Greenhouse Gas Fluxes of Agricultural Soils in Finland. In: Shurpali N, Agarwal AK, Srivastava V, editors. Greenhouse Gas Emissions. Singapore: Springer; 2019. pp. 7-22. [DOI: 10.1007/978-981-13-3272-2_2]

Modelling the regional potential for reaching carbon neutrality in Finland: Sustainable forestry, energy use and biodiversity protection

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.

Sources and sinks of greenhouse gases in the landscape: Approach for spatially explicit estimates

Climate change mitigation is a global response that requires actions at the local level. Quantifying local sources and sinks of greenhouse gases (GHG) facilitate evaluating mitigation options. We present an approach to collate spatially explicit estimated fluxes of GHGs (carbon dioxide, methane and nitrous oxide) for main land use sectors in the landscape, to aggregate, and to calculate the net emissions of an entire region. Our procedure was developed and tested in a large river basin in Finland, providing information from intensively studied eLTER research sites. To evaluate the full GHG balance, fluxes from natural ecosystems (lakes, rivers, and undrained mires) were included together with fluxes from anthropogenic activities, agriculture and forestry. We quantified the fluxes based on calculations with an anthropogenic emissions model (FRES) and a forest growth and carbon balance model (PREBAS), as well as on emission coefficients from the literature regarding emissions from lakes, rivers, undrained mires, peat extraction sites and cropland. Spatial data sources included CORINE land use data, soil map, lake and river shorelines, national forest inventory data, and statistical data on anthropogenic activities. Emission uncertainties were evaluated with Monte Carlo simulations. Artificial surfaces were the most emission intensive land-cover class. Lakes and rivers were about as emission intensive as arable land. Forests were the dominant land cover in the region (66%), and the C sink of the forests decreased the total emissions of the region by 72%. The region's net emissions amounted to 4.37 ± 1.43 Tg CO₂-eq yr^-1, corresponding to a net emission intensity 0.16 Gg CO₂-eq km^-2 yr^-1, and estimated per capita net emissions of 5.6 Mg CO₂-eq yr^-1. Our landscape approach opens opportunities to examine the sensitivities of important GHG fluxes to changes in land use and climate, management actions, and mitigation of anthropogenic emissions.

Agriculture-induced environmental Kuznets curve: the case of China

This study investigates the long-run equilibrium relationship among carbon dioxide (CO₂) emissions, real income, energy consumption, and agriculture, thus testing the existence of the agriculture-induced environmental Kuznets curve (EKC) hypothesis in the case of China for the period of 1971-2014. The level relationship among the variables in the conducted model is confirmed by the bounds test approach under the autoregressive distributed lag (ARDL) mechanism. Error correction model under the ARDL mechanism suggests that short-run values of CO₂ emissions converge to its long-run equilibrium level by 73.8% speed of adjustment every year by the contribution of energy consumption, real income, and agriculture. ARDL estimation results suggest that real income and energy consumption have a positive, elastic impact; agricultural development has positive, inelastic impact on CO₂ emissions where squared real income has a negative and inelastic impact on air pollution. Conditional Granger causality test results reveal that there are unidirectional causalities running from real income, squared real income, energy consumption, and agricultural development in long run as well as in the short run.