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Developing countries like Pakistan majorly depend on fossil fuels for achieving higher economic growth but have sloppy environmental rules and regulations in order to attract foreign direct investment (FDI). As a result, energy consumption is considered the primary cause of environmental degradation. Besides CO emission, environmental degradation is also associated with emission of sulfur dioxide (SO). The purpose of this study was to investigate the relationship among SO emissions, energy consumption, economic growth, and FDI in Pakistan. By applying the 3SLS method, study has estimated the scale effect, composition effect, and technique effect. The scale effect and technique effect findings indicated that capital stock, FDI, and SO emissions all had a significant impact on GDP. When the capital accumulation effects of FDI were considered, the relationship between FDI and stock of capital was found to be positive. According to the technique effect results, FDI, population density, and energy consumption were all significantly related to SO emissions. The study came to a conclusion with significant policy implications.
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http://dx.doi.org/10.1007/s11356-021-15898-9 | DOI Listing |
Small
December 2024
College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou, 310018, People's Republic of China.
The conversion of biomass into chemical fuels is exciting but quite challenging in the development of an effective conversion strategy to generate easily-separated products without energy consumption. Herein, a lignocellulosic biomass-to-H conversion system via photo-thermal catalysis over MoC hierarchical nanotube catalysts in an acidic solution, in which the lignocellulose is hydrolyzed to small organic molecules (such as glucose, etc) by dilute HSO, and then the resulting glucose is oxidized by MoC catalyst to generate H are reported. During the photo-thermal catalytic processes, the carbon vacancy in MoC catalysts results in the generation of undercoordinated Mo sites, which act as active sites for both biomass oxidation and H generation reactions.
View Article and Find Full Text PDFAdv Mater
December 2024
Catalonia Institute for Energy Research (IREC), Jardins de les Dones de Negre 1, 2, Sant Adriá de Besós, Barcelona, 08930, Spain.
Neuromorphic hardware facilitates rapid and energy-efficient training and operation of neural network models for artificial intelligence. However, existing analog in-memory computing devices, like memristors, continue to face significant challenges that impede their commercialization. These challenges include high variability due to their stochastic nature.
View Article and Find Full Text PDFHuan Jing Ke Xue
January 2025
Research Center for Environmental Management, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
The wastewater treatment industry is an energy-intensive industry and one of the main sources of high warming potential greenhouse gases (GHG) such as CH and NO. The GHG reduction in this industry is an important part of achieving global climate goals. In 2019, there were 4 359 urban wastewater treatment plants in China, with a total wastewater treatment volume of 63.
View Article and Find Full Text PDFHuan Jing Ke Xue
January 2025
Institute of Blue and Green Development, Shandong University, Weihai 264209, China.
Clarifying the spatial correlation network structure from tourism transportation carbon emissions and its influencing factors is crucial for China's tourism and transportation industry to coordinate the planning of carbon reduction governance and realize the sustainable development of the tourism transportation industry. Based on inter-provincial panel data from 2001 to 2021, China's carbon emissions from tourism transportation were measured, and the modified spatial gravity model was used to construct characteristics of provincial spatial networks and their influencing factors, which were analyzed using the social network analysis method and the QAP model. The study showed that ① China's total carbon emissions from tourism and transportation have been growing slowly year by year, showing a distribution pattern of "high in the southeast and low in the northwest," with obvious differences between the eastern and western regions.
View Article and Find Full Text PDFHuan Jing Ke Xue
January 2025
College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China.
The farming-pastoral ecotone has an important strategic place in the energy supply and ecological layout of China. Thus, exploring the spatial and temporal variation characteristics of carbon emissions in this region will help to deeply understand the information on the historical carbon emissions in China's energy production bases and provide data references for the formulation of differentiated emission reduction policies and the promotion of regional energy-saving and carbon-reducing measures, which is of great significance for the realization of low-carbon economic development. This study constructed a spatialization model of carbon emissions based on land use, night lighting, and provincial energy consumption data; explored the spatiotemporal changes and aggregation characteristics of carbon emissions in the farming-pastoral ecotone from 1995 to 2020 using the global Moran's index and hotspot analysis; and then combined it with the slack-based measure model to calculate the carbon emission efficiency and emission reduction potential of each city from 2010 to 2020 and classify cities to propose a differentiated emission reduction path.
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