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首页> 外文期刊>Air quality, atmosphere & health >Integrated modeling assessments of the population exposure in Finland to primary PM2.5 from traffic and domestic wood combustion on the resolutions of 1 and 10 km
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Integrated modeling assessments of the population exposure in Finland to primary PM2.5 from traffic and domestic wood combustion on the resolutions of 1 and 10 km

机译：在1 km和10 km分辨率下，芬兰的人口对交通和家用木材燃烧产生的主要PM 2.5 暴露的综合模型评估

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This study assesses population exposure caused by the emissions of primary fine particulate matter (PM2.5) 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 PM2.5; 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 PM2.5, 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.
机译：这项研究评估了2000年和2020年芬兰道路交通和家用木材燃烧产生的主要细颗粒物（PM 2.5 ）排放所引起的人口暴露。使用源-受体矩阵（ SRMs），基于使用本地和区域尺度的大气弥散模型进行的计算，基于两个不同的网格分辨率：1 km和10 km。全国范围内，道路交通和家用木材燃烧是主要的PM 2.5 的最重要排放源类别。预计到2020年，它们将占芬兰总排放量的42％。尽管预计将来交通排放量将大大减少，但从2000年到2020年将减少91％，但非排放量预计会增加。与国内木材燃烧排放相比，交通排放平均导致主要PM 2.5 的人口加权浓度（PWC）平均大大增加。根据1公里分辨率SRM的计算，到2020年，芬兰的交通和家庭燃烧造成的总PWC分别占排气和非排气交通排放的PWC的5.5％和62％。关于家用木材燃烧的子类别，补充木材加热导致相对较高的PWC，到2020年达到22％。使用区域规模模型以10 km的分辨率对交通排放和扩散进行建模，得出PWC更大。与使用1 km分辨率的局部比例模型进行的相应计算相比，它要小一个数量级。该研究的一般含义是，使用综合评估模型评估的PWC值可能对方法敏感，尤其是随着空间分辨率的提高，这些值可能会显着增加。

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