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In peatlands drained for forestry, the soil carbon (C) or carbon dioxide (CO 2) balance is affected by both (i) higher heterotrophic CO 2 -C release from faster decomposing soil organic matter (SOM) and (ii) higher plant litter C input from more vigorously growing forests. This balance and other greenhouse gas (GHG) sinks and sources in managed lands are annually reported by national GHG inventories to the United Nations Climate Change Convention. In this paper, we present a revised, fully dynamic method for reporting the CO 2 balance of drained peatland forest soils in Finland. Our method can follow temporal changes in tree biomass growth, tree harvesting and climatic parameters, and it is built on empirical regression models of SOM decomposition and litter input in drained peatland forests. All major components of aboveground and belowground litter input from ground vegetation as well as live trees and trees that died naturally are included, supplemented by newly acquired turnover rates of woody plant fine roots. Annual litter input from harvesting residues is calculated using national statistics of logging and energy use of trees. Leaching, which also exports dissolved C from drained peatlands, is not included. The results are reported as time series from 1990–2021 following the practice in the GHG inventory. Our revised method produces an increasing trend of annual emissions from 0.2 to 2.1 t CO 2 ha -1 yr -1 for the period 1990–2021 in Finland (equal to a trend from 1.4 to 7.9 Mt CO 2 yr -1 for the entire 4.3 Mha of drained peatland forests), with a statistically significant difference between the years 1990 and 2021. Across the period 1990–2021, annual emissions are on average 1.5 t CO 2 ha -1 yr -1 (3.4 Mt CO 2 yr -1 for 2.2 Mha area) in warmer southern Finland and - 0.14 t CO 2 ha -1 yr -1 (- 0.3 Mt CO 2 yr -1 for 2.1 Mha area) in cooler northern Finland. When combined with data on the CO 2 sink created by the growing tree stock, in 2021 the drained peatland forest ecosystems were a source of 1.0 t CO 2 ha -1 yr -1 (2.3 Mt CO 2 yr -1) in southern Finland and a sink of 1.2 t CO 2 ha -1 yr -1 (2.5 Mt CO 2 yr -1) in northern Finland. We compare these results to those produced by the semi-dynamic method used earlier in the Finnish GHG inventory and discuss the strengths and vulnerabilities of the new revised method in comparison to more static emission factors. [ABSTRACT FROM AUTHOR]

Hydrogen Direct Reduction of Iron (HDRI) combined with renewable electricity is an attractive option for low-carbon steel production. In this paper, we present a novel and computationally efficient techno-economic power-to-x-plant optimization model which is then applied to an HDRI plant located in Finland. Plant dimensioning was carried out in several current and future power market and regulatory scenarios. We predict a production cost of 373 €/t for hot briquetted iron, and 351 €/t for a future scenario of 2025–2030. When the recently introduced EU rules for renewable fuels of non-biological origin are applied, the production costs increased by 30–46 €/t. The rules also have a significant increasing effect on the required hydrogen storage. The flexibility of the direct reduction shaft emerged as an important parameter affecting the required hydrogen storage as well as total production cost. The results of this paper hold significance for the optimal design of future low-carbon steel plants. • Computationally efficient optimization model for Power-to-X operations and dimensions. • Hydrogen Direct Reduction Ironmaking (HDRI) plant using wholesales and wind power. • Significant amounts of intermittent wind power can be absorbed by the HDRI plant. • HDRI/HBI production costs analyzed for EU regulatory scenarios on green hydrogen. • Emission reductions over 96% compared to CO 2 emissions of fossil steelmaking. [ABSTRACT FROM AUTHOR]

The electricity sector has a central role in the efforts to meet climate targets. Consequently, efforts are taking place to electrify industry, heating, and transportation. The Finnish government has set the target to halve carbon dioxide traffic emissions by 2030 and achieve carbon neutrality by 2045. Due to this target, the currently small proportion of electric vehicles (EVs) in Finland could expand in a manner that is difficult to forecast but could be exponential. Amid already strained investment budgets, anticipating the alternative scenarios and impacts of such a transport electrification evolution is of high importance to distribution system operators in order to optimize network planning and enhancements during the coming 15–25 years. The novelty and contribution of this paper is in utilizing a formal scenario planning process to envision what the alternative scenarios are (i.e., possible futures) for the evolution of the electric car fleet in Finland until 2040 and how these alternative scenarios could impact distribution grids. The impact analysis is performed in terms of additional energy and additional power in order to gain an understanding of the high-level impacts and investment needs. The analysis utilizes a real distribution grid in southern Finland as a case example that enables quantification. The results indicate the electric vehicles will, depending the scenario, pose an essential additional load in terms of both energy and power and that the required investment levels and investment types will be heavily dependent on the scenario. [ABSTRACT FROM AUTHOR]

