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Financial Incentives (FIs) for green buildings are a major component of energy policy planning and play a vital role in the promotion of sustainable development and carbon mitigation strategies. Despite the presence of numerous FIs in Canada, there is still a lack of understanding on their distribution and effectiveness. This review first investigates the FIs available for residential and commercial buildings in Canada, and then performs a comprehensive review of studies related to FIs' effectiveness evaluation. It is found that FIs for buildings in Canada can be distributed into four categories tax, loans, grants, and rebates. Among these, rebates from utility providers are the most common and are administered in all provinces. In addition to these, special incentives are available for three end-users (low-income, aboriginal people, landlords and tenants) and for three types of buildings (heritage, non-profit and energy rated). A clear contrast is observed on FIs offered in three regulatory regimes (Federal, provincial and municipal). Four provinces (Alberta, British Columbia, Ontario and Quebec) are leading in green building efforts. The in-depth literature review was also used to develop an understanding on the criteria used in effectiveness evaluation and the factors impacting effectiveness. Based on the findings of different studies on FIs effectiveness, a generic approach for evaluation of FIs is proposed that can help in deploying successful FIs programs. The results of this review are of importance to the policymakers, government authorities, and utilities engaged in designing and improving FIs for energy efficient buildings.Environmental change created worldwide interest in investing in renewable energy. Less reliance on fossil fuels would have a substantial influence on investors for alternative energy, especially renewable energy. The literature has concentrated on empirical studies of herding behaviour in finance, but not in renewable energy. This paper fills the gap by investigating herding in renewable energy, using daily closing prices in renewable and fossil fuel energy stock returns in the USA, Europe, and Asia, for March 24, 2000-May 29, 2020, which covers the Global Financial Crisis (GFC) (2007-2009), the coronavirus crises of SARS (2003). And the ongoing COVID-19 (2019-2020) pandemic. The paper shows that (1) for low extreme oil returns, investors are more likely to display herding in the stock market; (2) for SARS and COVID-19, herding is more likely during extremely high oil returns after the GFC; and (3) herding is more likely during periods of extremely low oil returns during the coronavirus crises. These results suggest that after the GFC, investors are more sensitive to asset losses, so they will be more likely to display herding in the stock market. However, during SARS and COVID-19, investors panic so they may unwisely sell their assets. There are strong cross-sector herding spillover effects from US fossil fuel energy to renewable energy, especially before the GFC, while the US fossil fuel energy market has a significant influence on the Europe and Asia renewable energy returns during COVID-19. During SARS, which was not a pandemic, US fossil fuels only had an impact on US renewable energy returns.This paper offers perspectives on the development of low-carbon energy technology in Brazil, pinpointing changes that have occurred since our former publication in 2011. It takes a fresh approach in terms of how likely Brazil will achieve its Nationally Determined Contributions Commitments in the energy sector. ubiquitin-Proteasome degradation Many countries have implemented national climate policies to accomplish their pledged NDC and contribute to the temperature objectives of the Paris Agreement on climate change. Based on official reports and databases of energy development projections in Brazil and the socioeconomic context, we discuss what can be expected for the future of the Brazilian energy sector, the probability of implementing selected technologies, and the prospects of reaching the NDC targets for 2025 and 2030. In addition, this paper provides an overview of the current stage of development of these technologies, main directions, and bottlenecks in Brazil. Analyses have shown that the Brazilian renewable matrix tends to remain significant, driven by the development of solar and mostly small hydroelectric power sources, as well as different types of biomass. In addition, the system will include the replacement of thermoelectric plants powered by diesel and fuel oil by natural gas plants. The prospects for Brazil's official energy plan for 2027 are aligned with the reference technology scenario, which represents the business as usual scenario. Despite this, low-carbon technologies could be implemented far beyond the NDC's goals, given the abundance of renewable natural resources in the country.We reviewed the literature focusing on nineteen integrated Energy System Models (ESMs) to (i) identify the capabilities and shortcomings of current ESMs to analyze adequately the transition towards a low-carbon energy system; (ii) assess the performance of the selected models by means of the derived criteria, and (iii) discuss some potential solutions to address the ESM gaps. This paper delivers three main outcomes. First, we identify key criteria for analyzing current ESMs and we describe seven current and future low-carbon energy system modeling challenges the increasing need for flexibility, further electrification, emergence of new technologies, technological learning and efficiency improvements, decentralization, macroeconomic interactions, and the role of social behavior in the energy system transition. These criteria are then translated into required modeling capabilities such as the need for hourly temporal resolution, sectoral coupling technologies (e.g., P2X), technological learning, flexibility technologies, stakeholder behavior, cross border trade, and linking with macroeconomic models. Second, a Multi-Criteria Analysis (MCA) is used as a framework to identify modeling gaps while clarifying high modeling capabilities of MARKAL, TIMES, REMix, PRIMES, and METIS. Third, to bridge major energy modeling gaps, two conceptual modeling suites are suggested, based on both optimization and simulation methodologies, in which the integrated ESM is hard-linked with a regional model and an energy market model and soft-linked with a macroeconomic model.