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Due to the record-breaking wildfires that occurred in Canada in 2023, unprecedented quantities of air pollutants and greenhouse gases were released into the atmosphere. The wildfires had emitted more than 1.3 Pg CO2 and 0.14 Pg CO2 equivalent of other greenhouse gases (GHG) including CH4 and N2O as of 31 August. The wildfire-related GHG emissions constituted more than doubled Canada's planned cumulative anthropogenic emissions reductions in 10 years, which represents a significant challenge to climate mitigation efforts. The model simulations showed that the Canadian wildfires impacted not only the local air quality but also that of most areas in the northern hemisphere due to long-range transport, causing severe PM2.5 pollution in the northeastern United States and increasing daily mean PM2.5 concentration in northwestern China by up to 2 µg m−3. The observed maximum daily mean PM2.5 concentration in New York City reached 148.3 µg m−3, which was their worst air quality in more than 50 years, nearly 10 times that of the air quality guideline (i.e., 15 µg m−3) issued by the World Health Organization (WHO). Aside from the direct emissions from forest fires, the peat fires beneath the surface might smolder for several months or even longer and release substantial amounts of CO2. The substantial amounts of greenhouse gases from forest and peat fires might contribute to the positive feedback to the climate, potentially accelerating global warming. To better understand the comprehensive environmental effects of wildfires and their interactions with the climate system, more detailed research based on advanced observations and Earth System Models is essential. [ABSTRACT FROM AUTHOR]

Canada is recognized as a global leader in sustainable forest management. Canadian forests and the forest sector remain vital pillars of the Canadian economy and home to many rural and remote communities. However, climate change is an existential threat to the sustainability of forests and forest-dependent communities. While both direct and indirect threats posed by climate change to Canada's forest sector are now well understood, our understanding of specific forest practices that have emerged from the body of science to mitigate and adapt to climate change impacts is not well documented. Through a review of the scientific and grey literature, this study expands our knowledge and operational gaps associated with implementing climate change adaptation and mitigation practices in Canadian forests. The study found a dearth of literature specifically dedicated to reporting on the type of forest practices currently in use across Canada to address mitigation and adaptation. Most reports or studies were published in 2019 or later, with federal and provincial governments being the dominant actors in reporting and monitoring, research, and funding. Across the 15 terrestrial ecozones in Canada, forest practices linked to climate change were reported in 12 ecozones, with most practices reported in the Montane Cordillera located in western Canada. Common forest practices reported include fuel management, assisted migration, enhanced silvicultural activities, and carbon offset projects. We conclude that climate change adaptation/mitigation practices in Canada are in their early stages of implementation. Many practices remain in experimental stages (e.g., genetic trials) or are implemented at a relatively small scale in Canada (e.g., climate-based seed transfer and carbon reserves). The literature suggests that the most mainstream practices associated with climate change mitigation in Canada include tree planting for carbon sequestration and the designation of protected areas to enhance ecosystem resilience. We conclude that despite increasing reports linking climate change benefits with reported forest practices, the reporting in the scientific literature is scarce, poorly reported, and often not grounded in credible evidence. [ABSTRACT FROM AUTHOR]

With its northern location, the exposure and vulnerability of Canada's forest ecosystems to climate change impacts are all too glaring. While there is now an extensive body of literature describing expected climate change impacts and potential responses, studies characterizing the implementation of adaptation and mitigation practices in forest management remain rare in the Canadian forest sector. Using a systematic literature review, we examined reports on forest management practices implemented in response to climate change, specifically focusing on governance and institutional arrangements that either support or limit climate change adaptation and mitigation responses. Our literature sample size of 24 documents suggests that the body of literature reporting on adaptation and mitigation practices in forest management is scarce. Governments remain the dominant actors providing funding and leading the implementation and reporting of climate change adaptation practices, primarily in response to national or international climate change commitments. Forest practices such as enhanced silviculture, assisted migration, and nature-based solutions were the most frequently reported. However, given the scarcity of literature, it is difficult to conclude the scope of climate change adaptation practice uptake in Canada. Barriers such as lack of information/data, inter-jurisdictional knowledge transfer, policy conflicts, forest tenure models, technical capacity gaps, and economic barriers to adaptation need to be overcome to strengthen climate change response in forest management. Better coordination of reporting at the provincial and national levels and improved information flows between private sector organizations and governments are needed. [ABSTRACT FROM AUTHOR]

