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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.

Highly efficient nanocatalysts which can selectively decompose hydrous hydrazine for hydrogen production are introduced.

In this work we assess the pathways for environmental improvement by the coal utilization industry for power generation in Australia. In terms of resources, our findings show that coal is a long term resource of concern as coal reserves are likely to last for the next 500 years or more. However, our analysis indicates that evaporation losses of water in power generation will approach 1000 Gl (gigalitres) per year, equivalent to a consumption of half of the Australian residential population. As Australia is the second driest continent on earth, water consumption by power generators is a resource of immediate concern with regards to sustainability. We also show that coal will continue to play a major role in energy generation in Australia and, hence, there is a need to employ new technologies that can minimize environmental impacts. The major technologies to reduce impacts to air, water and soils are addressed. Of major interest, there is a major potential for developing sequestration processes in Australia, in particular by enhanced coal bed methane (ECBM) recovery at the Bowen Basin, South Sydney Basin and Gunnedah Basin. Having said that, CO2 capture technologies require further development to support any sequestration processes in order to comply with the Kyoto Protocol. Current power generation cycles are thermodynamic limited, with 35-40% efficiencies. To move to a high efficiency cycle, it is required to change technologies of which integrated gasification combined cycle plus fuel cell is the most promising, with efficiencies expected to reach 60-65%. However, risks of moving towards an unproven technology means that power generators are likely to continue to use pulverized fuel technologies, aiming at incremental efficiency improvements (business as usual). As a big picture pathway, power generators are likely to play an increasing role in regional development; in particular EcoParks and reclaiming saline water for treatment as pressures to access fresh water supplies will significantly increase.

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.

Abstract This paper is based on dynamic optimization methodology to investigate the economic energy efficiency issues in developing countries. The paper introduces some definitions about energy efficiency both in economics and physics, and establishes a quantitative way for measuring the economic energy efficiency. The linkage between economic energy efficiency, energy consumption and other macroeconomic variables is demonstrated primarily. Using the methodology of dynamic optimization, a maximum problem of economic energy efficiency over time, which is subjected to the extended Solow growth model and instantaneous investment rate, is modelled. In this model, the energy consumption is set as a control variable and the capital is regarded as a state variable. The analytic solutions can be derived and the diagrammatic analysis provides saddle-point equilibrium. A numerical simulation based on China is also presented; meanwhile, the optimal paths of investment and energy consumption can be drawn. The dynamic optimization encourages governments in developing countries to pursue higher economic energy efficiency by controlling the energy consumption and regulating the investment state as it can conserve energy without influencing the achievement of steady state in terms of Solow model. If that, a sustainable development will be achieved.

Abstract To guarantee the space heating in the heating season, conventional combined heat and power (CHP) plants operate in a heat-controlled operation mode, resulting in restricted peak-shaving ability (PSA). To improve the CHP plant’s PSA, a novel solar aided CHP (SA-CHP) system is proposed and simulated in this paper. In the new system, solar heat could be flexibly used to generate power or to supply heat according to the heating and power demands, thereby realizing the heat-power decoupling. A set of models for the SA-CHP system is developed and validated. The PSA, the standard coal consumption (SCC) and the techno-economic performances of a 330 MWe SA-CHP system are comprehensively analyzed in this paper. The results show that the SA-CHP system can significantly improve (up to double) the PSA compared with the CHP plant under the same rated heating power. The feasible operation region area of the SA-CHP system is 74.7% larger than that of the CHP plant. The annual SCC of the SA-CHP system are 17378.23 t less than that of the CHP plant. The net annual revenue of the SA-CHP system is $2.24 M. Besides, techno-economic performances of SA-CHP systems with two different heat storage systems are compared.

Abstract The urge to increase renewable energy penetration into the power supply mix has been frequently highlighted in response to climate change. South Korea was analyzed as a case study for which the government has shown motivation to increase renewable energy penetration. Herein, a hybrid renewable energy system (HRES) including solar and wind energies were selected due to their relatively stable and mature technology. In addition, Power-to-X has been incorporated to cover other renewable energy options such as hydrogen and synthetic natural gas (SNG). Therefore, an approach of forecasting the weather characteristics and demand loading over a relatively long timeframe was implemented via deep learning techniques (LSTM and GRU) and statistical approaches (Fbprophet and SARIMA), respectively. A deployment strategy incorporating HRES and Power-to-X is then proposed in correspondence to the forecasted results of the 15 regions considered in this study. An extension of this, the reliability of the designed system is further assessed based on the probability of the demand losses with the aid of Monte-Carlo simulation. With the proposed deployment strategy, a total annual cost of 9.88 × 1011 $/year and a greenhouse gas reduction of 1.24 × 106 tons/year are expected for a 35% renewable energy penetration. However, only SNG shows relatively competitive cost (at 23.20 $/m3 SNG), whereas the average costs of electricity (0.133 $/kWh) and hydrogen (7.784 $/kg H2) across the regions are yet to be competitive compared to the current market prices. Nonetheless, the priority of deployment across regions has been identified via TOPSIS.