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Planning power system (PS) towards renewable energy is crucial for reducing carbon dioxide (CO 2) emission as well as mitigating climate change. However, the inherent uncertainty and hierarchical structure of PS pose intractable challenges to the planning process. This study develops a multi-GCM-based interval bi-level programming (MIBP) method that can balance two-level decision-making conflict between CO 2 -emisison reduction and system cost minimization. MIBP can also deal with uncertainties expressed as interval values in objective functions and constraints. Then, a MIBP-PS model is formulated to plan PS for China (2021–2050), where the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. The major findings are: (i) the CO 2 emission for PS would reach peak value before 2030 and then reduce by [10.2, 20.4]% in 2050, which is mainly owing to the curtailment of fossil fuel; (ii) compared with the conventional model, CO 2 emission from MIBP-PS model could decrease by [3.1, 4.8]%, which shows the superiority of the developed model; (iii) the fossil-fuel power would be gradually replaced by renewable energy, and the proportion of coal-fired power would decrease by 38.8% by 2050, especially small coal-fired facilities (i.e., below 0.3 GW) should be gradually phased down. [Display omitted] [ABSTRACT FROM AUTHOR]

To mitigate climate change, many studies have been conducted to identify the determinants of CO 2 emissions. However, a consensus has not been reached yet on the issue because past work has often not considered the unobserved individual heterogeneity across countries. Therefore, this study revisits the environment-energy-growth nexus by employing a panel quantile regression to incorporate the effects of renewable energy consumption and technological innovation within the research background of global 30 countries over the period 1980–2014. The advantage of this method is considering the distributional heterogeneity to provide a detailed description of linkage between the CO 2 emissions and driving factors at different emissions levels. The results show that the effects of determinants on CO 2 emissions are heterogeneous. For high-emissions countries, the function of renewable energy consumption is limited in reducing CO 2 emissions due to the smaller proportion of renewable energy use. Moreover, technological innovation greatly affects countries with relatively higher CO 2 emissions. Therefore, one option is to financially support and apply technological innovations to generate renewable energy at lower costs as well as increase energy efficiency. Moreover, transforming the economic growth mode is helpful to transfer from non-renewable to renewable sources of energy to meet energy demand. [ABSTRACT FROM AUTHOR]

Abstract: Biomass from the forest sector can be an important source of renewable energy and can contribute to climate change mitigation and bioenergy development. However, the removal of biomass from forests has significant impacts on the forest ecosystem. For instance, it modifies soil litter which is particularly important to preserve soil characteristics and to sustain a diversity of organisms. Our aim is to analyze alternatives of sustainable forest management and compare how they perform in terms of carbon savings in order to assess the role of the sector in a regional emission reduction plan. The analysis is performed applying CO2FIX, a well-known carbon accounting model to the forests of the Italian region of Emilia-Romagna. The behavior of the most important forest macro-categories is investigated under common management alternatives: no harvest activities, maintenance of a constant stock, different rotation lengths, and maximization of harvested biomass. We evaluate their impact at landscape level on the regional carbon budget, thus estimating the maximum potential contribution from the forest sector. [Copyright &y& Elsevier]