Periodic Reporting for period 2 - BAM (Super Bio-Accelerated Mineral weathering: a new climate risk hedging reactor technology)
Période du rapport: 2022-09-01 au 2024-02-29
Conventional climate change mitigation alone will not be able to stabilise atmospheric CO2 concentrations at a level compatible with the 2°C warming limit of the Paris Agreement. Safe and scalable negative emission technologies (NETs), which actively remove CO2 from the atmosphere and ensure long-term carbon (C) sequestration, will be needed. Still, no NETs are even on the verge of achieving a substantial contribution to the climate crisis in a sustainable, energy-efficient and cost-effective manner. BAM! develops ‘super bio-accelerated mineral weathering’ (BAM) as a radical, innovative solution to the NET challenge. While enhanced silicate weathering (ESW) was put forward as a potential NET earlier, we argue that current research focus on either 1/ ex natura carbonation or 2/ slow in natura ecosystem-based ESW, hampers the potential of the technology to provide a substantial contribution to negative emissions within the next two decades. BAM! focuses on an unparalleled reactor effort to maximize biotic weathering stimulation at low resource inputs, and implementation of an automated, rapidlearning process that allows to fast-adopt and improve on critical weathering rate breakthroughs. The direct transformational impact of BAM! lies in its ambition to develop a NET that serves as a climate risk hedging tool on the short term (within 10-20 years). BAM! builds on the natural powers that have triggered dramatic changes in the Earth’s
weathering environment, embedding them into a novel, reactor-based technology. The ambitious end-result is the development of an indispensable environmental remediation solution, that transforms large industrial CO2 emitters into no-net CO2 emitters.
weathering environment, embedding them into a novel, reactor-based technology. The ambitious end-result is the development of an indispensable environmental remediation solution, that transforms large industrial CO2 emitters into no-net CO2 emitters.
The main objectives of BAM! are to:
1. assess the ESW stimulation potential of an unprecedented amount of > 2000 combinations of different biotic weathering stimulants through ambitious batch experiments;
2. build an advanced hybrid reactor to assess abiotic and biotic conversions during the weathering process. Tested combinations will be based on the outcome of the batch experiments;
3. apply a 3-module machine learning approach to fast-forward knowledge on weathering mechanisms and steer the reactor into a regime of optimal CO2 sequestration.
The first objective is the focus of WP1, in which 200 batch reactors were set up to test >2000 combinations of minerals, biota and organic matter. One batch run takes 2 months. Currently, we finalized 10 batch runs in which we tested 2000 combinations. We are now analyzing and interpreting the results of 1921 columns, which will guide targeted further experiments. This is a joint effort of all groups, and particularly involving the data scientists of IMEC.
For the second objective, which is the core of WP2, we designed the advanced hybrid reactor. The design phase included analyses to decide on the size and dimensions of the reactor vessel, on the gas and liquid inputs and outputs and the equipment needed for in-line and discrete measurements. The first reactor runs took place in 2023. New reactor runs are planned. Each run involves different abiotic and biotic materials and different treatments.
The third objective focuses on guiding the batch and reactor experiments to ensure the most interesting results possible. To this end, an optimal experimental design methodology that maximizes information gained by each experiment was created. In view of the advanced machine learning analyses, expert knowledge was exchanged concerning the relationships among different variables being measured. Via the machine learning analyses, the batch designs were modified.
1. assess the ESW stimulation potential of an unprecedented amount of > 2000 combinations of different biotic weathering stimulants through ambitious batch experiments;
2. build an advanced hybrid reactor to assess abiotic and biotic conversions during the weathering process. Tested combinations will be based on the outcome of the batch experiments;
3. apply a 3-module machine learning approach to fast-forward knowledge on weathering mechanisms and steer the reactor into a regime of optimal CO2 sequestration.
The first objective is the focus of WP1, in which 200 batch reactors were set up to test >2000 combinations of minerals, biota and organic matter. One batch run takes 2 months. Currently, we finalized 10 batch runs in which we tested 2000 combinations. We are now analyzing and interpreting the results of 1921 columns, which will guide targeted further experiments. This is a joint effort of all groups, and particularly involving the data scientists of IMEC.
For the second objective, which is the core of WP2, we designed the advanced hybrid reactor. The design phase included analyses to decide on the size and dimensions of the reactor vessel, on the gas and liquid inputs and outputs and the equipment needed for in-line and discrete measurements. The first reactor runs took place in 2023. New reactor runs are planned. Each run involves different abiotic and biotic materials and different treatments.
The third objective focuses on guiding the batch and reactor experiments to ensure the most interesting results possible. To this end, an optimal experimental design methodology that maximizes information gained by each experiment was created. In view of the advanced machine learning analyses, expert knowledge was exchanged concerning the relationships among different variables being measured. Via the machine learning analyses, the batch designs were modified.
