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General

Meta data ID	{86E010B9-29E6-4149-914F-A4E605971E60}
Last modified	2020-03-16T16:20:46

Dataset creators

Contact person

First name	Niko
Last name	Karvosenoja
Email	niko.karvosenoja@syke.fi
Organisation	Finnish Environment Institute

Dataset creators

First name	Ville-Veikko
Last name	Paunu
Organisation	Finnish Environment Institute

Dataset creators

First name	Niko
Last name	Karvosenoja
Organisation	Finnish Environment Institute

Dataset creators

First name	Mikko
Last name	Savolahti
Organisation	Finnish Environment Institute

Description

Basic information

Dataset title	Finnish air pollution emission scenarios
Theme	Environment and Conservation
Description	The dataset contains anthropogenic air pollution and greenhouse gas emissions from Finland for 2015 and 2030. The emissions are calculated with the Finnish Regional Emission Scenario (FRES) model developed at the Finnish Environment Institute. The pollutants included are PM10, PM2.5, PM1, BC, OC, NOx, SO2, CO, VOC, NH3, BaP, CO2, CO2bio, CH4 and N2O. CO2bio refers to biogenic CO2 emissions, e.g. wood combustion. The emissions are given separately for point sources on municipal level and area sources on 250 m x 250 m resolution. The point source emissions indicate the emissions from major energy production and industrial plants. They are calculated based on several year average emissions and are not the officially reported emissions. The area sources are aggregated to 8 sectors: traffic exhaust, traffic dust, machinery and off-road, small scale wood combustion, other small scale combustion, agriculture, peat production, and other area sources.
Language (dataset)	English
Keyword	air pollution, emission, particles, PM, black carbon

Data processing steps

Data processing steps	processing
Description	The emissions are calculated using the FRES-model. All annual emission estimates are calculated as a product of activity data (fuel use/mileage/land area etc.) and emission factors for a given pollutant or greenhouse gas. Some sources also include technologies for emission reduction. Historical and projected emissions are estimated in five-year intervals. The latest year for historical emissions is currently 2015. Point sources: Point sources are combustion/industrial plants with notable annual emissions. FRES model currently includes 400+ point sources. A combination of bottom-up and top-down approaches are used to calculate emissions from point sources. The locations of point sources are known, as well as some other data, such as capacity. Plant-specific emission factors are used for some important point sources and representative averages for others. Activity data like fuel use in each plant is not year-specific but represent the annual average in a given plant. Thus, the modelled and reported emissions from an individual plant are usually not quite congruent. However, total fuel use for a group of similar plants, like coal-fired power plants, is the same as reported that year. For most process industry sites emissions are not modelled, but the reported emissions are used. Area sources: Area sources are smaller sources of emissions, for which annual emissions are not reported by the actors. The most important area sources are traffic and mobile machinery, residential combustion and agriculture. A top-down approach is used to calculate emissions from area sources. Activity data: Fuel combustion is the most common activity that produces emissions. Annual consumption of fuels in a given sector is taken from Energy table service by Statistics Finland (https://pxhopea2.stat.fi/sahkoiset_julkaisut/energia2018/start.htm). Other activities, such as mileage, animal numbers and various land use areas are also from Statistics Finland Emission factors: Emission factors of greenhouse gases from combustion sources are fuel-specific. Emission factors of air pollutants are based on various sources like literature, legislative emission levels, measurements and data reported by industrial operators. For traffic and mobile machinery, emission factors are taken from the international GAINS model, in which they are based on COPERT 4 emission calculation tool. For residential wood combustion, emission factors are mostly from measurements made in domestic campaigns. For point sources, emission factors are based on plant-specific technology, representative emission control legislation or reported emissions. Scenarios and emission projections: The FRES model is mostly a tool for integrated assessment of future emission scenarios. Scenarios are based on projections of activity data, foreseeable or agreed changes in legislation and political measures that influence emissions. Current 2030 projection is mostly based on the activities in the WAM scenario of the National Energy and Climate Strategy, published in 2017. It includes legislation that is agreed to enter into force by 2030, such as stricter emission levels for combustion plants and the Ecodesing directive that sets maximum levels for particulate emissions from most residential wood combustion appliances. The emission projection is explained in more detail in the National Air Pollution Control Programme 2030. References: Description of the FRES model: Karvosenoja N. 2008. Emission scenario model for regional air pollution. Monographs of the Boreal Environment Research 32. Emissions from residential wood combustion: Savolahti, M., Karvosenoja, N., Tissari, J., Kupiainen, K., Sippula, O. & Jokiniemi, J. (2016). Black carbon and fine particle emissions in Finnish residential wood combustion: Emission projections, reduction measures and the impact of combustion practices. Atmospheric Environment. 140. 10.1016/j.atmosenv.2016.06.023. National Air Pollution Control Programme 2030: Ministry of the Environment. National Air Pollution Control Programme 2030; Publications of the Ministry of Environment: Suomi, Finland, 2019. https://julkaisut.valtioneuvosto.fi/handle/10024/161467
Additional information (URL)	http://www.syke.fi/projects/fres

Data processing steps

processing

Description

Spatial distribution of the area source emissions are based on several proxies. The main data sources for the proxies are Digiroad for roads and traffic volumes, The National Buildings and Dwellings Register for buildings data, and CORINE2012 for land use data. More information on the proxies can be found in the references below. Paunu V.-V., Karvosenoja N., Savolahti M., Kupiainen K. 2013. High quality spatial model for residential wood combustion emissions. 16th IUAPPA World Clean Air Congress, Cape Town, South Africa, 29 September - 4 October 2013. 4 pp. 11 Karvosenoja N., et al. 2018. A high-resolution national emission inventory and dispersion modelling – Is population density a sufficient proxy variable? 36th International Technical Meetings (ITM) on Air Pollution Modelling and its Application, Ottawa, Canada, 14.05.2018 - 18.05.2018.

Material time period

Start date	2015
End date	2030

Area

West Bounding Longitude	19
East Bounding Longitude	32
South Bounding Latitude	59.5
North Bounding Latitude	70.2

Distribution

Contact person

First name	Niko
Last name	Karvosenoja
Email	niko.karvosenoja@syke.fi
Organisation	Finnish Environment Institute

Resources

Resource content description	ArcGIS Online viewer for the emission data
Web-address (URL)	https://www.syke.fi/emissionmap

Resources

Resource content description	ArcGIS Online viewer for the emission data
Web-address (URL)	https://www.syke.fi/emissionmap

Reference publications

Reference

Karvosenoja N. 2008. Emission scenario model for regional air pollution. Monographs of the Boreal Environment Research 32 https://helda.helsinki.fi/handle/10138/39332?locale-attribute=en

The license for open SYKE's open datasets is Creative Commons Attribution 4.0 International.

The data described here can be freely used to all purposes, provided that the source of the data is mentioned.

The citation for the dataset as given above.

Further information on the license:
https://creativecommons.org/licenses/by/4.0/legalcode (English)
https://creativecommons.org/licenses/by/4.0/legalcode.fi (Finnish)

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