About This Project

An open-source system for biomass feedstock pre-processing to enable carbon removal and valorization

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Motivating Factor

It is widely acknowledged that at least 5-10B tonnes of atmospheric carbon dioxide removal (CDR) is needed by 2050 to keep warming below 1.5-2C. Non-biomass pathways such as DAC and ERW face significant scaling constraints due to land use, energy, and raw materials which limit them to <4Gt even under extremely optimistic assumptions. Waste biomass approaches can operate with little to no energy input, minimal land use, and few other constraints. It is critical that we improve our utilization of this vast untapped resource (10B t CDR potential p.a.) to meet our climate and carbon removal goals. This is particularly true if, as seems likely, decarbonization efforts are slower than previously forecasted. Today, the vast majority of biomass waste is landfilled or incinerated each year, wasting resources and leading to pollution and contamination instead. However working with waste feedstocks presents challenges that have slowed development thus far.

Specific Bottleneck

A key limitation in working with waste biomass feedstocks is that it is extremely variable and heterogeneous, making it difficult to develop broadly applicable, scalable processes. Feedstocks range from crop residues to municipal waste to sewage sludge, varying in moisture content, COD, salinity, pH, and other critical factors. Composition can also vary across time and geography. High transportation costs (in both dollars and emissions) make it difficult to consolidate “similar” feedstocks for processing. Instead, we need to develop processes which can ingest geographically colocated feedstocks (regardless of composition) for biomass valorization to scale. To date, most carbon removal approaches have focused on working with dry, heterogeneous, lignocellulosic feedstocks (e.g. corn stover or sugarcane bagasse) to mitigate this problem; however, this significantly limits scaling potential. Waste-to-energy processes have been similarly limited by feedstock variability.

Actionable Goals

A broadly applicable system for triaging, blending and pre-treating feedstocks, bringing key parameters within pre-defined acceptable ranges, would vastly improve viability of biomass-based approaches to carbon removal, unlocking greater scale potential. This requires first understanding how different feedstock parameters affect viability and performance for different processing methods (much of which is available in the literature), to identify a nominal composition for different processes. Next, development of a standardized, rapid and cost-efficient testing approach is needed to test potential feedstocks against these parameters in situ. These are key given 1) the dearth of public data on feedstock composition 2) the need for rapid assessment and pre-processing of feedstock required to enable large scale facilities. This would ideally be integrated with a low-cost treatment system capable of grinding, dosing, or otherwise treating the feedstock to bring it within an acceptable range