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Canadian provinces are required to regulate their power sectors using carbon pricing systems that meet national minimum stringency standards, which are set by the federal government. A diverse set of systems has emerged as a result. However, there has been limited assessment of how different pricing mechanisms impact the evolution of Canada's electricity system. To address this gap, we use an electricity system planning model called COPPER and a scenario-based approach to assess if, and to what extent, different policy regimes impact power sector greenhouse gas emissions and costs. Our results show that carbon pricing systems currently in place lead to significant carbon reductions over the long term, provided that free emissions allocations are reduced. However, the cost-optimal pathway for the power sector differs across provinces depending on the carbon pricing mechanism. Some provinces achieve least-cost emissions reductions by switching from high-carbon technologies to renewables, while others are better served by replacing high-carbon technologies with low-carbon fossil fuel alternatives. Further, provinces that implement cap-and-trade systems may affect the transitions of interconnected jurisdictions. Power sector climate policy design should reflect the heterogeneity of available assets, resources, and neighbouring approaches. [ABSTRACT FROM AUTHOR]

Jurisdictions use an assortment of policies to reduce greenhouse gas emissions. Climate policy mixes have often evolved through the ad hoc layering of new policies onto an existing policy mix, rather than deliberate design of a complete policy portfolio. This can lead to unanticipated interactions between policies which can support or undermine policy objectives and is further complicated where climate policy is implemented at multiple jurisdictional levels. In the context of Canada and its four most populous provinces, we examine the development of climate policy mixes across jurisdictional levels between 2000 and 2020 and evaluate policy interactions. We develop an inventory of 184 climate policies, and examine each in terms of instrument type, implementation timing, technological specificity, and expected abatement. We evaluate interactions between overlapping policies both within jurisdictional levels (horizontal) and across jurisdictional levels (vertical) for their impact on emissions abatement using a policy coherence analysis framework. We find that subsidies and R&D funding were the most abundant policies (58%), although pricing and flexible regulation are expected to achieve the most abatement. Sub-national jurisdictions have often acted as policy pilots preceding federal policy implementation. We evaluate 356 policy interactions and find 74% are consistent in adding abatement. Less than 8% have a negative impact by reducing abatement, although vertical interactions between federal and provincial policies were more often negative (11%) than horizontal interactions at the federal (<3%) or provincial (<2%) levels. Although the impact of many interactions is unknown (13%), we generate interaction matrices as a foundational roadmap for future research, and for policy-makers to consider potential interactions when designing and assessing policy effectiveness. Key policy insights Climate policy mixes have expanded and diversified over the period 2000–2020 across jurisdictions in Canada. Sub-national jurisdictions have often acted as policy 'pilots' by implementing policy before the adoption of similar national level policy. Climate mitigation policy interactions are predominantly supportive toward achieving additional emissions abatement. Vertical interactions between federal and provincial policy can undermine the additionality of policy effort by sub-national jurisdictions. These findings emphasize the need for better coordination in climate policy mix design between national and sub-national jurisdictions. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions have increased globally 10% in the last decade, but there is a large variation in emissions trajectories by country. Understanding the main drivers of recent changes in GHG emissions is important to guide effective climate action. Using a narrative scoping review of academic literature, we access 648 abstracts and review 30 studies to identify statistically significant independent variables that were associated with GHG emissions nationally and multinationally (i.e., in country groupings) during or overlapping the period 2010--2019. We describe the findings in terms of potential reasons for the positive or negative associations, outline the strength of associations relative to other variables within the same study, and compare the associations to findings in other studies. We find that population, energy consumption, and gross domestic product (GDP) per capita are the most common independent variables associated with increases in GHG emissions, whereas the square of GDP per capita and renewable energy production are associated withGHGreductions.We assign GHG drivers to seven categories: economic, energy, demographic, technology innovation, transportation, policy, and others.We conclude by discussing implications for future research and climate policy. [ABSTRACT FROM AUTHOR]

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Governments at all levels rely on energy-economy models to design climate policy portfolios. Models vary in their purposes and methodologies, yet there is limited research comparing model characteristics and identifying models suitable for specific policy questions. We conduct a web-based survey of energy-economy model users and developers (n = 14) in Canada's public, private, and non-profit sectors, to systematically compare seventeen models against the following characteristics: Technology representations, microeconomic and macroeconomic details, policy representations, treatment of uncertainty, high-resolution spatial and temporal representations, and data transparency. We find that for the most part, models represent technology, micro-, and macroeconomic characteristics according to the typology of bottom-up, top-down, and hybrid models. However, several modelling evolutions have emerged. To varying extents, top-down models can explicitly represent technologies and some bottom-up models incorporate microeconomic (non-financial) characteristics. We find that models differ in the types of policies they can simulate, sometimes underrepresenting performance regulations, government procurement, and research and development programs. All models use at least one method to explore uncertainty, rarely incorporate spatial and temporal representations, and most models lack publicly available methodological documentation. We discuss the implications of our comparative model analysis for climate policy projections and future research. [ABSTRACT FROM AUTHOR]