Reporting the greenhouse gas (GHG) emissions from the LULUCF sector in the GHG inventory requires sound methods for estimating both the inputs and outputs of carbon (C) in managed ecosystems. Soil CO2 balance of forests consists of the CO2 released from decomposing soil organic matter (SOM) and the C entering 15 the soil through aboveground and belowground plant litter input. Peatlands drained for forestry release soil C as CO2 because the drainage deepens the oxic peat layer prone to SOM decomposition. IPCC Guidelines provide default CO2 emission factors for different climatic zones and the defaults or locally adapted static emission factors are commonly in use in GHG inventory reporting for drained peatlands. In this paper, we describe a new dynamic method to estimate the CO2 balance of drained peatland forest soils in Finland. Contrary to static emission factors, the annual CO2 release from soil is in our method estimated using empirical regression models driven by time series of tree basal area (BA), derived from the national forest inventories in Finland, time series of air temperature and the drained peatland forest site type. Aboveground and belowground litter input is also estimated using empirical models with newly acquired turnover rates for tree fine roots and BA as a dynamic driver. All major components of litter input from ground vegetation and live, harvested and naturally died trees are included. Our method produces an increasing trend of emissions from 1.4 to 7.9 Mt CO2 for drained peatland forest soils in Finland for the period 1990-2021, with a statistically significant difference between years 1990 and 2021. Across the period 1990-2021, annual emissions are on average 3.4 Mt and -0.3 Mt in southern and northern parts of Finland, respectively. When combined with data of the CO2 sink created by trees, it appears that in 2021 drained peatland forest ecosystems were a source of 2.3 Mt CO2 in southern Finland and a sink of 2.5 Mt CO2 in northern Finland. We compare the emissions produced by the new method with those produced by the old GHGI method of Finland and discuss the strengths and vulnerabilities of our method in comparison to static emission factors. [ABSTRACT FROM AUTHOR]

Nuclear energy is a particularly regulated and politicised part of energy production. In this article, we analyse how private companies have promoted their interests in this challenging sector. We focus on the case of Finland, where manufacturing industries have regarded cheap and abundant power as a key component of their business strategies. From the 1950s onwards, nuclear energy seemed a particularly attractive option, as Finland had few alternative power sources. However, private companies faced opposition from a number of actors. They included the Soviets, who were eager to sell their reactors, while the Finns wanted to buy Western ones; centrist and left-wing politicians, who favoured state-controlled options; and finally, the environmental movement, which from the 1980s onwards opposed the construction of all new reactors. Politicians rejected proposals for a fifth nuclear reactor until the industrialists learned to present the reactor as a 'green' project, which would reduce carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

The Sustainable Development Goal (SDG) that emphasizes sustainable and affordable energy presents a practical pathway to achieve sustainable growth. Moreover, this goal aligns with SDG 13, which focuses on climate action. Nonetheless, it is important to consider factors such as political and financial risk, as they can influence climate action efforts and the renewable energy sources adoption. Hence, this study broadens the conversation surrounding CO 2 emission reduction and the achievement of Sustainable Development Goals (SDGs). It accomplishes this by investigating the interplay between renewable energy, political risk, financial risk, and CO 2 emissions in Finland spanning from 1990/Q1 to 2021/Q4. Notably, this research distinguishes itself through its exploration of these complex connections, employing a wavelet-based quantile methodology. Unlike traditional quantile regression, which can only reveal connections between variables within each quantile, the wavelet-based quantile approach enables the simultaneous capture of correlations across quantiles and periods. The results show that in the long-term and across all quantiles (0.01–0.99), energy efficiency, specifically gas and oil efficiency, lessens CO 2. In addition, low financial and political risks improve ecological quality by lessening CO 2 across all periods and quantiles (0.01–0.99). The paper outcomes serve as a basis for formulating a policy framework aimed at achieving SDG 7 and SDG 13 in Finland. • We explore the impact of energy efficiency and country risk on CO 2 emissions. • The role of renewable energy and economic growth are also analyzed. • The Time series data of the Finland is used from 1990/Q1 to 2020/Q4. • Various wavelet-based quantile correlation is applied. • Renewable energy, oil and gas efficiency decrease CO 2 emissions in each quantile and across periods. [ABSTRACT FROM AUTHOR]