Energy transitions in Indigenous, Northern and remote communities in Canada promise benefits that go beyond reliable, clean and affordable energy services. The Federal and Provincial governments have committed funding to get remote communities off diesel, acknowledging energy transitions' global and local benefits. Besides climate change mitigation, other benefits, including job creation, income generation, community ownership and local economic growth, are fundamental components of the value proposition of renewable energy projects. However, despite the promises, little evidence of the impacts of renewable energy on communities' local conditions exists. This article looks at the relationship between renewable energy projects and community well-being in Canada. We construct a panel of Indigenous communities and well-being levels using Census data and information about renewable energy projects for the period 1981–2016. The findings suggest that renewable energy is associated with higher levels of well-being. Concretely, having access to renewable energy increases overall well-being by 1 to 5 points on the 0–100 well-being scale, depending on the component of the well-being index considered in the analysis. • Renewable energy and community wellbeing is an essential relationship for successful energy transitions. • The size of the renewable energy projects is strongly associated with higher community wellbeing. • Communities that hold majority ownership of renewable energy projects exhibit higher wellbeing levels. • Solar and wind energy projects are associated with higher wellbeing levels, whereas hydropower is associated with lower ones. [ABSTRACT FROM AUTHOR]

• Innovate a BaPMI method for macro-scale distributed hydrologic modeling. • Apply it to a typical large cold-region watershed, Athabasca River Basin in Canada. • Verify feasibility & advantages in characterizing macro-scale cold-region hydrology. • Quantify parametric & hyperparametric sensitivities for facilitating its applications. • Reveal variabilities of climate-driven cross-scale uppermost hydro-variational effects. At macroscales (e.g., large river basins, nations, continents, or the globe), hydro-hazard mitigation under climate change requires accurate, applicable hydrologic models, especially over cold regions of complicated hydroclimatic relations. As an effort to address such a challenge, we innovate a macroscale distributed hydro-modeling method, Bayesian principal-monotonicity inference (BaPMI), based on climate classification, representative-grids selection, statistical hydrology, surrogates-based Bayesian optimization, and variance-based sensitivity analyses. The method is applied to a typical large cold-region watershed, i.e., Athabasca River Basin in Canada, and reveals a series of findings such as the following representatives. BaPMI shows promising skills in quantitatively characterizing macroscale cold-region hydrology under overall impacts of heterogeneous climates. Bayesian optimization of which hyperparameters are insensitive decreases hydro-modeling computational time by up to 96.3% and, together with climate classification, largely enhances BaPMI applicability while ensuring modeling accuracies. Individual BaPMI hydro-model parameters can explain over ¾ of the variation of hydro-modeling accuracies and, due to their interaction, joint calibration is required for avoiding underestimation of the impacts. Climatic conditions dominating cross-scale uppermost hydrologic variations consist of night temperature (40%), day temperature (38%), and precipitation (22%) for all catchments; all river flows along the mainstem are associated with upstream climatic events such as glacier melts. Climatic impacts decline from upstream to downstream and from summer, spring, winter to autumn; this may relate to tempo-spatial heterogeneity of soil, vegetation, geology, human interference and other non-climatic factors. Without this study, macroscale distributed hydrologic modeling would lack one advanced method (i.e., BaPMI) that can immunize against effects of data uncertainty, subjective judgement and climatic collinearity, adapt to complicated hydroclimatic relations and diverse hydro-variable(s) distributions, reveal cross-scale uppermost hydrologic variations and, through inexpensive computations, enhance hydro-modeling accuracies to avoid climatic-impact underestimation. The findings of this study could facilitate BaPMI applications and advance macroscale (cold-region) hydrology. [ABSTRACT FROM AUTHOR]

