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Greenhouse gas (GHG) emissions are currently at the crux of political, environmental, technological, and cultural discussions due to climate change. A drastic reduction of GHG emissions is needed in order to mitigate potentially catastrophic climate change impacts. Thus, thoroughly understanding emission sources is imperative. A disaggregated analysis of Canada’s future GHG emission projections has not yet been conducted. The objectives in this paper are to assess disaggregated GHG emissions in Canada for the years 2014, 2030, and 2050, and analyze the results through Sankey diagrams. Emissions are calculated using a bottom-up multi-regional accounting-based Long-range Energy Alternative Planning systems model. Each major economic sector in Canada is analyzed including the electricity generation, residential, commercial and institutional, industrial, transportation, and agriculture sectors. The emissions released in these sectors are traced to the resources and end-uses responsible. Results are presented for Canada and for provinces individually. GHG emissions contained in exported resources are evaluated. Results show that Canada’s business-as-usual GHG emissions will grow from 732 million tonnes in 2014 to 780 and 798 million tonnes in 2030 and 2050, respectively. Canada exports more emissions contained in resources than it emits. Per capita emissions intensity will fall by 14% between 2014 and 2050. Results are compared to climate targets and key areas of GHG mitigation potential are identified. Alberta’s oil and gas sector and Ontario’s transportation sector are the two single largest sectoral sources of emissions by 2050. This research can help policy makers, innovators, and the public better understand GHG emissions, which can lead to more effective GHG mitigation. [ABSTRACT FROM AUTHOR]

The paper explains the findings of the MC3 Project (Meeting the Climate Change Challenge). This project brought together over 100 researchers, practitioners, civil-society leaders, and policy-makers, led by researchers from Royal Roads University, Simon Fraser University, and the University of British Columbia, with 12 major research partners from the public and private sectors, including the Union of British Columbia municipalities. Researchers conducted a detailed evaluation of 11 leading, yet different, municipalities across the province to identify the leading innovators and innovations on climate action. The case studies revealed the following key drivers of innovation, in order of prominence: the legislative and policy framework, supported by provincially led incentives and tools, access to partnership funding and intermediary support, and framing the issue as critically important. [ABSTRACT FROM AUTHOR]

The objective of this paper is to assess the impact of proposed Canadian climate change mitigation policies (discounting and carbon pricing) on cost, energy use, and greenhouse gas (GHG) emissions in the single-objective design/expansion optimization of the Amherstview water distribution system in Amherstview, Ontario, Canada. The single-objective optimization problem is solved with the elitist genetic algorithm (EGA). The optimization approach is used in a parametric analysis to examine the impact of discounting and carbon pricing on GHG reductions for cement-mortar ductile iron and polyvinyl chloride pipe materials. Preliminary results indicate that the discount rate and carbon prices investigated had no significant influence on energy use and GHG mass in the Amherstview system and did not meet the emission-reduction targets set by the Canadian government. This result was attributed to a number of factors, including adequately installed hydraulic capacity in the Amherstview system, the use of a time-declining GHG emission intensity factor, and the scope of the expansion problem. [ABSTRACT FROM AUTHOR]

Summary: Uncertainty estimation of climate change impacts has been given a lot of attention in the recent literature. It is generally assumed that the major sources of uncertainty are linked to General Circulation Models (GCMs) and Greenhouse Gases Emissions Scenarios (GGES). However, other sources of uncertainty such as the choice of a downscaling method have been given less attention. This paper focuses on this issue by comparing six downscaling methods to investigate the uncertainties in quantifying the impacts of climate change on the hydrology of a Canadian (Quebec province) river basin. The downscaling methods regroup dynamical and statistical approaches, including the change factor method and a weather generator-based approach. Future (2070–2099, 2085 horizon) hydrological regimes simulated with a hydrological model are compared to the reference period (1970–1999) using the average hydrograph, annual mean discharge, peak discharge and time to peak discharge as criteria. The results show that all downscaling methods suggest temperature increases over the basin for the 2085 horizon. The regression-based statistical methods predict a larger increase in autumn and winter temperatures. Predicted changes in precipitation are not as unequivocal as those of temperatures, they vary depending on the downscaling methods and seasons. There is a general increase in winter discharge (November–April) while decreases in summer discharge are predicted by most methods. Consistently with the large predicted increases in autumn and winter temperature, regression-based statistical methods show severe increases in winter flows and considerable reductions in peak discharge. Across all variables, a large uncertainty envelope was found to be associated with the choice of a downscaling method. This envelope was compared to the envelope originating from the choice of 28 climate change projections from a combination of seven GCMs and three GGES. Both uncertainty envelopes were similar, although the latter was slightly larger. The regression-based statistical downscaling methods contributed significantly to the uncertainty envelope. Overall, results indicate that climate change impact studies based on only one downscaling method should be interpreted with caution. [Copyright &y& Elsevier]