Analysis of decarbonization measures for the Indian Cement Sector.

Cement is one of the widely used materials in construction, and its production is both energy- and emission-intensive, contributing significantly to industrial emissions. This study investigates multiple methods for reducing emissions in the Indian cement sector based on the mass and energy balances of a representative cement plant. A novel methodology for calculating the overall emissions reduction per tonne of cement with multiple emission reduction measures and their interdependencies is proposed. The effect of captive power plants in the cement industry on emissions reduction is also considered. The results are depicted using an emission abatement curve, which gives the CO2 abatement cost against cumulative emission reduction per tonne of cement, and a cost premium curve, which shows the cumulative abatement cost against percentage abatement. The analysis shows that up to 30% emissions reduction is possible using existing emission reduction measures in all the cases considered with no additional cost, and near-zero emission reduction is only possible with the adoption of emerging technologies such as carbon capture and storage. The proposed methodology is the first to explore the impact of multiple measures for emission reduction on a given cement plant, allowing for a realistic estimate of emission reduction from the measures implemented.

Emerging Directions for Carbon Capture Technologies: A Synergy of High-Throughput Theoretical Calculations and Machine Learning.

As the world grapples with the challenges of energy transition and industrial decarbonization, the development of carbon capture technologies presents a promising solution. The Scalable Modeling, Artificial Intelligence (AI), and Rapid Theoretical calculations, referred as SMART here, is an interdisciplinary approach that combines high-throughput calculation and data-driven modeling with expertise from chemical, materials, environmental, computer and data science and engineering, leading to the development of advanced capabilities in simulating and optimizing carbon capture processes. This perspective discusses the state-of-the-art material discovery research enabled by high-throughput calculation and data-driven modeling. Further, we propose a framework for material discovery, and illustrate the synergies among deep learning models, pretrained models, and comprehensive data sets, emerging as a robust framework for data-driven design and development in carbon capture. In essence, the adoption of the SMART approach promises a revolutionary impact on efforts in energy transition and industrial decarbonization.

Is Additive Manufacturing an Environmentally and Economically Preferred Alternative for Mass Production?

The manufacturing sector accounts for a large percentage of global energy use and greenhouse gas emissions, and there is growing interest in the potential of additive manufacturing (AM) to reduce the sector's environmental impacts. Across multiple industries, AM has been used to reduce material use in final parts by 35-80%, and recent publications have predicted that AM will enable the fabrication of customized products locally and on-demand, reducing shipping and material waste. In many contexts, however, AM is not a viable alternative to traditional manufacturing methods due to its high production costs. And in high-volume mass production, AM can lead to increased energy use and material waste, worsening environmental impacts compared to traditional production methods. Whether AM is an environmentally and economically preferred alternative to traditional manufacturing depends on several hidden aspects of AM that are not readily apparent when comparing final products, including energy-intensive and expensive material feedstocks, excessive material waste during production, high machine costs, and slow rates of production. We systematically review comparative studies of the environmental impacts and costs of AM in contrast with traditional manufacturing methods and identify the conditions under which AM is the environmentally and economically preferred alternative. We find that AM has lower production costs and environmental impacts when production volumes are relatively low (below ∼1,000 per year for environmental impacts and below 42-87,000 per year for costs, depending on the AM process and part geometry) or the parts are small and would have high material waste if traditionally manufactured. In cases when the geometric freedom of AM enables performance improvements that reduce environmental impacts and costs during a product's use phase, these can counteract the higher production impacts of AM, making it the preferred alternative at larger production volumes. AM's ability to be environmentally and economically beneficial for mass manufacturing in a wider variety of contexts is dependent on reducing the cost and energy intensity of material feedstock production, eliminating the need for support structures, raising production speeds, and reducing per unit machine costs. These challenges are not primarily caused by economies of scale, and therefore, they are not likely to be addressed by the increasing expansion of the AM sector. Instead, they will require fundamental advances in material science, AM production technologies, and computer-aided design software.

Achieving artificial carbon cycle via integrated system of high-emitting industries and CCU technology: Case of China.

Process-related carbon emissions, which cannot be completely eliminated by the improvement of processes and energy structure, are recognized as an enormous challenge for in-depth decarbonization. To accelerate the achievement of carbon neutrality, the concept of 'artificial carbon cycle' is proposed based on the integrated system of process-related carbon emissions from high-emitting industries and CCU technology as a potential pathway towards a sustainable future. This paper conducts a systematic review on the integrated system with the case of China, which is the largest carbon-emitting and manufacturing country, to provide a clearer and more meaningful analysis. Multi-index assessment was used to organize the literature and draw the useful conclusion. Based on literature review, the high-quality carbon sources, reasonable carbon capture approaches and promising chemical products were identified and analyzed. Then the potential and practicability of the integrated system was further summarized and analyzed. Finally, key factors of future development including technology improvement, green hydrogen, clean energy and industrial cooperation were stressed to provide a theoretical reference for future researchers and policy makers.

Environmental management of industrial decarbonization with focus on chemical sectors: A review.

A considerable portion of fossil CO2 emissions comes from the energy sector for production of heat and electricity. The industrial sector has the second order in emission in which the main parts are released from energy-intensive industries, namely metallurgy, building materials, chemicals, and manufacturing. The decarbonization of industrial wastes contemplates the classic decarbonization through optimization of conventional processes as well as utilization of renewable energy and resources. The upgrading of existing processes and integration of the methodologies with a focus on efficiency improvement and reduction of energy consumption and the environment is the main focus of this review. The implementation of renewable energy and feedstocks, green electrification, energy conversion methodologies, carbon capture, and utilization, and storage are also covered. The main objectives of this review are towards chemical industries by introducing the potential technology enhancement at different subsectors. For this purpose, state-of-the-art roadmaps and pathways from the literature findings are presented. Both common and innovative renewable attempts are needed to reach out both short- and long-term deep decarbonization targets. Even though all of the innovative solutions are not economically viable at the industrial scale, they play a crucial role during and after the energy transition interval.