Ágnes Szép, Róbert |
| description | The air quality decrease, especially in urban areas, is related to local-scale conditions and to dispersion of air pollutants (regional and long-range) as well. The main objective of this study was to decipher the seasonal variation of PM
10
, NO, NO
2
, NO
x
, SO
2
, O
3
, and CO over a 1-year period (2017) and the possible relationships between air pollution and meteorological variables. Furthermore, trajectory cluster analysis and concentration-weighted trajectory (CWT) methods were used to assess the trajectories and the source-receptor relationship of PM
10
in the Ciuc basin Transylvania, known as the “Cold Pole” of Romania. The pollutants show lower concentrations during warmer periods, especially during summer, and significantly higher concentrations were observed on heating season in winter due to seasonal variations in energy use (biomass burning) and atmospheric stability. Subsequently, in February, the highest concentration of PM
10
was 132 μg/m
3
, which is 4 times higher than the highest recorded monthly mean. Our results indicate a negative correlation between CO/temperature (− 0.89), NO
x
/temperature (− 0.84) and positive between NO
x
/PM
10
(0.95), CO/PM
10
(0.9), and NO
x
/CO (0.98), respectively. Dominant transport pathways were identified and the results revealed that slow-moving southerly (~ 45%) and northwesterly (~ 32%) air masses represent almost 80% and mainly regional flows were discerned. During 2017, increased PM
10
levels were measured at the study site when air masses arrived mostly from northwest and southeast. The CWT and polarplot models show a strong seasonal variation and significant differences were observed between weekdays and weekends, namely highest PM
10
concentrations during weekends at low wind speed (2–4 m/s). |
| doi_str_mv | 10.1007/s11356-020-09838-2 |
| format | Article |
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10
, NO, NO
2
, NO
x
, SO
2
, O
3
, and CO over a 1-year period (2017) and the possible relationships between air pollution and meteorological variables. Furthermore, trajectory cluster analysis and concentration-weighted trajectory (CWT) methods were used to assess the trajectories and the source-receptor relationship of PM
10
in the Ciuc basin Transylvania, known as the “Cold Pole” of Romania. The pollutants show lower concentrations during warmer periods, especially during summer, and significantly higher concentrations were observed on heating season in winter due to seasonal variations in energy use (biomass burning) and atmospheric stability. Subsequently, in February, the highest concentration of PM
10
was 132 μg/m
3
, which is 4 times higher than the highest recorded monthly mean. Our results indicate a negative correlation between CO/temperature (− 0.89), NO
x
/temperature (− 0.84) and positive between NO
x
/PM
10
(0.95), CO/PM
10
(0.9), and NO
x
/CO (0.98), respectively. Dominant transport pathways were identified and the results revealed that slow-moving southerly (~ 45%) and northwesterly (~ 32%) air masses represent almost 80% and mainly regional flows were discerned. During 2017, increased PM
10
levels were measured at the study site when air masses arrived mostly from northwest and southeast. The CWT and polarplot models show a strong seasonal variation and significant differences were observed between weekdays and weekends, namely highest PM
10
concentrations during weekends at low wind speed (2–4 m/s).</description><identifier>ISSN: 0944-1344</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-020-09838-2</identifier><identifier>PMID: 32617823</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Air masses ; Air pollution ; Air quality ; Aquatic Pollution ; Atmospheric models ; Atmospheric Protection/Air Quality Control/Air Pollution ; Biomass burning ; Biomass energy production ; Burning ; Carbon monoxide ; Climatic conditions ; Cluster analysis ; Earth and Environmental Science ; Ecotoxicology ; Energy consumption ; Environment ; Environmental Chemistry ; Environmental Health ; Environmental science ; Nitrogen dioxide ; Outdoor air quality ; Particulate matter ; Pollutants ; Pollution dispersion ; Research Article ; Seasonal variations ; Sulfur dioxide ; Trajectory analysis ; Urban areas ; Urban environments ; Waste Water Technology ; Water Management ; Water Pollution Control ; Wind speed</subject><ispartof>Environmental science and pollution research international, 2020-10, Vol.27 (30), p.38181-38199</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c509t-a36432510bfa80e0b3332933fc0c4064fd2c2cf9cb5978f893946e47432f1c4c3</citedby><cites>FETCH-LOGICAL-c509t-a36432510bfa80e0b3332933fc0c4064fd2c2cf9cb5978f893946e47432f1c4c3</cites><orcidid>0000-0003-1386-6957</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11356-020-09838-2$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11356-020-09838-2$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,778,782,883,27911,27912,41475,42544,51306</link.rule.ids></links><search><creatorcontrib>Bodor, Zsolt</creatorcontrib><creatorcontrib>Bodor, Katalin</creatorcontrib><creatorcontrib>Keresztesi, Ágnes</creatorcontrib><creatorcontrib>Szép, Róbert</creatorcontrib><title>Major air pollutants seasonal variation analysis and long-range transport of PM10 in an urban environment with specific climate condition in Transylvania (Romania)</title><title>Environmental science and pollution research international</title><addtitle>Environ Sci Pollut Res</addtitle><description>The air quality decrease, especially in urban areas, is related to local-scale conditions and to dispersion of air pollutants (regional and long-range) as well. The main objective of this study was to decipher the seasonal variation of PM
10
, NO, NO
2
