Impact of the open biomass fires in spring and summer of 2006 on the chemical composition of background air in south-eastern Finland

Anttila, Pia; Makkonen, Ulla; Hellén, Heidi; Kyllönen, Katriina; Leppänen, Sirkka; Saari, Helena; Hakola, Hannele

doi:10.1016/j.atmosenv.2008.04.020

Cited by 41 publications

(25 citation statements)

References 33 publications

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“…It is conceivable that the observations were strongly influenced by ozone precursor emissions associated with the 2006 heat-wave which are not adequately represented in the emission inventories employed in the standard model configurations. Air quality during much of the spring and summer of 2006 was influenced by wild-fires in the Russian Federation (Saarikoski et al, 2007;Witham and Manning, 2007;Anttila et al, 2008;Niemi et al, 2009) and it is possible that this influence specifically impacted upon the observed ozone levels at the Harwell station during July 18 th and 19 th .…”

Section: • Photochemical Trajectory Model (Ptm)mentioning

confidence: 99%

Analysis of UK and European NOx and VOC emission scenarios in the Defra model intercomparison exercise

Derwent¹,

Beevers

Chemel

et al. 2014

Atmospheric Environment

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Highlights• Emission scenarios were implemented in eight ozone air quality models• NOx-and VOC sensitivities for peak ozone levels were highly variable between days• Filtering by model performance minimised apparent conflicts between models KeywordsAir quality modelling, model intercomparison, episodic peak ozone levels, emission sensitivities, NO x and VOC emissions 2 ABSTRACTSimple emission scenarios have been implemented in eight United Kingdom air quality models with the aim of assessing how these models compared when addressing whether photochemical ozone formation in southern England was NO x -or VOC-sensitive and whether ozone precursor sources in the UK or in the Rest of Europe (RoE) were the most important during July 2006. The suite of models included three Eulerian-grid models (three implementations of one of these models), a Lagrangian atmospheric dispersion model and two moving box air parcel models. The assignments as to NO x -or VOC-sensitive and to UK-versus RoE-dominant, turned out to be highly variable and often contradictory between the individual models. However, when the assignments were filtered by model performance on each day, many of the contradictions could be eliminated. Nevertheless, no one model was found to be the 'best' model on all days, indicating that no single air quality model could currently be relied upon to inform policymakers robustly in terms of NO x -versus VOCsensitivity and UK-versus RoE-dominance on each day. It is important to maintain a diversity in model approaches.

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Section: • Photochemical Trajectory Model (Ptm)mentioning

confidence: 99%

Analysis of UK and European NOx and VOC emission scenarios in the Defra model intercomparison exercise

Derwent¹,

Beevers

Chemel

et al. 2014

Atmospheric Environment

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“…and Virolahti EMEP station (Anttila et al, 2008), located in the south-eastern corner of Finland, with the Russian border 6 km to the east and E18 highway 5 km to the north.…”

Section: Hyytiälä Smear II (Station For Measuring Forestmentioning

confidence: 99%

Black carbon concentration and deposition estimations in Finland by the regional aerosol–climate model REMO-HAM

et al. 2013

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The prediction skill of the regional aerosol–climate model REMO-HAM was assessed against the black carbon (BC) concentration measurements from five locations in Finland, with focus on Hyytiälä station for the year 2005. We examined to what extent the model is able to reproduce the measurements using several statistical tools: median comparison, overlap coefficient (OVL; the common area under two probability distributions curves) and Z score (a measure of standard deviation, shape and spread of the distributions). The results of the statistics showed that the model is biased low. The local and regional emissions of BC have a significant contribution, and the model tendency to flatten the observed BC is most likely dominated by the lack of domestic burning of biofuel in the emission inventories. A further examination of the precipitation data from both measurements and model showed that there is no correlation between REMO's excessive precipitation and BC underestimation. This suggests that the excessive wet removal is not the main cause of the low black carbon concentration output. In addition, a comparison of wind directions in relation with high black carbon concentrations shows that REMO-HAM is able to predict the BC source directions relatively well. Cumulative black carbon deposition fluxes over Finland were estimated, including the deposition on snow

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“…Forest fires have been observed to enhance the release of mercury (Friedli et al, 2003;Sigler et al, 2003;Cinnirella and Pirrone, 2006). This effect has also been observed at the Finnish station Virolahti (Anttila et al, 2008;Paatero et al, 2009), which is located close to north-west Russia, areas where extensive forest fires have occurred during recent years. TGM concentrations peaked during the forest fire period in August 2006 (see Figure 19).…”

Section: Figure 18 Number Of Days With Very High Forest Fire Risk Prmentioning

confidence: 65%

Atmospheric and catchment mercury concentrations and fluxes in Fennoscandia

Wängberg¹,

Pfaffhuber²,

Berg³

et al. 2010

TemaNord

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Impact of the open biomass fires in spring and summer of 2006 on the chemical composition of background air in south-eastern Finland

Cited by 41 publications

References 33 publications

Analysis of UK and European NOx and VOC emission scenarios in the Defra model intercomparison exercise

Analysis of UK and European NOx and VOC emission scenarios in the Defra model intercomparison exercise

Black carbon concentration and deposition estimations in Finland by the regional aerosol–climate model REMO-HAM

Atmospheric and catchment mercury concentrations and fluxes in Fennoscandia

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