The direct transformational impact of BAM! lies in its ambition to develop a NET that serves as a climate risk hedging tool. BAM! builds on the natural powers that triggered dramatic changes in the Earth’s weathering environment, embedding them into a novel, reactor-based technology. The ambitious end-result is the development of an indispensable environmental remediation solution, that transforms large industrial CO2 emitters into no-net CO2 emitters. The scientific and technological approach is designed to achieve a multi-purpose end-product, where flexible combinations of abiotics (e.g. potential water flow-through rate, local availability of minerals) and biotic stimulants are fitted together for specific conditions at the emission locality. The smart-testing environment of WP1, assisted by active learning techniques (WP3) for rapid synergy detection, in complement with the multi-sensor, machine learning assisted analysis of mechanistic processes in the advanced hybrid reactor (WP2, WP3), aims to achieve a portfolio of modular CO2 sequestration solutions.
Our unique multi-sensor approach fitted with machine-learning algorithms, provides perspective for process automation in the future deployment phase, with algorithm-driven self-adjustment of local parameters directly steering conditions to optimize CO2 sequestration. Opportunities of the specific weathering-oriented research also stretch beyond mere CO2 sequestration technology. The specific conditions created by a weathering ooze that can rapidly dissolve silicate minerals has potential applications in e.g. the sustainable mining industry (as a replacement for highly-polluting acid mine leaching techniques). The high-alkalinity silicate solutions produced in the reactor have potential industrial uses, e.g. binders in detergents and cleaners, sand agglomeration and geopolymer production. Our reactor potentially provides a new production technology for these valuable industrial products, that now require energy intensive production processes.
Climate change has become so evident in recent years, that society as a whole started to demand solutions. Still, societal, economic and technological barriers are slowing down implementation of a carbon-neutral society by 2050. BAM! provides a technological solution for challenging-to-decarbonize sectors, e.g. the (bio-) energy sector, steel industry and high-energy chemical industrial clusters. The price for emitting CO2 will inevitably rise in the coming decades: there is no question that a flexible, modular technique allowing to drastically reduce CO2 emissions will be strongly asked for. In fact, worldwide pioneer investments are performed to aggregate CO2 emissions in e.g. harbour industrial regions, and technologies to utilize the CO2 are highly sought for. BAM! aims to make a difference through its potential for embedment in a larger CO2 and sustainable agriculture/industry framework.The reactive mineral-organic-worm cast mixture in the BAM! reactor can potentially be transformed into a natural fertilizer. Silicate fertilization has been used for millennia to increase soil nutrient and essential element availability. BAM!s reactor residue will be strongly enriched in highly reactive silicates, providing further potential for CO2 sequestration through continued field ESW. To align with metal and steel industry, silicates can potentially be replaced with silicate steel slag waste from the industry itself. The same holds true for added biomass, which could originate directly from e.g. the bio-energy sector. Implementation in harbour areas provides potential for the implementation of management strategies to improve coastal resilience against ocean acidification (alkalinity) and eutrophication (increased silicate availability).
Our unique multi-sensor approach fitted with machine-learning algorithms, provides perspective for process automation in the future deployment phase, with algorithm-driven self-adjustment of local parameters directly steering conditions to optimize CO2 sequestration. Opportunities of the specific weathering-oriented research also stretch beyond mere CO2 sequestration technology. The specific conditions created by a weathering ooze that can rapidly dissolve silicate minerals has potential applications in e.g. the sustainable mining industry (as a replacement for highly-polluting acid mine leaching techniques). The high-alkalinity silicate solutions produced in the reactor have potential industrial uses, e.g. binders in detergents and cleaners, sand agglomeration and geopolymer production. Our reactor potentially provides a new production technology for these valuable industrial products, that now require energy intensive production processes.
Climate change has become so evident in recent years, that society as a whole started to demand solutions. Still, societal, economic and technological barriers are slowing down implementation of a carbon-neutral society by 2050. BAM! provides a technological solution for challenging-to-decarbonize sectors, e.g. the (bio-) energy sector, steel industry and high-energy chemical industrial clusters. The price for emitting CO2 will inevitably rise in the coming decades: there is no question that a flexible, modular technique allowing to drastically reduce CO2 emissions will be strongly asked for. In fact, worldwide pioneer investments are performed to aggregate CO2 emissions in e.g. harbour industrial regions, and technologies to utilize the CO2 are highly sought for. BAM! aims to make a difference through its potential for embedment in a larger CO2 and sustainable agriculture/industry framework.The reactive mineral-organic-worm cast mixture in the BAM! reactor can potentially be transformed into a natural fertilizer. Silicate fertilization has been used for millennia to increase soil nutrient and essential element availability. BAM!s reactor residue will be strongly enriched in highly reactive silicates, providing further potential for CO2 sequestration through continued field ESW. To align with metal and steel industry, silicates can potentially be replaced with silicate steel slag waste from the industry itself. The same holds true for added biomass, which could originate directly from e.g. the bio-energy sector. Implementation in harbour areas provides potential for the implementation of management strategies to improve coastal resilience against ocean acidification (alkalinity) and eutrophication (increased silicate availability).