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In Canada, greenhouse gas (GHG) emissions continue to remain high despite the federal government's commitment to reduce GHG emissions. Environmental policy across Canadian provinces has largely lacked consistency with some provinces implementing targeted policy such as carbon taxes while others have strongly resisted the federal government's attempts to encourage such policy. This study examines the impact of environmental policy on GHG gas emissions across Canadian provinces with policy uniquely measured by public and business sector spending on environmental protection as well as notable province-specific policies. An extended STIRPAT model is specified with the inclusion of proxies for environmental policy using panel data from Canada's ten provinces from 1995 to 2019. The cointegration and the error correction modelling approaches are employed to estimate the non-stationary panel data. A pooled mean group estimation is applied to provide short run and long run coefficients. The findings indicate that although per capita GDP is the main driver of GHG emissions in Canada, environmental policy has a significant mitigating effect, as shown by the negative association between emissions and private and public sector spending on environmental protection in the long run. Furthermore, provinces with targeted policies, such as Ontario's coal phase-out and British Columbia's carbon tax, experienced significant emissions reductions. The theoretical implication is the successful addition of policy variables to the STIRPAT model, providing the model a new application for future research. [Display omitted] • Assess the impact of environmental protection policies on per capita greenhouse gas emissions in Canada. • Utilize public and private expenditures on environmental protection, along with provincial policies. • Extend the STIRPAT model to incorporate environmental protection policies in an empirical model. • Demonstrate a significant negative relationship between environmental protection policies and GHG emissions. • Offer insights with implications for global environmental sustainability efforts. [ABSTRACT FROM AUTHOR]

The present study empirically investigates whether targeted government spending and environmental policies promote green growth, as measured by greenhouse gas productivity. Government spending for pollution abatement (GEPA) represents non-market environmental policies encompassing both enforcement regulations and stakeholder incentives, while policy dummy represents province specific targeted environmental policies. Using panel data from 1995 to 2020 across ten provinces of Canada, an empirical model based on STIRPAT has been developed and estimated, addressing various econometric issues to ensure the robustness and consistency of the results. The findings confirm that both GEPA and targeted environmental policies are crucial determinants in achieving green growth. Additionally, variables such as business sector expenditures for R&D, the share of renewable energy, per capita GDP, and population also contribute to green growth. These results highlight the importance of the stick-and-carrot approach as a key strategy and policy tool for sustainable development. The implications of these findings extend beyond Canada and hold valuable lessons for emerging and developing countries that predominantly rely on command-and-control regulations without adequate support. To effectively address the challenge of achieving green growth, a coordinated approach that combines targeted government spending and environmental policies, supported by innovation and renewable energy exploration, is essential. Overall, this study's findings have significant implications for environmental sustainability on a global scale. [Display omitted] • Examines the effect of targeted government spending and environmental policies on green growth in Canada. • Uses greenhouse gas productivity as an index of green growth. • Estimates the empirical model developed addressing advanced econometric issues related to panel data for 1995–2020. • Controls renewable energy, innovation, per capita income, population. • Have significant implications for environmental sustainability on a global scale. [ABSTRACT FROM AUTHOR]

There is strong evidence for climate change leading to a rise in temperatures and a change in precipitation trends. These environmental changes pose a threat to pavement infrastructure worldwide. Therefore, it is necessary to modify pavement design procedures to consider climate change. In addition, it is necessary to consider suitable pavement materials for future climate. The objective of this study is to develop a framework for selecting an appropriate adaptation strategy to mitigate climate change impact. To fulfill this, the influence of climate change on long-term pavement performance in Canada has been quantified over sixteen Canadian pavement sections located over various provinces in Canada. In addition, the fundamental causes of pavement deterioration due to climate change were determined using ten different climate change models. Various adaptation strategies such as upgrading asphalt binder grade, increasing the thickness of asphaltic concrete layer, increasing the base layer thickness, and using stabilized base layers were analyzed to reduce pavement deterioration and to extend the service life of the pavement. Unlike the other studies, pavement temperatures were determined using Enhanced Integrated Climate Model (EICM) to determine the change in binder grade for the future climate in the adaptation process. The study found that by 2070 all examined locations will require an upgrade in binder grade and the majority will require an upgrade in mixture gradation. Furthermore, the east and west coast will be more vulnerable to climate change and require additional measures in comparison to Central Canada. Newfoundland and Prince Edward Island are the only locations that will need to consider a change in asphalt thickness while British Columbia is the only location eventually requiring a stabilized base. This study emphasizes the necessity of climate change adaptation strategies for Canadian asphaltic concrete pavements. [Display omitted] • Different combinations of adaptation strategies are necessary at each location. • The Canadian coasts generally require more adaptation measures than Central Canada. • By 2070, all Canadian provinces will require an upgrade in asphalt binder. [ABSTRACT FROM AUTHOR]

Life cycle inventory (LCI) data gaps present a crucial challenge in research and development using life cycle assessment (LCA). The present study addresses this challenge by using optimized Artificial Neural Networks (ANNs). ANN's adjustable parameters (i.e. topology and hyperparameters) significantly affect prediction capability. Thus, the optimality of those parameters is of paramount importance. However, performing an optimization on the entire ANN's adjustable parameters is computationally demanding, which may result in an intractable problem. To tackle this challenge, the present study proposes a hybrid approach using heuristics and Genetic Algorithm to systematically design optimal ANNs in a tractable fashion. The proposed approach is then assessed through the prediction of data gaps in the Canadian fuel LCI database, GHGenius (an open-access tool for modeling Canadian fuel pathways). This is achieved using an automation workflow that extracts LCI data from GHGenius at the fuel/province/unit process level. It is found that the resulting optimal ANNs not only are accurate in predicting data to fill CO 2 -eq emissions data gaps for unit processes present in the Canadian fuel life cycles but also possess shallower hidden topologies. These salient results are ascribed to the impacts of the input layer on the optimal network. In particular, input layers comprised of categorical and numerical features lead to enhancement of network prediction and/or shallower hidden topology for optimal ANNs. Taken altogether, the present study proposes, implements, and validates a systematic framework to tractably design optimal ANNs for predicting data to fill data gaps in LCI databases. In addition, this study quantifies average contributions of each unit process present in the Canadian fuel life cycles, including fossil-based and renewable pathways, to total CO 2 -eq emissions, which is of particular interest in cut-off analysis. [Display omitted] • Contributions of unit processes of fuel pathways to net emissions are determined. • A tractable approach is proposed to optimally design ANNs to fill data gaps. • The combination of categorical and numerical attributes improves ANNs' optimality. • Emission data gaps are estimated using optimal Artificial Neural Networks (ANNs). [ABSTRACT FROM AUTHOR]