The low-carbon city pilot is an important policy for promoting sustainable development and addressing climate change. The level of green technological innovation is a significant driving force for China's transition to high-quality development and the realization of carbon peaking and carbon neutrality goals. This essay takes the panel data of 30 provinces in China from 2008 to 2020 as the research sample, regards the number of urban green invention patent applications as a quantifiable indicator of the level of urban green technological innovation, and takes the policy of low-carbon city pilot as a quasi-natural experiment, and uses the difference-in-differences model to test the impact of low-carbon city pilot on the level of urban green technological innovation, and to investigate the mechanism of action within. The main conclusions are as follows: (1) The policy of low-carbon city pilot has an outstanding promotion effect on the level of urban technological innovation. (2) Using the mediating effect to analyze, it is found that the low-carbon city pilot policy can improve the level of urban green technological innovation through the development of green finance.

Carbon emissions trading is an important part of emission reduction policy tools, and manufacturing is the foundation of a strong country. This paper explores the impact of carbon emissions trading pilot on the high-quality development of manufacturing industry by using the double difference method. It is found that carbon emissions trading can significantly promote the high-quality development of manufacturing industry, in which the government's will of ecological environment governance, technological progress and industrial structure rationalization have significant intermediary effects. Heterogeneity analysis reveals that the impact of carbon emissions trading on the high-quality development of the manufacturing industry is most significant in the western region. Accordingly, the study proposes suggestions on how to further improve China's carbon emissions trading market and realize the high-quality development of the manufacturing industry.

Since the Industrial Revolution, the emission of carbon dioxide and other greenhouse gases by human production activities has increased year by year, and the greenhouse effect has also increased. A series of problems, such as global warming, melting of the Antarctic continent, sea level rise and frequent occurrence of extreme climate, have attracted the attention of countries all over the world. As a developing country with the fastest economic growth rate, China's rapid economic growth is inseparable from the contribution of manufacturing industry. As an important engine of China's economic development, manufacturing industry inevitably brings environmental problems and a large number of greenhouse gas emissions while promoting rapid economic development. Therefore, manufacturing has become a major area for China to achieve its carbon emission reduction targets. With the "Made in China" to the world, the export trade of manufacturing industry plays a decisive role in China's total export trade and even the global trade. But whether the huge export demands will affect carbon emissions. Through the empirical study on carbon emissions of China's manufacturing export trade, the paper found that the increase of export demand of manufacturing industry will indeed bring a significant increase in carbon emissions, but also affected by some other factors. Finally, it provides reference for the high-quality development and export of China's manufacturing industry under the background of the target of “dual-carbon”.

The determinants of production-based carbon emission (PCE) have been extensively examined in the literature. However, PCE only accounts for emissions generated within the territory of a country and does not capture emissions embedded in imported goods. The rapid growth in Consumption-based Carbon Emissions (CCE) in Sub-Saharan Africa (SSA), driven by increasing imports and economic activities, highlights the need for a comprehensive understanding of these emissions. This motivates us to examine the impact of Renewable Energy Consumption (REC) on CCE in SSA. We employed a two-step system Generalized Method of Moments (GMM) methodology, utilizing data from 1995 to 2020. The results show a negative effect of REC on CCE, suggesting that increases in renewable energy consumption tend to reduce CCE. In contrast, the positive impact of real GDP and population indicates that economic growth and population expansion tend to bolster carbon emissions. These findings underscore the importance of implementing policies harmonizing economic growth with sustainable energy strategies. They provide valuable insights for informed environmental and economic planning decisions.

This is the first study to examine how Nigerian output is affected by the news-based Economic Policy Uncertainty Index by Tumala et al. (2023) and Climate Uncertainty Index by Salisu et al. (2023). Using ARDL and Granger causality on quarterly data from 2016Q2 to 2024Q1, the findings show that increased economic and climate uncertainties result in decreased output. Additionally, the study reveals that climate uncertainty has a more significant effect on output compared to economic policy uncertainty. The Granger causality indicates one-way causality from climate uncertainty to output, thereby reinforcing the substantial influence of climate uncertainty on output in Nigeria.

