• Energy Research
• 2016-2025close
• Closed Access close
• Embargo close
• FI close
• CD close

Abstract This study demonstrates the possibility to use energy-cost optimal building designs based on life cycle approach. There is a lack of studies that cover the comprehensive assessment of both embodied energy (EE) and operational energy (OE) in a single optimization problem. The primary goal of the current study is to compare the optimized results of using OE+EE together and OE only. The optimization is performed on a case study building (townhouse) in Finland with three structural alternatives (i.e., reinforced concrete (RC); cross-laminated timber (CLT) and Steel). Different options for insulation thickness of external wall, roof, floor and window types were considered as decision variables as the scope of the present study is on building envelope. The objectives of the optimization are to minimize life cycle energy (LCE) and life cycle costs (LCC). The LCE difference between the most and least energy efficient solution on the pareto front is greater in case of the OE optimization, compared to OE+EE optimization. For all studied structures, the EE of the optimal solutions from OE+EE optimization ranges 16%–23% of LCE. Many of the non-dominated optimal solutions obtained from the OE+EE optimization shows a higher U-value for the building envelope components compared to the optimal solutions from the OE optimization. A relationship between both OE and EE with the overall thermal resistance of the building envelope is discussed to obtain a deeper understanding of such differences in U-value for the optimal solutions obtained from the OE+EE and OE optimization.

One of the biggest challenges in forestry research is the effective and accurate measuring and monitoring of forest variables, as the exploitation potential of forest inventory products largely depends on the accuracy of estimates and on the cost of data collection. This paper presented a novel computational method of low-cost forest inventory using global navigation satellite system (GNSS) signals in a crowdsourcing approach. Statistical features of GNSS signals were extracted from widely available GNSS devices and were used for predicting forest attributes, including tree height, diameter at breast height, basal area, stem volume, and above-ground biomass, in boreal forest conditions. The basic evidence of the predictions is the physical correlations between forest variables and the responses of GNSS signals penetrating through the forest. The random forest algorithm was applied to the predictions. GNSS-derived prediction accuracies were comparable with those of the most accurate 2-D remote sensing techniques, and the predictions can be improved further by integration with other publicly available data sources without additional cost. This type of crowdsourcing technique enables the collection of up-to-date forest data at low cost, and it significantly contributes to the development of new reference data collection techniques for forest inventory. Currently, field reference can account for half of the total costs of forest inventory.

This paper presents an optimal control strategy for a district heating power plant with thermal energy storage. The main goal of the control strategy is to reduce the operation costs of the power plant, by scheduling the boilers, the operation of the thermal energy storage and the curtailment on the loads. The problem is stated as a constrained optimization in the form of a Mixed Integer Linear Program (MILP), embedded on an Model Predictive Control (MPC) framework. Particular attention is paid to modeling of boilers operating constraints, including the outlet water flow temperature, to the energy exchanged with the thermal energy storage and to the operating modes of the power plant layout, including the constraints related to the supply water temperature needed from the network. The results are performed using the data and the layout of the power plant located in the city of Ylivieska, in Finland. The cost analysis performed shows the advantages of using the predictive control strategy.

The growing concern on global warming has pushed to set ambitious targets of carbon neutrality or net zero at the water sector. Meanwhile, poor data availability has been reported to restrict the national assessment of climate impacts and mitigation strategies in water sector. In national greenhouse gas (GHG) inventories, water sector is embedded in other sectors' emissions making it difficult to monitor separately. This study presents a national scale evaluation of climate change impacts for water sector in Finland based on life cycle analysis (LCA). In addition, the effectiveness of currently available emission reduction measures is evaluated by scenario analysis until the year 2035. According to the results, the life cycle climate change impacts from the Finnish municipal water sector were 0,67 (0,46-0,88) million tonnes CO2-eq./year (142.8 (98.9-187.1) kg CO2-eq./person/year). Drinking water services accounted for 12.5-13.9 % and wastewater services 86.1-87.4 % of the total emissions. With currently feasible emission reduction measures, the climate change impacts could be reduced approximately 14-30 % in total by 2035. The aim of carbon neutrality in the water sector was found to be unrealistic to achieve with existing and currently feasible measures for Finland and thus significant new emission mitigation measures are needed. The vague definition of carbon neutrality and system boundary of water sector as well as the uncertainties related to the assessment of direct emissions, undermine the credibility of the ambitiously set target. Prioritizing emission offsets to reach the target may inadvertently lead to unintended negative consequences due to the limitations and incompleteness of offset methods.

Reduction of greenhouse gas emissions and mitigation of climate change are the main aims of the global climate policy. Increased use of renewable energy is a central measure in achieving these goals. However, mitigation of climate change through increased use of renewable energy also has negative environmental impacts. Focusing merely on greenhouse gas emissions may lead to overseeing these other negative environmental impacts and thereby in unwanted side-effects. The aim of this review was to assess the overall life cycle impacts related to the production and use of the different renewable energy sources. Impacts were assessed for unit processes and for the Finnish national renewable energy targets as a whole. The review points out that in order to comprehensively understand the overall environmental impacts of the different renewable energy sources, a thorough life cycle assessment with a unified framework would be needed. Presently there is only limited information available or the published results are not comparable with each another. However, assessment using the Finnish National Renewable Energy Targets for 2020 also indicates that under the present targets, the overall environmental impacts of the renewable energy use are likely to be low. Main impacts or risks of impacts relate to the use of forest energy.

During urban planning, city planners and municipal authorities make various choices that impact districts' energy efficiency and emissions significantly. However, they often lack information about the actual effects of the design options. This paper describes a methodology, embedded to a tool called Kurke, that aims to support the planning of sustainable and energy efficient urban areas by analysing the energy performance of city plans and the impacts of their energy design alternatives on carbon dioxide emissions during planning. The methodology supports holistic energy analysis of urban areas, including energy demand of buildings and transport, and comparing 10 alternatives for local energy supply. The methodology is tested in two Finnish residential and mixed-use areas. The improved transportation plans can reduce CO2 emissions 10-20% compared to the business-as-usual design in case areas. CO2 emissions from buildings' heating can be reduced 18-24%. The total CO2 reduction potential of urban planning choices varies from 2% to 78% in case areas. This shows the significant role of urban planning in reducing CO2 emissions. Therefore, it is important that urban planners understand the impacts of the design decisions. Kurke tool offers such support with fast and practical evaluation of the planning options.