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The Sustainable Development Goal (SDG) that emphasizes sustainable and affordable energy presents a practical pathway to achieve sustainable growth. Moreover, this goal aligns with SDG 13, which focuses on climate action. Nonetheless, it is important to consider factors such as political and financial risk, as they can influence climate action efforts and the renewable energy sources adoption. Hence, this study broadens the conversation surrounding CO 2 emission reduction and the achievement of Sustainable Development Goals (SDGs). It accomplishes this by investigating the interplay between renewable energy, political risk, financial risk, and CO 2 emissions in Finland spanning from 1990/Q1 to 2021/Q4. Notably, this research distinguishes itself through its exploration of these complex connections, employing a wavelet-based quantile methodology. Unlike traditional quantile regression, which can only reveal connections between variables within each quantile, the wavelet-based quantile approach enables the simultaneous capture of correlations across quantiles and periods. The results show that in the long-term and across all quantiles (0.01–0.99), energy efficiency, specifically gas and oil efficiency, lessens CO 2. In addition, low financial and political risks improve ecological quality by lessening CO 2 across all periods and quantiles (0.01–0.99). The paper outcomes serve as a basis for formulating a policy framework aimed at achieving SDG 7 and SDG 13 in Finland. • We explore the impact of energy efficiency and country risk on CO 2 emissions. • The role of renewable energy and economic growth are also analyzed. • The Time series data of the Finland is used from 1990/Q1 to 2020/Q4. • Various wavelet-based quantile correlation is applied. • Renewable energy, oil and gas efficiency decrease CO 2 emissions in each quantile and across periods. [ABSTRACT FROM AUTHOR]

Interactions between government and industry have the characteristics of leader-follower games. To protect the environment, the government uses regulations and economic instruments to indirectly influence operational and investment decisions in industry. The government needs to calibrate its policies while considering industry's self-interested, cost-minimizing reactions. In this paper, a leader-follower model is developed as a bilevel mixed integer linear program for the selection of carbon emissions mitigation measures. It is assumed that the government sets the emissions reduction target, percentage subsidy for mitigation measures, and economic penalty for excess carbon emissions; in response to these policies, industry then chooses mitigation measures to be implemented. The model is demonstrated with a case study on maritime shipping emissions, where a heuristic solution is identified using a fuzzy interactive optimization algorithm. The solution achieves 11.5% reduction in emissions through the implementation of six mitigation measures, of which only one is subsidized. General implications of these results for decarbonization policy are also discussed. [Display omitted] • A bilevel optimization model for industrial decarbonization portfolios is developed. • Government-industry interaction is modelled as a Stackelberg game. • The model is demonstrated on a maritime carbon emissions reduction case study. • Implications for policy development and engineering decision-making are discussed. [ABSTRACT FROM AUTHOR]

Nowadays, China's economy and energy structure are deeply adjusting to the direction of low-carbonization and non-carbonization with unprecedented efforts. This paper considered carbon emissions and energy endowments, adopted SBM-Undesirable model and spatial Durbin model to calculate the energy efficiency of 30 provinces and municipalities in China from 2015 to 2019 and analyze the direct effect, indirect effect and total effect on energy efficiency of 7 variables. Empirical results show that: Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. The valuable conclusions obtained in this study deepens the insights about the influencing factors of China's energy efficiency under the constraints of carbon emission and energy endowment. Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. [Display omitted] • Energy efficiency has spatial positive correlation and agglomeration characteristics. • Energy consumption structure mainly affects energy efficiency. • Environment Kuznets Curve exists in China. • "Pollution paradise hypothesis" exists in foreign direct investment. • Environmental pollution is transferred to surrounding provinces through resource trades. [ABSTRACT FROM AUTHOR]

Compressed air systems have a high energy transfer capacity. They are widely used in the manufacturing industry due to being clean, dependable, and simple-to-use. On the other hand, these systems are among the most significant energy consumers in the manufacturing sector because they are inefficient with high electricity usage and high CO 2 emissions. As a result, all kinds of the energy efficiency enhancements in these systems promote cleaner production by lowering total energy consumption and CO 2 emissions in factories. In this paper, the energy-saving potential and carbon emissions of Compressed Air Systems are investigated using data from in-situ energy audits. A simple set of equations is proposed to calculate the mass flow rate of air leakage. The sound intensity (dB) obtained from ultrasonic flow measurements were used as the input of the equation set. Furthermore, two new Energy Performance Indicators have been proposed to guide energy audit evaluation and continuous monitoring of the energy efficiency of Compressed Air Systems in industrial facilities. The new evaluation criteria "Specific Compressed Air Savings" and "Specific Leakage Savings" provide a comparison tool to help decision-makers with their compressed air system investment decisions. Using the "Specific Compressed Air Savings" and "Specific Leak Savings" parameters, the analysis method is demonstrated for an example industrial plant. The facility's specific compressed air and leakage savings are calculated as 0.0067 TOE/ton and 0.0035 TOE/ton, respectively. [ABSTRACT FROM AUTHOR]