BERmon32 Emission scenario model for regional air pollution
Niko Karvosenoja, 2008
Monographs of the Boreal Environment Research no. 32, p.55.URN:ISBN:978-952-11-3185-1, ISBN 978-952-11-3185-1 (PDF). The publication is available also in printed form ISBN 978-952-11-3184-4.
Air pollution emissions are produced in a wide variety of sources. They often result in detrimental impacts on both environments and human populations. To assess the emissions and impacts of air pollution, mathematical models have been developed. This study presents results from the application of an air pollution emission model, the Finnish Regional Emission Scenario (FRES) model, that covers the emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3), non-methane volatile organic compounds (NMVOCs) and primary particulate matter (TSP, PM10, PM2.5 and PM1) in high 1 ´ 1 km2 spatial resolution over the area of Finland. The aims of the study were to identify key emission sources in Finland at present and in the future, to assess the effects of climate policies on air pollution, and to estimate emission reduction potentials and costs. Uncertainties in emission estimates were analyzed. Finally, emission model characteristics for use in different air pollution impact applications were discussed.
The main emission sources in Finland are large industrial and energy production plants for SO2 (64% of 76 Gg a-1 total in the year 2000). Traffic vehicles are the main contributors for NOx (58% of 206 Gg a-1), NMVOCs (54% of 152 Gg a-1) and primary PM2.5 (26% of 31 Gg a-1) emissions. Agriculture is the key source for NH3 (97% of 33 Gg a-1). Other important sources are domestic wood combustion for primary PM2.5 (25%) and NMVOCs (12%), and fugitive dust emissions from traffic and other activities for primary PM10 (30% of 46 Gg a-1).
In the future, the emissions of traffic vehicle exhaust will decrease considerably, by 76% (NMVOCs), 74% (primary PM2.5) and 60% (NOx), from 2000 to 2020, because of tightening emission legislations. Rather smaller decrease is anticipated in the emissions of large combustion plants, depending on future primary energy choices. Sources that are not subject to tight emission standards, e.g. domestic combustion and traffic-induced fugitive dust (i.e. non-exhaust), pose a risk for increasing emissions.
The majority of measures to abate climate change, e.g. energy saving and non-combustion based energy production, lead to co-benefits as reduced air pollution emissions, especially of SO2 (20% to 28% reduction). However, promotion of domestic wood combustion poses a risk for increase in PM2.5 and NMVOCs emissions. Further emission reductions with feasible control costs are possible mainly for PM2.5 in small energy production plants and domestic combustion sources. Highest emission uncertainties were estimated for primary PM emission factors of domestic wood combustion, traffic non-exhaust sources and small energy production plants.
The most important characteristics of emission models are correct location information of flue gas stacks of large plants for the assessment of acidification, and description of small polluters with high spatial resolution when assessing impacts on populations. Especially primary PM2.5 emissions originate to a considerable degree from small low-altitude sources in urban areas, and therefore it is important to be able to assess the impacts that take place near the emission sources. Detailed descriptions of large plants and 1 ´ 1 km2 spatial resolution for small emission sources applied in the FRES model enable its use in the assessment of various national environmental impacts and their reduction possibilities.
The main contribution of this work was the development of a unique modeling framework to assess emission scenarios of multiple air pollutants in high sectoral and spatial resolution in Finland. The developed FRES model provides support for Finnish air pollution polices and a tool to assess the co-benefits and trade-offs of climate change strategies on air pollution.
Niko Karvosenoja, Finnish Environment Institute (SYKE), email@example.com