The deep decarbonization of the power systems is pivotal to the efforts of global energy transition and climate mitigation. The small modular reactor (SMR) is a decarbonized, reliable and secure generating technology that can bring new possibilities for global power-sector transition. However, such a transition involves a variety of complexities even beyond conventional systems. We comprehensively explore the SMR deployment and the decarbonization pathway in a number of diversified power and jurisdictional systems under various complexities associated with multiple variables, objectives, criteria and constraints that have dynamic and interactive relationships. This effort is based on the development of an SMR-embedded multi-region power system management model (SMPM). Using Canada as an example, here we show that SMRs would play different roles in diversified power systems, particularly for fossil-fuel dependent, highly variable renewable energy-penetrated and off-grid. The introduction of SMRs to Canada would result in up to 71% (/48%) emission reduction from 2005 (/2018) level in the country by 2045. Our results would help show the significance of SMRs for supporting the global energy transition. [Display omitted] • An SMPM model is developed to analyze low-carbon power system transition in Canada. • Multiple complexities and uncertainties in power systems are reflected. • SMR development issue is investigated within a power-system optimization framework. • The regional development of Canada is analyzed by a holistic optimization method. • GHG emissions from Canada's power sector would be 48% lower in 2045 than in 2018. [ABSTRACT FROM AUTHOR]

The success and rate of forest regeneration has consequences for sustainable forest management, climate change mitigation, and biodiversity, among others. Systematically monitoring forest regeneration over large and often remote areas is challenging. Remotely sensed data and associated analytical approaches have demonstrated consistent and transparent options for spatially-explicit characterization of vegetation return following disturbance. Moreover, time series of satellite imagery enable the establishment of spatially meaningful recovery baselines that can provide a benchmark for identifying areas that are either under- or over-performing relative to those baselines. This information allows for the investigation and/or prioritization of areas requiring some form of management intervention, including guiding tree planting initiatives. In this research, we assess recovery following stand replacing disturbances for the 650 Mha forested ecosystems of Canada for the period 1985–2017, wherein ~51 Mha of Canada's forested ecosystems were impacted by wildfire, and ~ 21 Mha were impacted by harvesting. For quantification of forest recovery, we implement the Years to Recovery or Y2R metric using Landsat time series data based on the Normalized Burn Ratio (NBR) to relate the number of years required for a pixel to return to 80% of its pre-disturbance NBR value. By the end of the analyzed period, 76% of areas impacted by wildfire were considered spectrally recovered compared to 93% of harvested areas. On average, we found that harvest areas had more rapid spectral recovery (mean Y2R = 6.1 years) than wildfire (mean Y2R = 10.6 years) and importantly, that Y2R varied by ecozone, disturbance type, pre-disturbance land cover, and latitude. We used airborne laser scanning data to assess whether pixels that were considered spectrally recovered had attained United Nations Food and Agricultural Organization benchmarks of canopy height (>5 m) and cover (>10%) across four geographic regions representing different forest types. Overall, 87% and 97% of recovered pixels sampled in harvests and wildfires, respectively, had achieved at least one of the benchmarks, with benchmarks of height more readily achieved than benchmarks of cover. By analyzing spatial patterns of Y2R, we identified areas that had significant positive or negative spatial clustering in their rate of spectral recovery. Approximately 3.5–4% of areas disturbed by wildfire or harvest had significant positive spatial clustering, indicative of slower spectral recovery rates; these areas were also less likely to have attained benchmarks of height and cover. Conversely, we identified significant negative spatial clustering for 0.94% of areas recovering from harvest and 1.93% of areas recovering from wildfire, indicative of spectral recovery that was more rapid than the ecozonal baseline. Herein, we demonstrated that remote sensing can provide spatial intelligence on the nature of disturbance-recovery dynamics in forested ecosystems over large areas and moreover, can retrospectively quantify and characterize historic forest recovery trends within the past three decades that have implications for forest management, climate change mitigation, and restoration initiatives in the near term. • Landsat time series monitored forest disturbance and recovery for 32 years across 650 Mha. • Harvests spectrally recovered more rapidly (6.1 years) than wildfire (10.6 years). • Lidar-derived benchmarks of canopy cover (>10%) and height (>5 m) used for validation. • 87% and 97% of recovered harvest and wildfire samples achieved one of the benchmarks. • Nationally, 3.5%–4% of wildfire and harvest areas had slower than expected recovery. [ABSTRACT FROM AUTHOR]