More than 25% of the total energy consumption in Finland has been produced with wood fuels. Since 2012, the share has been greater than that of oil, coal, or natural gas. Internal carbon pricing is used to manage the risks in wood procurement after wood import from Russia ended. Further, the EU announced plans to sell more carbon emission permits to fund the EU's exit from Russian energy. To manage these challenges, a data-driven internal carbon pricing mechanism (DDICPM) has been developed for wood procurement optimization. Particularly, local changes are considered via available information about growth-based carbon sinks (GBCS). The results of the new scenario were compared to the basic national scenario that ensures carbon neutrality in forestry. The DDICPM may provide the optimum wood-procurement operations maintaining carbon neutrality in the integrated energy and material industry (IEMI). In this study, the use of DDICPM increased profitability b 16.2, 16.1, and 16.0% between adapted wood procurement areas at the EU's emission allowance prices of 30, 65, and 98 € t−1 CO2. The experiments' results also revealed that the DDICPM could consistently and significantly outperform the conventional solution adopted by the company in terms of economic costs. A significant conclusion is that an increase in profitability is possible if the size of wood procurement areas is allowed to vary optimally with respect to transport distance to take advantage of the GBCS as a new application of the renewable carbon sink. [ABSTRACT FROM AUTHOR]

This paper examines the asymmetric and long-run effect of energy productivity on the quality of the environment in Finland. Finland, as one of the Nordic countries, is a major contributor to the global drive to achieve decarbonization by 2050. In effect, this study seeks to contribute to the strides by querying the extent to which shocks in energy productivity make or mar the sustainability of the Finland environment from 1990:Q1 to 2019:Q4. The other impacts of financial development, economic growth, and trade openness are considered in the model estimated by using the novel hidden panel cointegration and nonlinear autoregressive distributed lag (NARDL) methodology. The results reveal a significant asymmetric equilibrium cointegration relationship among the variables over long-run time horizons; energy productivity utilization enhances the quality of the environment in Finland over the long run while trade openness, financial development, and economic growth contribute to environmental degradation in Finland in the long term. In particular, a 1% positive and negative fluctuation in energy productivity lowers carbon emissions by 1.79442% and 0.84799% in the long term. Whereas 1% change in trade openness, financial development, and economic growth trigger CO 2 emissions (CO 2 E) by 1.15298%, 0.271365%, and 2.93402% in Finland's economies. The results of the frequency domain causality model corroborate the NARDL results. On the basis of these empirical findings, this study suggests that policymakers in Finland should consider the asymmetric behavior among these variables in setting their trade, environmental, growth, and energy policies. [Display omitted] • The effect of energy productivity on environmental degradation in Finland is examined. • Nonlinear ARDL, Fourier ADL cointegration and frequnecy domain causality tests are employed. • Energy productivity leads to lower environmental degradation in Finland. • Energy productivity causes environmental sustainability at different frequencies. [ABSTRACT FROM AUTHOR]

Ecotechnologies have the potential to reduce the use of finite resources while providing a variety of co-benefits to society, though they often lack in market competitiveness. In this study, we investigate the sustainability of ecotechnologies for recovering carbon and nutrients, and demonstrate how a so-called "bottom-up" approach can serve as a decision-making instrument. Based on three case study catchments with a focus on domestic wastewater in Sweden and Poland, and on manure, grass and blackwater substrates in Finland, we apply a cost–benefit analysis (CBA) on system alternatives derived from a participatory process. After drawing on an initial systematic mapping of relevant ecotechnologies, the scope of the CBA is determined by stakeholder suggestions, namely in terms of the considered assessment criteria, the physical impacts and the utilised data. Thus, this CBA is rooted in a localised consideration of ecotechnologies rather than a centralised governmental approach to systems boundaries. The key advantage of applying such a bottom-up approach is that it has gone through a robust participatory selection process by local stakeholders, which provides more legitimacy to the decisions reached compared with traditional feasibility studies. Despite considering the revenues of the recovered products as well as the provision of the non-market goods CO2 mitigation and reduced eutrophication, findings from this study indicate that the benefits of the considered ecotechnologies are often outweighed by their costs. Only anaerobic digestion of agricultural wastes appears to be economically feasible under the current conditions, highlighting that further efforts and incentives may be required to mainstream ecotechnologies. [ABSTRACT FROM AUTHOR]