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Air pollution is an important cause of adverse health effects, even in the Nordic countries, which have relatively good air quality. Modelling-based air quality assessment of the health impacts relies on reliable model estimates of ambient air pollution concentrations, which furthermore rely on good-quality spatially resolved emission data. While quantitative emission estimates are the cornerstone of good emission data, description of the spatial distribution of the emissions is especially important for local air quality modelling at high resolution. In this paper we present a new air pollution emission inventory for the Nordic countries with high-resolution spatial allocation (1 km × 1 km) covering the years 1990, 1995, 2000, 2005, 2010, 2012, and 2014. The inventory is available at 10.5281/zenodo.10571094 (Paunu et al., 2023). To study the impact of applying national data and methods to the spatial distribution of the emissions, we compared road transport and machinery and off-road sectors to CAMS-REGv4.2, which used a consistent spatial distribution method throughout Europe for each sector. Road transport is a sector with well-established proxies for spatial distribution, while for the machinery and off-road sector, the choice of proxies is not as straightforward as it includes a variety of different type of vehicles and machines operating in various environments. We found that CAMS-REGv4.2 was able to produce similar spatial patterns to our Nordic inventory for the selected sectors. However, the resolution of our Nordic inventory allows for more detailed impact assessment than CAMS-REGv4.2, which had a resolution of 0.1° × 0.05° (longitude–latitude, roughly 5.5 km × 3.5–6.5 km in the Nordic countries). The EMEP/EEA Guidebook chapter on spatial mapping of emissions has recommendations for the sectoral proxies. Based on our analysis we argue that the guidebook should have separate recommendations for proxies for several sub-categories of the machinery and off-road sectors, instead of including them within broader sectors. We suggest that land use data are the best starting point for proxies for many of the subsectors, and they can be combined with other suitable data to enhance the spatial distribution. For road transport, measured traffic flow data should be utilized where possible, to support modelled data in the proxies. [ABSTRACT FROM AUTHOR]

Air pollution is an important cause of adverse health effects even in the Nordic countries, which have relatively good air quality. Modelling-based air quality assessment of the health impacts relies on reliable model estimates of ambient air pollution concentrations, which furthermore rely on good quality spatially resolved emission data. While quantitative emission estimates are the cornerstone of good emission data, description of the spatial distribution of the emissions is especially important for local air quality modelling on high resolution. In this paper we present a new air pollution emission inventory for the Nordic countries with high-resolution spatial allocation (1 km × 1 km) covering years 1990, 1995, 2000, 2005, 2010, 2012, and 2014. The inventory is available at https://doi.org/10.5281/ZENODO.8070155 (Paunu et al., 2023)). To study the impact of applying national data and methods to the spatial distribution of the emissions, we compared road transport and machinery and off-road sectors to CAMS-REGv4.2, which used consistent spatial distribution method throughout Europe for each sector. Road transport is a sector with well-established proxies for spatial distribution, while for machinery and off-road the choice of proxies is not as straightforward as it includes a variety of different type of vehicles and machines operating in various environments. We found that the CAMS-REGv4.2 was able to produce similar spatial patterns as our Nordic inventory for the selected sectors. However, the resolution of our Nordic inventory allows for more detailed impact assessment than the CAMS-REGv4.2, which had resolution of 0.1° × 0.05° (longitude-latitude, roughly 5.5 km × 3.5-6.5 km in the Nordic countries). The EMEP/EEA Guidebook chapter on spatial mapping of emissions has recommendations for the sectoral proxies. Based on our analysis we argue that the guidebook should have separate recommendations for proxies for several sub-categories of the machinery and off-road sectors, instead of including them within broader sectors. We suggest that land use data is the best starting point for proxies for many of the subsectors, and they can be combined with other suitable data to enhance the spatial distribution. For road transport, measured traffic flow data should be utilized where possible, to. support modelled data in the proxies. [ABSTRACT FROM AUTHOR]

