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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.

Abstract Energy poverty has evolved as an important issue of research from academic and policy perspectives during the last two decades. The energy poverty estimates exhibit widespread variations across regions, methodologies and datasets, making the task of energy and development policies challenging. The variations in energy poverty estimates necessitate a systematic and rigorous analysis of these empirical studies to obtain a true measure of energy poverty. The present study conducts a meta-analysis of 30 studies and 103 estimates of energy poverty. On average, 71.1 percent of the population in the overall sample studies has been identified as energy poor. High I-square statistic values suggest heterogeneity bias in the sample studies; therefore, analysis at the subgroup level has been conducted. Meta-regression analysis of overall sample and subgroups has identified type of methodology, citations, impact factor of the journal, regional dummies, average key crude oil price and gross domestic product as significant factors that explain heterogeneity in the energy poverty effect sizes. We recommend inclusion of local and regional factors in assessment of energy poverty for developing a uniform methodology to assess energy poverty across developing economies.

Present climate change consists of global warming that is caused by the emission of greenhouse gases, generally carbon dioxide. The study examines the pollution haven, pollution halo, and environmental Kuznets curve for a number of Asian countries during the period of 1985 to 2020. Outcomes suggest that urbanization, gross domestic product per capita, energy consumption, and foreign direct investment inflow have positive effects, while gross domestic product square, foreign direct investment square, and tourism have negative effects on emissions of carbon dioxide. Furthermore, findings support the validity of the environmental Kuznets curve, pollution haven, and pollution halo hypothesis for the selected Asian countries. We also find robust results of rationality of the environmental Kuznets curve hypothesis for Pakistan, Bangladesh, India, China, Indonesia, Korea, Japan, Malaysia, Vietnam, and Singapore; of pollution haven hypothesis for Bangladesh, China, Indonesia, Japan, Pakistan, and Singapore; and of pollution halo hypothesis for Bangladesh, China, Indonesia, Japan, Pakistan, and Singapore.

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.

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.

The declaration of 2014-2024 as the Decade of Sustainable Energy for All has catalyzed actions towards achieving universal electricity access. The high costs of building electric infrastructure are a major impediment to improved access, making stand-alone photovoltaic (PV) systems an attractive solution in remote areas. Here, we analyze the cost-effective electrification solution for Kenya comparing grid extension with stand-alone PV systems. We use micro-data from a national household survey to estimate electricity demand for households that are within reach of electricity infrastructure and to predict latent demand in unconnected households. These regional demands are used in a spatially explicit supply model to seek for a least cost electrification solution. Our results suggest that decentralized PV systems can make an important contribution in areas, with low demand and high connection costs. We find that up to 17% of the population can be reached cost-effectively by off-grid PV systems till 2020.

Hydrogen is expected to play a significant role in the future energy system. A key enabler to a hydrogen-including economy will be the development and deployment of processes that can produce hydrogen whilst satisfying the criteria for sustainability, i.e. economic competitiveness, environmental protection and security of energy supply. This paper evaluates selected hydrogen production processes based on natural gas steam reforming, coal and biomass gasification and water electrolysis. These options are expected to play a significant role in the short to medium term. Industrial large-scale processes, using natural gas and coal, will constitute the most important routes. However, increasing prices for natural gas are likely to make coal gasification more competitive. Biomass gasification could become important if present technological barriers are overcome. Electrolytic hydrogen, however, will likely be practical for niche applications in the short term due to the high electricity costs, especially when electricity is generated by renewable energy sources.

Off-grid electricity generation using renewable energy technologies has become a more reliable source to fulfill the needs of rural areas at limited level without considering conventional resources. The main purpose of this study was to propose an economical and optimized design for electricity generation using hybrid energy source PV/Biomass for an agricultural farm and a residential community centered in a small village of district Layyah in the Punjab province of Pakistan. The electric load data was collected for the irrigation and residential needs. Hybrid Optimization Model for Electric Renewable (HOMER) was used to design and perform techno-economic analysis to meet the load requirements using PV/biomass hybrid configuration. The solar irradiance data and the available biomass potential on the farm was used in the HOMER software to perform the analysis. Total net present cost (NPC) and cost of electricity (COE) were obtained as a solution by the HOMER analysis and then these results were refined further by performing sensitivity analysis. Sensitivity parameter such as biomass potential, biomass price, solar irradiance and variations in loads were used in the sensitivity analysis. This analysis compares the performance of the system and shows that system is techno-economically viable based on the net present cost and cost of energy.

Using time-series data from 1984 to 2019, the study examines the vigorous trade-environment relation in Pakistan. Pakistan is an interesting case study in which trade liberalization has expanded economic activity while also increasing environmental pollution during the last two decades. As a result, determining whether trade and industrial operations have contributed to environmental degradation is crucial. Our first goal is to look at how trade affects the environment in terms of scale, composition, and technique. The second step is to look into the pollution haven theory. The study uses a new approach to measuring trade openness called composite trade intensity, which differs from the traditional approach. The dynamic autoregressive distributed lag (ARDL) simulation framework, which was recently developed, was employed. The findings show that the scale impact raises CO2 emissions while the technique effect helps to lessen them, proving the existence of an environmental Kuznets curve (EKC) hypothesis. The composition impact contributes to increased pollution in the environment. Through the expansion of pollution-intensive export businesses, trade openness degrades environmental quality over the long as well as in the short term. The notion of a pollution hypothesis has also been proven. The quality of the environment deteriorates as a result of urbanization, whereas it improves as a result of good governance. Economic growth, trade openness, urbanization, and CO2 emissions have bidirectional causality, according to frequency domain causality findings. Based on our empirical findings, the study concludes that individual efforts, as well as collective efforts at the international level to reduce carbon emissions, are critical to solving the problem of environmental degradation and making the world a completely peaceful place.