• Energy Research
• Closed Access close
• 12. Responsible consumption close
• PK close
• BG close

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

Developing a low-carbon economy is the only way for countries to achieve sustainable development. Carbon emission reduction policies and low-carbon technology (LCT) innovation play key roles in developing low-carbon economy. Under government reward and punishment regulations, based on the bilateral matching and evolutionary theories, this paper constructs an evolution model consisting of a manufacturer investing LCT and a supplier offering LCT to analyze multi-phase LCT investment strategies. Firstly, the profit optimization model of a green supply chain is constructed from the perspectives of centralized-matching (CM), decentralized-matching (DM), and mismatching (MM), and the spatial information internal evolution law of multi-phase LCT investment is described by the Markov chain. Then, a bilateral matching algorithm is proposed to solve the equilibrium solutions, and the evolution process of the three modes is analyzed by numerical simulation. Finally, based on the product green degree, we analyze the impact of subsidies and taxes on investment-production decisions. Analytical results show that the matching mechanism proposed in this paper can help supply chain firms to obtain stable matching and has a significant effect on the realization of "triple wins" of society, economy, and environment. The investment utility of CM is higher than that of DM and MM. Manufacturers are inclined to adopt LCT, and the investment level tends to be stable over time. Government reward and punishment regulations are helpful to motivate supply chain firms to invest in LCT, and the synergistic effect of subsidies and taxes is better than that of a single policy.

Abstract We present a production-theoretical approach to decomposing the change of aggregate CO2 emissions over time using the Shephard input distance functions and the environmental data envelopment analysis (DEA) technology in production theory. Application of the proposed approach requires only some aggregate data and the change of aggregate CO2 emissions can be decomposed into contributions from seven factors. These contributions are obtained through solving a series of DEA models. The key features of the proposed approach are the use of panel data to estimate the production frontier and the inclusion of several production technology related components. Using the proposed approach, we present two application studies on decomposing the CO2 emissions for world regions and OECD countries. A comparison between the proposed approach and other decomposition analysis methods is also presented.

As an effective emission reduction approach, CO2 capture and storage (CCS) combined with enhanced water recovery (EWR) technology can not only reduce CO2 emissions, but can also recover deep saline water resources to relieve pressure on regional water resources, and can ensure the energy supply and both social and economic development. However, the environmental benefits and application costs of CCS-EWR are uncertain, and are determined by the technology level, geological conditions, and other physical factors. In this study, an optimal source-sink matching model and a techno-economic assessment model were developed to evaluate the contributions of CCS-EWR to carbon emission reduction and the increase of the water supply by considering various uncertain factors, as well as the corresponding costs. In addition, the Yellow River Basin (YRB) in China was selected as the research region because, while there are abundant coal-fired power plants (CFPPs) in the YRB, the water resources are scarce. The results revealed the following. (1) The maximum CO2 capture capacity of the 236 CFPPs in the YRB is about 738.77 Mt/a, and nearly 13.14 Gt of fresh water could be provided until the 236 CFPPs in the YRB retire, which can partially relieve the pressure on the supply of water resources. (2) With the consideration of the CCS-EWR benefits, the average cost of the 236 CFPPs in the YRB in their residual lifetime to reduce their CO2 emissions by 90% will be no more than 180 CNY/t. (3) The incentive effect of the increase of the industrial water price on the profits of CCS-EWR projects is not significant. CCS-EWR technology has better application prospects in China under the dual constraints of carbon-neutral targets and water shortages, and more policy support is required for its deployment.

A key factor in social development and sustainable urban expansion is the establishment of sustainable and affordable transport systems. This study aims to investigate the impact of transport infrastructure investment on environmental degradation and economic growth and to test the validity of the EKC hypothesis in China, India, Russia, and Japan over the period 1995-2020. The results show that GDP has a significant positive effect, and GDP2 and GDP3 have significant adverse effects on environmental degradation, respectively. These results confirm the validity of the inverted U-shaped EKC hypothesis in selected emerging Asian economies. Rail infrastructure investment has significant adverse effects, while road infrastructure investment and aviation infrastructure investment have significant positive effects on environmental degradation. Likewise, the impact of investment in transport infrastructure system (roads, rail, and aviation) on economic growth is positive and statistically significant. Country-level estimates confirm the validity of the inverted U-shaped EKC hypothesis in China, India, and Russia, while the N-shaped EKC is only valid in Japan. Investments in rail infrastructure based on modern rail systems that run on electricity are believed to be less polluting in the transport mix, help create sustainable and safe transport systems, and reduce emissions at the urban and intercity levels in emerging Asian countries. In addition, the growing impact of free trade on environmental pollution should be strengthened to harmonize the strict enforcement of environmental conditions dominated by trade agreements.

