Marcello B. Solomon, Swapna S. Rabha, Gustavo Fimbres-Weihs, Himanshu Goyal, Firouzeh R. Taghikhah, Jithin J. Varghese, Samuel R. Wenger, Weibin Liang, Eleanor R. Kearns, Jun Huang, Niket S. Kaisare* and Deanna M. D’Alessandro*,
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Decarbonization in Australia and India: Bilateral Opportunities and Challenges for the Net Zero Transformation
The global Net Zero transformation is a vital response to the climate change crisis. Australia and India face similar challenges due to their reliance on fossil resources, growing energy demand, and agricultural emissions. However, differences exist in the population, industry, and development. This perspective explores these comparisons between Australia and India’s Net Zero aspirations and current sociopolitical and economic drivers. As part of the portfolio of options needed to address net zero goals, Carbon Capture, Utilization, and Storage (CCUS) and Carbon Dioxide Removal (CDR) solutions are specifically discussed. The perspective concludes with opportunities for the nations to engage in knowledge sharing and bilateral partnerships to help accelerate the world’s transformation to Net Zero.
期刊介绍：
）ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)
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