Life Cycle Assessment of Cross-Laminated Timber Transportation from Three Origin Points

Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities

Carbon capture, utilization, and sequestration (CCUS) is a promising solution to decarbonize the energy and industrial sectors to mitigate climate change. An integrated assessment of technological options is required for the effective deployment of CCUS large-scale infrastructure between CO2 production and utilization/sequestration nodes. However, developing cost-effective strategies from engineering and operation perspectives to implement CCUS is challenging. This is due to the diversity of upstream emitting processes located in different geographical areas, available downstream utilization technologies, storage sites capacity/location, and current/future energy/emissions/economic conditions. This paper identifies the need to achieve a robust hybrid assessment tool for CCUS modeling, simulation, and optimization based mainly on artificial intelligence (AI) combined with mechanistic methods. Thus, a critical literature review is conducted to assess CCUS technologies and their related process modeling/simulation/optimization techniques, while evaluating the needs for improvements or new developments to reduce overall CCUS systems design and operation costs. These techniques include first principles- based and data-driven ones, i.e. AI and related machine learning (ML) methods. Besides, the paper gives an overview on the role of life cycle assessment (LCA) to evaluate CCUS systems where the combined LCA-AI approach is assessed. Other advanced methods based on the AI/ML capabilities/algorithms can be developed to optimize the whole CCUS value chain. Interpretable ML combined with explainable AI can accelerate optimum materials selection by giving strong rules which accelerates the design of capture/utilization plants afterwards. Besides, deep reinforcement learning (DRL) coupled with process simulations will accelerate process design/operation optimization through considering simultaneous optimization of equipment sizing and operating conditions. Moreover, generative deep learning (GDL) is a key solution to optimum capture/utilization materials design/discovery. The developed AI methods can be generalizable where the extracted knowledge can be transferred to future works to help cutting the costs of CCUS value chain.

A Lifecycle Assessment of a Low-Energy Mass-Timber Building and Mainstream Concrete Alternative in Central Chile

While high-rise mass-timber construction is booming worldwide as a more sustainable alternative to mainstream cement and steel, in South America, there are still many gaps to overcome regarding sourcing, design, and environmental performance. The aim of this study was to assess the carbon emission footprint of using mass-timber products to build a mid-rise low-energy residential building in central Chile (CCL). The design presented at a solar decathlon contest in Santiago was assessed through lifecycle analysis (LCA) and compared to an equivalent mainstream concrete building. Greenhouse gas emissions, expressed as global warming potential (GWP), from cradle-to-usage over a 50-year life span, were lower for the timber design, with 131 kg CO2 eq/m2 of floor area (compared to 353 kg CO2 eq/m2) and a biogenic carbon storage of 447 tons of CO2 eq/m2 based on sustainable forestry practices. From cradle-to-construction, the embodied emissions of the mass-timber building were 42% lower (101 kg CO2 eq/m2) than those of the equivalent concrete building (167 kg CO2 eq/m2). The embodied energy of the mass-timber building was 37% higher than that of its equivalent concrete building and its envelope design helped reduce space-conditioning emissions by as much as 83%, from 187 kg CO2 eq/m2 as estimated for the equivalent concrete building to 31 kg CO2 eq/m2 50-yr. Overall, provided that further efforts are made to address residual energy end-uses and end-of-life waste management options, the use of mass-timber products offers a promising potential in CCL for delivering zero carbon residential multistory buildings.