Residential wood combustion (RWC) is a major source of air pollutants in the Nordic and many other countries. The emissions of the pollutants have been estimated with inventories on several scopes, e.g. local and national. An important aspect of the inventories is the spatial distribution of the emissions, as it has an effect on health impact assessments. In this study, we present a novel residential wood combustion emission inventory for the Nordic countries based on national inventories and new gridding of the emissions. We compare the emissions of the Nordic inventory, and especially their spatial distribution, to local assessments and European level TNO-newRWC-inventory to assess the spatial proxies used. Common proxies used in the national inventories in the Nordic countries were building data on locations and primary heating methods and questionnaire-based wood use estimates for appliances or primary heating methods. Chimney sweeper register data was identified as good proxy data, but such data may not be available in an applicable format. Comparisons of national inventories to local assessments showed the possibility to achieve similar spatial distributions through nation-wide methods as local ones. However, this won't guarantee that the emissions are similar. Comparison to the TNO-newRWC-inventory revealed the importance of how differences between urban and rural residential wood combustion are handled. The comparison also highlighted the importance of local characteristics of residential wood combustion in the spatial distribution of emissions. PM 2.5 emissions from residential wood combustion in the Nordic countries in 2014 per 1 km × 1 km cell. [Display omitted] • New high-resolution emission inventory for Nordic residential wood combustion. • Country level methods can produce similar spatial distributions as local level. • Difference between urban and rural RWC is important for the spatial distribution. • National characteristics are essential for spatial representation of RWC emissions. [ABSTRACT FROM AUTHOR]

Gas flaring in the oil and gas industry has been identified as an important source of anthropogenic black carbon (BC) affecting the climate, particularly in the Arctic. Our study provides spatially-explicit estimates of BC emissions from flaring in Russia utilising state-of-the-art methodology for determining the emission factors. We utilised satellite time series of the flared gas volume from Visible Infrared Imaging Radiometer Suite (VIIRS) for the period 2012 to 2017, supplemented with information on the gas and oil field type. BC emissions at flaring locations were calculated based on field type-specific emission factors, taking into account different gas compositions in each field type. We estimate that the average annual BC emissions from flaring in Russia were 68.3 Gg/year, with the largest proportion stemming from oil fields (82%). We observed a decrease in the yearly emissions during the period 2012 to 2017 with regional differences in the trend. Our results highlight the importance of detailed information on gas composition and the stage of oil and gas separation of the flared gas to reduce uncertainties in the BC emission estimates. [Display omitted] • New estimate for black carbon emissions from flaring in Russia. • Enhanced temporal profiles of flared gas volume from VIIRS. • Oil and gas field-type specific emission factors developed. • Average BC emissions from 2012 to 2017 are estimated at 68.3 Gg/year. [ABSTRACT FROM AUTHOR]

We present regionally aggregated emissions of greenhouse gases (GHG) from five land cover categories in Finland: artificial surfaces, arable land, forest, waterbodies, and wetlands. Carbon (C) sequestration to managed forests and unmanaged wetlands was also assessed. Models FRES and ALas were applied for emissions (CO2, CH4, N2O) from artificial surfaces and agriculture, and PREBAS for forest growth and C balance. Empirical emission coefficients were used to estimate emissions from drained forested peatland (CH4, N2O), cropland (CO2), waterbodies (CH4, CO2), peat production sites and undrained mires (CH4, CO2, N2O). We calculated gross emissions of 147.2 ± 6.8 TgCO2eq yr−1 for 18 administrative units covering mainland Finland, using data representative of the period 2017–2025. Emissions from energy production, industrial processes, road traffic and other sources in artificial surfaces amounted to 45.7 ± 2.0 TgCO2eq yr−1. The loss of C in forest harvesting was the largest emission source in the LULUCF sector, in total 59.8 ± 3.3 TgCO2eq yr−1. Emissions from domestic livestock production, field cultivation and organic soils added up to 12.2 ± 3.5 TgCO2eq yr−1 from arable land. Rivers and lakes (13.4 ± 1.9 TgCO2eq yr−1) as well as undrained mires and peat production sites (14.7 ± 1.8 TgCO2eq yr−1) increased the total GHG fluxes. The C sequestration from the atmosphere was 93.2 ± 13.7 TgCO2eq yr−1. with the main sink in forest on mineral soil (79.9 ± 12.2 TgCO2eq yr−1). All sinks compensated 63% of total emissions and thus the net emissions were 53.9 ± 15.3 TgCO2eq yr−1, or a net GHG flux per capita of 9.8 MgCO2eq yr−1. [ABSTRACT FROM AUTHOR]

