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Bank lending and environmental quality in Gulf Cooperation Council countries
To achieve economies with net-zero carbon emissions, it is essential to develop a robust green financial intermediary channel. This study seeks empirical evidence on how domestic bank lending to sovereign and private sectors in Gulf Cooperation Council (GCC) countries impacts carbon dioxide and greenhouse gas emissions. We employ PMG-ARDL model to panel data comprising six countries in GCC over twenty years for carbon dioxide emissions and nineteen years for greenhouse gas emissions. Our findings reveal a long-term positive impact of both bank lending variables on carbon dioxide and greenhouse gas emissions. In addition, lending to the government shows a negative short-term effect on greenhouse gas emissions. The cross-country results demonstrate the presence of a long-run effect of explanatory variables on both types of emissions, except for greenhouse gas in Saudi Arabia. The sort-term impact of the explanatory variables on carbon dioxide and greenhouse gas emissions is quite diverse. Not only do these effects differ across countries, but some variables have opposing effects on the two types of emissions within a single country. The findings of this study present a new perspective for GCC economies: neglecting total greenhouse gas emissions and concentrating solely on carbon dioxide emissions means missing critical information for devising effective strategies to combat threats of environmental degradation and achieve net-zero goals.
Effects of nitrogen vacancy sites of oxynitride support on the catalytic activity for ammonia decomposition
Nitrogen-containing compounds such as imides and amides have been reported as efficient materials that promote ammonia decomposition over nonnoble metal catalysts. However, these compounds decompose in an air atmosphere and become inactive, which leads to difficulty in handling. Here, we focused on perovskite oxynitrides as air-stable and efficient supports for ammonia decomposition catalysts. Ni-loaded oxynitrides exhibited 2.5–18 times greater catalytic activity than did the corresponding oxide-supported Ni catalysts, even without noticeable differences in the Ni particle size and surface area of the supports. The catalytic performance of the Ni-loaded oxynitrides is well correlated with the nitrogen desorption temperature during N2 temperature-programmed desorption, which suggests that the lattice nitrogen in the oxynitride support rather than the Ni surface is the active site for ammonia decomposition. Furthermore, NH3 temperature-programmed surface reactions and density functional theory (DFT) calculations revealed that NH3 molecules are preferentially adsorbed on the nitrogen vacancy sites on the support surface rather than on the Ni surface. Thus, the ammonia decomposition reaction is facilitated by a vacancy-mediated reaction mechanism.
Mechanisms of electrochemical hydrogenation of aromatic compound mixtures over a bimetallic PtRu catalyst
Efficient electrochemical hydrogenation (ECH) of organic compounds is essential for sustainability, promoting chemical feedstock circularity and synthetic fuel production. This study investigates the ECH of benzoic acid, phenol, guaiacol, and their mixtures, key components in upgradeable oils, using a carbon-supported PtRu catalyst under varying initial concentrations, temperatures, and current densities. Phenol achieved the highest conversion (83.17%) with a 60% Faradaic efficiency (FE). In mixtures, benzoic acid + phenol yielded the best performance (64.19% conversion, 74% FE), indicating a synergistic effect. Notably, BA consistently exhibited 100% selectivity for cyclohexane carboxylic acid (CCA) across all conditions. Density functional theory (DFT) calculations revealed that parallel adsorption of BA on the cathode (−1.12 eV) is more stable than perpendicular positioning (-0.58 eV), explaining the high selectivity for CCA. These findings provide a foundation for future developments in ECH of real pyrolysis oil.
Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts
Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.
Photo-assisted technologies for environmental remediation
Industrial processes can lead to air and water pollution, particularly from organic contaminants such as toluene and antibiotics, posing threats to human health. Photo-assisted chemical oxidation technologies leverage light energy to mineralize these contaminants. In this Review, we discuss the mechanisms and efficiencies of photo-assisted advanced oxidation processes for wastewater treatment and photothermal technologies for air purification. The integration of solar energy enhances degradation efficiency and reduces energy consumption, enabling more efficient remediation methods. We evaluate the technological aspects of photo-assisted technologies, such as photo-Fenton, photo-persulfate activation, photo-ozonation and photoelectrochemical oxidation, emphasizing their potential for practical applications. Finally, we discuss the challenges in scaling up photo-assisted technologies for specific environmental remediation needs. Photo-assisted technologies have demonstrated effectiveness in environmental remediation, although large-scale applications remain constrained by high costs. Future potential applications of photo-assisted technologies will require that technology selection be tailored to specific pollution scenarios and engineering processes optimized to minimize costs.
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