, NO
x
, SO
2
, O
3
, and CO over a 1-year period (2017) and the possible relationships between air pollution and meteorological variables. Furthermore, trajectory cluster analysis and concentration-weighted trajectory (CWT) methods were used to assess the trajectories and the source-receptor relationship of PM
10
in the Ciuc basin Transylvania, known as the “Cold Pole” of Romania. The pollutants show lower concentrations during warmer periods, especially during summer, and significantly higher concentrations were observed on heating season in winter due to seasonal variations in energy use (biomass burning) and atmospheric stability. Subsequently, in February, the highest concentration of PM
10
was 132 μg/m
3
, which is 4 times higher than the highest recorded monthly mean. Our results indicate a negative correlation between CO/temperature (− 0.89), NO
x
/temperature (− 0.84) and positive between NO
x
/PM
10
(0.95), CO/PM
10
(0.9), and NO
x
/CO (0.98), respectively. Dominant transport pathways were identified and the results revealed that slow-moving southerly (~ 45%) and northwesterly (~ 32%) air masses represent almost 80% and mainly regional flows were discerned. During 2017, increased PM
10
levels were measured at the study site when air masses arrived mostly from northwest and southeast. The CWT and polarplot models show a strong seasonal variation and significant differences were observed between weekdays and weekends, namely highest PM
10
concentrations during weekends at low wind speed (2–4 m/s).</description><subject>Air masses</subject><subject>Air pollution</subject><subject>Air quality</subject><subject>Aquatic Pollution</subject><subject>Atmospheric models</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Biomass burning</subject><subject>Biomass energy production</subject><subject>Burning</subject><subject>Carbon monoxide</subject><subject>Climatic conditions</subject><subject>Cluster analysis</subject><subject>Earth and Environmental Science</subject><subject>Ecotoxicology</subject><subject>Energy consumption</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Environmental science</subject><subject>Nitrogen dioxide</subject><subject>Outdoor air quality</subject><subject>Particulate matter</subject><subject>Pollutants</subject><subject>Pollution dispersion</subject><subject>Research 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Pollut Res</stitle><date>2020-10-01</date><risdate>2020</risdate><volume>27</volume><issue>30</issue><spage>38181</spage><epage>38199</epage><pages>38181-38199</pages><issn>0944-1344</issn><eissn>1614-7499</eissn><abstract>The air quality decrease, especially in urban areas, is related to local-scale conditions and to dispersion of air pollutants (regional and long-range) as well. The main objective of this study was to decipher the seasonal variation of PM
10
, NO, NO
2
, NO
x
, SO
2
, O
3
, and CO over a 1-year period (2017) and the possible relationships between air pollution and meteorological variables. Furthermore, trajectory cluster analysis and concentration-weighted trajectory (CWT) methods were used to assess the trajectories and the source-receptor relationship of PM
10
in the Ciuc basin Transylvania, known as the “Cold Pole” of Romania. The pollutants show lower concentrations during warmer periods, especially during summer, and significantly higher concentrations were observed on heating season in winter due to seasonal variations in energy use (biomass burning) and atmospheric stability. Subsequently, in February, the highest concentration of PM
10
was 132 μg/m
3
, which is 4 times higher than the highest recorded monthly mean. Our results indicate a negative correlation between CO/temperature (− 0.89), NO
x
/temperature (− 0.84) and positive between NO
x
/PM
10
(0.95), CO/PM
10
(0.9), and NO
x
/CO (0.98), respectively. Dominant transport pathways were identified and the results revealed that slow-moving southerly (~ 45%) and northwesterly (~ 32%) air masses represent almost 80% and mainly regional flows were discerned. During 2017, increased PM
10
levels were measured at the study site when air masses arrived mostly from northwest and southeast. The CWT and polarplot models show a strong seasonal variation and significant differences were observed between weekdays and weekends, namely highest PM
10
concentrations during weekends at low wind speed (2–4 m/s).</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>32617823</pmid><doi>10.1007/s11356-020-09838-2</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0003-1386-6957</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Environmental science and pollution research international, 2020-10, Vol.27 (30), p.38181-38199 |
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| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7496053 |
| source | Springer Nature - Complete Springer Journals |
| subjects | Air masses Air pollution Air quality Aquatic Pollution Atmospheric models Atmospheric Protection/Air Quality Control/Air Pollution Biomass burning Biomass energy production Burning Carbon monoxide Climatic conditions Cluster analysis Earth and Environmental Science Ecotoxicology Energy consumption Environment Environmental Chemistry Environmental Health Environmental science Nitrogen dioxide Outdoor air quality Particulate matter Pollutants Pollution dispersion Research Article Seasonal variations Sulfur dioxide Trajectory analysis Urban areas Urban environments Waste Water Technology Water Management Water Pollution Control Wind speed |
| title | Major air pollutants seasonal variation analysis and long-range transport of PM10 in an urban environment with specific climate condition in Transylvania (Romania) |
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