Role of land cover in Finland’s greenhouse gas emissions

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. Supplementary Information The online version contains supplementary material available at 10.1007/s13280-023-01910-8.

Emissions from waste management consist of CH4 from dump sites, CH4 and N2O from wastewater treatment, and CH4 and N2O from biological treatment, i.e., composting and decomposition.Emissions from dump sites are calculated with the First Order of Decay method (IPCC 2006).Information on the annual amount of waste dumped, its composition and decomposition properties, and the recovery of waste gases is input to the calculations.Default parameters used in the national GHG inventory are applied (Statistics Finland 2022), with information on waste amount and gas recovery on the municipality and dump site level.For emissions from biological and wastewater treatment, National GHG inventory values are allocated to municipalities based on information on population and the building area of industrial plants.For each municipality, waste management emissions are reported for each municipality according to the amount of waste produced in each municipality, regardless of where the waste was managed, and aggregated to the region in which the municipality is located.
Agriculture (from Lounasheimo et al. 4.11 Maatalous) Emissions from agriculture consist of CH4 and N2O from domestic livestock production (enteric fermentation and manure management), and CO2 from field cultivation (liming and urea application) (Table ALas 11).Information on the number of livestock in each municipality is input to the calculations.Emissions from field cultivation use information on the cultivated area of different crops in each municipality and the crop yield in each region, as well as national level usage of agricultural liming material, urea, mineral nitrogen fertilizer and municipal sewage sludge.

Summary of PREBAS model runs
Carbon sequestration in forest biomass was simulated with PREBAS, which is a dynamic processbased model of carbon assimilation and tree growth (Minunno et al. 2016(Minunno et al. , 2019)).PREBAS is initialized using forest structural variables (i.e.average height of the stand, average diameter at breast height, basal area).The model is initialized for the three main species in Finland: Scots pine, Norway spruce and Silver birch.Information on the initial state of the forest is based on data from the multi-source national forest inventories (MS-NFI), that provide forest variables at 16 m resolution.Regional harvesting intensities are modelled on the basis of the Finnish national statistics and consist of annual levels of roundwood, pulpwood and energy wood.

Examples of regional differences
Cropland cultivation on mineral soil in Southwest Finland (region 2) contributed 15% of total mineral soil emissions from cropland in the 18 regions.Cropland cultivation on mineral soil was an important source of emissions in Satakunta (region 4) (9% of country total mineral soil cropland GHG).Peat as fuel in energy production caused also high emissions in Satakunta (15% of country total energy production with peat).Total anthropogenic emissions in Satakunta represented 5% of the country total, while forest emissions were 4% of country total.Satakunta total sink was 3% of the total sink of mainland Finland.
In all of Ostrobothnia (regions 14, 15, 16, 17), as well as in Satakunta and Kanta-Häme (regions 4, 5) the relative importance of cropland emissions was higher than the country average (5%) (Suppl.Fig. S7).In Central and North Ostrobothnia, Kainuu and Lapland (regions 16,17,18,19) more than a quarter of the cultivated area was on organic soils.For these regions 98% of the cropland emissions were from organic soils.For the whole country the importance of the organic soils for cropland emissions was almost equally high, 93% (Suppl.Tab.S13).
Forests on mineral soils caused on average 81% of the total forest emissions.Only in North Karelia, South, Central and North Ostrobothnia, Kainuu and Lapland (regions 12,14,16,17,18,19) the role of forested mineral soils was lower than 20% (Suppl.Tab.S14).The carbon sequestration in forests on mineral soil represented 89% of the total forest sink on the country level.Only in South, Central and North Ostro-bothnia and in Kainuu did less than 90% of the total forest sink occur on upland forest soils.Figure S3.Net emission intensity (GgCO2eq km -2 yr -1 ).

Figure S4 .
Figure S4.Relative area of artificial surfaces.

Figure S6 .
Figure S6.Relative area of arable land.

Table S1 .
Administrative regions

Table S4 .
Spatially explicit data sources

Table S6 .
Emission flux rates from arable land, given as mean (standard deviation)

Table S7 .
Carbon flux rates of lakes for five lake size classes, given as mean (standard deviation), standard deviations as inVanhala et al. (2016).

Table S9 .
Carbon flux rates of rivers of different size classes, given as mean (standard deviation), standard deviations as inVanhala et al. (2016).
TableS11aEmission flux rates of undrained mires, given as mean (standard deviation)