This study assesses population exposure caused by the emissions of primary fine particulate matter (PM 2.5 ) originated from road traffic and domestic wood combustion in Finland in 2000 and 2020. The evaluations were performed using source-receptor matrices (SRMs) based on the computations using a local and a regional scale atmospheric dispersion model, on two different grid resolutions: 1 and 10 km. Road traffic and domestic wood combustion are nationally the most important emission source categories of primary PM 2.5 ; they were projected to contribute to 42% of the Finnish total emissions in 2020. Although traffic exhaust emissions were projected to decrease considerably in the future, by 91% from 2000 to 2020, non-exhaust emissions were predicted to increase. Traffic emissions were found to cause on the average considerably higher population-weighted concentration (PWC) to primary PM 2.5 , compared with domestic wood combustion emissions. Based on the computation with 1-km resolution SRMs, the exhaust and non-exhaust traffic emissions were projected to cause 5.5% and 62% of the PWC, respectively, of the total combined PWC caused by traffic and domestic combustion in Finland in 2020. Regarding the sub-categories of domestic wood combustion, supplementary wood heating was found to cause relatively high PWC, 22% in 2020. The modeling of traffic emissions and dispersion using the regional scale model on a resolution of 10 km resulted in PWC that is more than an order of magnitude smaller, compared with the corresponding computations using a local scale model on a resolution of 1 km. The general implication of this study is that the PWC values evaluated using integrated assessment models can be sensitive to the methodology, especially these can substantially increase with an increasing spatial resolution.
Abstract. Residential wood combustion (RWC) is an important contributor to
air quality in numerous regions worldwide. This study is the first extensive
evaluation of the influence of RWC on ambient air quality in several Nordic
cities. We have analysed the emissions and concentrations of PM2.5 in
cities within four Nordic countries: in the metropolitan areas of
Copenhagen, Oslo, and Helsinki and in the city of Umeå. We have
evaluated the emissions for the relevant urban source categories and
modelled atmospheric dispersion on regional and urban scales. The emission
inventories for RWC were based on local surveys, the amount of wood
combusted, combustion technologies and other relevant factors. The accuracy
of the predicted concentrations was evaluated based on urban concentration
measurements. The predicted annual average concentrations ranged spatially
from 4 to 7 µg m−3 (2011), from 6 to 10 µg m−3 (2013), from 4 to more than 13 µg m−3 (2013) and from 9 to more
than 13 µg m−3 (2014), in Umeå, Helsinki, Oslo and
Copenhagen, respectively. The higher concentrations in Copenhagen were
mainly caused by the relatively high regionally and continentally
transported background contributions. The annual average fractions of
PM2.5 concentrations attributed to RWC within the considered urban
regions ranged spatially from 0 % to 15 %, from 0 % to 20 %, from 8 % to 22 % and from 0 % to 60 % in Helsinki, Copenhagen, Umeå and Oslo,
respectively. In particular, the contributions of RWC in central Oslo were
larger than 40 % as annual averages. In Oslo, wood combustion was used
mainly for the heating of larger blocks of flats. In contrast, in
Helsinki, RWC was solely used in smaller detached houses. In Copenhagen and
Helsinki, the highest fractions occurred outside the city centre in the
suburban areas. In Umeå, the highest fractions occurred both in the city
centre and its surroundings.
Health effect estimates depend on the methods of evaluating exposures. Due to non-linearities in the exposure-response relationships, both the predicted mean exposures as well as its spatial variability are significant. The aim of this work is to systematically quantify the impact of the spatial resolution on population-weighted mean concentration (PWC), its variance, and mortality attributable to fine particulate matter (PM 2.5) exposure in Finland in 2015. The atmospheric chemical transport model SILAM was used to estimate the ambient air PM 2.5 concentrations at 0.02°longitudinal × 0.01°latitudinal resolution (ca. 1 km), including both the national PM 2.5 emissions and the long-range transport. The decision-support model FRES source-receptor matrices applied at 250-m resolution was used to model the ambient air concentrations of primary fine particulate matter (PPM 2.5) from local and regional sources up to 10 km and 20 km distances. Numerical averaging of population and concentrations was used to produce the results for coarser resolutions. Population-weighted PM 2.5 concentration was 11% lower at a resolution of 50 km, compared with the corresponding computations at a resolution of 1 km. However, considering only the national emissions, the influences of spatial averaging were substantially larger. The average population-weighted local PPM 2.5 concentration originated from Finnish sources was 70% lower at a resolution of 50 km, compared with the corresponding result obtained using a resolution of 250 m. The sensitivity to spatial averaging, between the finest 250-m and the coarsest 50-km resolution, was highest for the emissions of PPM 2.5 originated from national vehicular traffic (about 80% decrease) and lowest for Electronic supplementary material The online version of this article (
Air pollution has been estimated to be one of the leading environmental health risks in Finland. National health impact estimates existing to date have focused on particles (PM) and ozone (O3). In this work, we quantify the impacts of particles, ozone, and nitrogen dioxide (NO2) in 2015, and analyze the related uncertainties. The exposures were estimated with a high spatial resolution chemical transport model, and adjusted to observed concentrations. We calculated the health impacts according to Word Health Organization (WHO) working group recommendations. According to our results, ambient air pollution caused a burden of 34,800 disability-adjusted life years (DALY). Fine particles were the main contributor (74%) to the disease burden, which is in line with the earlier studies. The attributable burden was dominated by mortality (32,900 years of life lost (YLL); 95%). Impacts differed between population age groups. The burden was clearly higher in the adult population over 30 years (98%), due to the dominant role of mortality impacts. Uncertainties due to the concentration–response functions were larger than those related to exposures.
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