The EU aims at reaching carbon neutrality by 2050 and Finland by 2035. We integrated results of three spatially distributed model systems (FRES, PREBAS, Zonation) to evaluate the potential to reach this goal at both national and regional scale in Finland, by simultaneously considering protection targets of the EU biodiversity (BD) strategy. Modelling of both anthropogenic emissions and forestry measures were carried out, and forested areas important for BD protection were identified based on spatial prioritization. We used scenarios until 2050 based on mitigation measures of the national climate and energy strategy, forestry policies and predicted climate change, and evaluated how implementation of these scenarios would affect greenhouse gas fluxes, carbon storages, and the possibility to reach the carbon neutrality target. Potential new forested areas for BD protection according to the EU 10% protection target provided a significant carbon storage (426–452 TgC) and sequestration potential (− 12 to − 17.5 TgCO2eq a−1) by 2050, indicating complementarity of emission mitigation and conservation measures. The results of the study can be utilized for integrating climate and BD policies, accounting of ecosystem services for climate regulation, and delimitation of areas for conservation. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive evaluation of the combination of the regional scale chemistry-transport model DEHM (Danish Eulerian Hemispheric Model) and the Gaussian plume-in-grid model UBMv10 (Urban Background Model). The focus of the study was centred around the following research question: the combination of an Eulerian regional scale approach and a Gaussian high-resolution/local scale approach improves the performance from evaluation with measurements compared to the Eulerian regional scale approach alone. We also investigated the research question that the integrated Eulerian/Gaussian approach has a similar performance as Eulerian models set up with the same high spatial resolution. The DEHM/UBM model has been run for a domain covering Denmark, Finland, Norway and Sweden with a 1 km × 1 km spatial resolution, producing hourly concentration estimates for four decades, 1979–2018. The results were evaluated against rural and urban background measurements in the four countries and the performance of the DEHM/UBM model was compared to the performance of the DEHM model based on a similar evaluation. The comparison showed that the DEHM/UBM model, in general, performs similar to the DEHM model, however, DEHM/UBM captures the interannual variability better in most cases. The DEHM/UBM model results for 2015 were also compared with corresponding high-resolution results from the chemistry-transport models SILAM (System for Integrated modeLling of Atmospheric coMposition) and MATCH (Multi-scale Atmospheric Transport and CHemistry model) for the four Nordic capitals; Copenhagen, Helsinki, Oslo and Stockholm. This model comparison was carried out to evaluate and compare the performance of the relatively simple, yet computationally fast approach of the DEHM/UBM model setup to the more time-consuming approaches of applied regional scale models on very high-resolution. The DEHM/UBM model performed similarly to SILAM and MATCH for most components, however, the 3D models performed better with respect to capturing the differences between rural and urban settings for the four capitals. • Combining a regional scale Eulerian model with a Gaussian plume-in-grid model enables long-term high-resolution local scale modelling of air pollution for a large geographic area. • Ambient concentrations of NO 2 , O 3 and PM 2.5 in the continental Nordic countries were modelled with 1 km x 1 km spatial and hourly temporal resolution for 1979-2018. • The Eulerian-Gaussian approach performs better than the Eulerian approach for PM 2.5 in general and with respect to year-to-year variation for NO 2 and O 3. • The Eulerian-Gaussian approach performs similar to high-resolution local scale Eulerian models. [ABSTRACT FROM AUTHOR]