As a financial innovation model to promote sustainable economic development, carbon finance promotes green and inclusive economic development by reshaping the financial system. As a big energy consumer, China has been committed to the green transformation of energy structure, and carbon finance has been regarded as an important tool to support carbon emission reduction. This paper divides carbon finance from three levels, financial macro, environmental governance, and technological development, and selects 17 indexes to measure the development level of carbon finance in China. Time series regression model and the entropy weight method (EWM) are used to analyze the impact of carbon finance on China's energy consumption structure. The empirical results show that carbon finance plays a positive role in promoting China's energy consumption structure, and developing carbon finance is conducive to the use of clean energy and the optimization of energy consumption structure in China; carbon finance can further optimize China's energy consumption structure by investing capital, resources, and technology in industries related to promoting clean energy consumption. Therefore, China should continue to develop carbon finance and promote the establishment of a unified national carbon trading market; at the same time, China should use the CCER trading mechanism to promote the development of renewable energy and enhance the endogenous driving force of energy transformation by promoting technological progress.

Abstract Global environmental change is driven by food production. Biogas from food waste is a better source of clean energy. Ghana’s energy strategy targets a 10% increase in renewable energy and modern biomass in the national electricity generation mix. Studies on the assessment of electricity generation potential and economic feasibility of biogas to electricity projects in Ghana’s major cities are scarcely available. This study assesses the electricity generation potential of biogas from food waste through anaerobic digestion technology. The municipal solid waste generation potential of Accra and Kumasi was estimated from 2020 to 2039. The potential theoretical methane yield from food waste was calculated using Buswell’s equation. The study analyzed anaerobic digestion projects’ economic feasibility using the total life cycle cost, net present value, investment payback period, levelized cost of energy, and internal rate of return methods. A sensitivity analysis based on two scenarios (optimistic and pessimistic) was performed to analyze the influence of changes in the composition of food waste, per capita waste generation rate, population growth rate, per capita GDP growth rate, discount rate, capacity factor, electricity generation efficiency, waste collection efficiency, and methane production potential on the economic feasibility of the projects. The main findings indicate that the amount of waste generation in Accra during the project life cycle is 899,000 t/y to 3,359,000 t/y, while that of Kumasi is 915,000 t/y to 3,159,000 t/y. The power generation potential of the project in Accra ranges from 80.43 to 300.49 GWh/y, and in Kumasi ranges from 60.63 to 209.31 GWh/y. Economically, the project is feasible in Accra and Kumasi. The net present value of the project in Accra and Kumasi is $217,800,000 and $156,100,000. The sensitivity analysis shows that the project is infeasible in all the cities with a discount rate exceeding 20%. When the discount rate exceeds 20%, the project becomes highly infeasible in Accra compared to Kumasi. This study will offer itself as scientific guidance for investment in biogas to electricity projects in Ghana’s cities.

Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.

Abstract The transportation and electricity sectors are in the midst of leading changes in the endeavor to mitigate climate change and air pollution issues. In future years, traditional fossil-fuelled vehicles are estimated to be substituted with electric vehicles (EVs), resulting in higher electricity demand from the transport sector. Meanwhile, the electricity sector is transforming due to policies to adopt renewable energy resources such as solar, wind, and hydropower in the future. However, there are still societal concerns regarding the environmental benefits of these vehicle technologies and how new energy options and vehicles benefit the 2050 HK Carbon Neutral Plan. To address these concerns, this paper aims to analyse the environmental burdens of current (2019) and future (2050) vehicle scenarios in Hong Kong using a life cycle assessment (LCA). The LCA was performed for internal combustion vehicles (ICEVs) fuelled by diesel and petrol and plug-in hybrid vehicles (PHEVs) and EVs with future electricity energy mix scenarios (2025–2050). The results revealed that EVs with the 2050 HK electricity mix are an optimal choice and have the least environmental impact in selected impact categories. Additionally, PHEV with diesel were the second most optimal choice to reduce the environmental impacts in current scenarios. In contrast, the petrol ICEV has the utmost environmental impacts in all damage category results. The study shows that clean energy could decrease the environmental impact and mitigate climate change in Hong Kong.