This study seeks to investigate how climate change affects actual output in African countries, using greenhouse gas emission as a case study. This paper uses the actual output of Nigeria, Ghana, Liberia, The Gambia, Cabo Verde, and Sierra Leone for the analysis. Climate change is proxied by greenhouse gas emission, which are extracted from the International Monetary Fund (IMF) database, for the period, 1980 to 2022. Descriptive statistics, unit root, and panel System Generalized Method of Moments 1(SGMM1) are estimated, and the result shows that agricultural greenhouse gas emission reduces the output of the selected African Countries, while other greenhouse gases such as building and other sector’s greenhouse gas emission, energy industries greenhouse gas emissions, mineral industry greenhouse gas emission and road transport greenhouse gas emission increase output. For actual output to increase, the paper suggests policy remedies such as sustainable farming practices and adoption of climate-smart technologies.

This paper evaluates the use of macro-level insurance to finance post-disaster recovery and reinstatement by investigating the case of the National Disaster Insurance policy implemented by Sri Lanka. The national scheme provided cover for all properties in the country against hazards such as flooding and provided compensation for those affected. Analysis of secondary data obtained from the organisations that managed the scheme showed that the scheme has delivered a much higher return compared to the total insurance premium paid, suggesting that the scheme has delivered a net positive benefit compared to the cost of the premium and can be considered a viable option. However, the existing secondary data did not reveal the values of other costs and indirect benefits associated with the scheme to compute a meaningful benefit-to-cost ratio. Further rigorous, evidence-based cost-benefit analysis is required to assess the cost-effectiveness of a scheme of this nature. A cost-benefit analysis approach based on an analytical hierarchy process is proposed as a possible solution to assess the cost-effectiveness of the scheme, which could be used by government organisations as an alternative, where analytical and research resources may be limited, to evaluate a range of disaster recovery financing options using stakeholder opinion.

The clean energy revolution is a global concern. Cross-border collaboration is crucial for sharing knowledge, pooling resources, and tackling complex challenges on a global scale. International partnerships can accelerate innovation by drawing on diverse knowledge and experience from different regions. Access to capital is a key driver of innovation and entrepreneurship in clean energy. Institutional investors and financial institutions increasingly recognize the potential for high returns from the clean energy sector. This research aimed to understand whether "dirty" energies, such as the Brent Crude Spot, WTI, FTSE 350 Oil, Gas & Coal, EURO STOXX Oil & Gas, influence the formation of sustainable energy prices, namely Geothermal Index, Solar Energy Index, NASDAQ OMX Bio Clean Fuels Index, Wind Energy Index, WilderHill Clean Energy Index, during the 2020 Covid-19 pandemic and the Russian invasion of Ukraine in 2022. When comparing the two sub-periods, the results show that the level of autocorrelation in price formation has increased, i.e., the mean rhoDCCA went from 32 to 45, the weak correlation coefficients without trend decreased from 30 to 19, and the anti-persistence has also decreased from 8 to 4. The strong rhoDCCA increased from 2 to 4; during the Tranquil period, the FTSE 350 / EURO STOXX Oil index pairs had a rhoDCCA of 0.76. While in the Stress subperiod, the NASDAQ OMX Bio / Solar Energy pairs had a slope of 0.70, and the FTSE 350 / EURO STOXX Oil indices had a rhoDCCA of 0.91. Evidence shows a notable dissociation between fossil energy prices and sustainable energy sources. This dissociation is characterized by various degrees of influence between fossil energy prices and sustainable energy indices, from low to moderate. This dissociation between fossil energy prices and sustainable energy prices suggests that investments in sustainable energy can offer diversification opportunities.