Biogenic Material Separation From MSW for Biochar Production
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Solution Overview
Problem
Municipal solid waste (MSW) decomposition into greenhouse gases (GHGs) poses a significant environmental challenge due to the high biogenic content, necessitating effective separation and processing of biogenic materials to minimize GHG emissions.
Innovation Solution
A system utilizing image sensors, machine learning, and sorting devices to identify and separate biogenic materials from MSW, followed by pyrolysis to convert them into biochar and syngas, dynamically adjusting processes to achieve desired formulations and compositions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If biogenic material is landfilled and decomposes naturally, then it returns to the carbon cycle, but it generates greenhouse gases (carbon dioxide and methane) that contribute to climate change
Solution Approach 1:
The patent extracts biogenic materials from the municipal solid waste stream using advanced sorting technologies (optical sensors, AI/ML algorithms, robotic manipulators) before they can decompose in landfills. This separation removes the harmful decomposition process while preserving the carbon cycle function by directing biogenic materials to controlled processing facilities where they are converted to biochar, preventing GHG emissions while maintaining carbon sequestration.
Solution Approach 2:
The patent changes the processing parameters of biogenic materials by applying controlled pyrolysis conditions (temperature, atmosphere, residence time) to convert organic waste into biochar. This parameter transformation converts the harmful decomposition pathway into a beneficial carbon sequestration pathway, producing a stable carbon product that does not release GHGs while maintaining the natural carbon cycle function.
2Object-generated harmful factors
If advanced sorting technologies are used to separate biogenic materials from MSW, then GHG emissions are reduced, but system complexity increases
Solution Approach 1:
The patent employs a multi-functional sorting system that integrates optical sensing, AI/ML classification, and robotic manipulation into a single automated platform. This universal system handles multiple material types (food waste, yard waste, paper, cardboard, textiles) simultaneously, reducing the need for separate processing lines and minimizing overall system complexity while achieving effective biogenic material separation.
Solution Approach 2:
The patent introduces AI/ML algorithms as an intermediary layer between sensing and sorting actions. This intelligent mediator processes sensor data, identifies biogenic materials, and controls sorting mechanisms, simplifying the overall control architecture while improving sorting accuracy and reducing GHG emissions from mismanaged biogenic waste.
3Object-generated harmful factors
If biogenic materials are processed through pyrolysis to produce biochar, then carbon is sequestered and valuable byproducts are generated, but energy consumption increases
Solution Approach 1:
The patent implements self-service in the pyrolysis process by using the biogenic materials themselves as the energy source. The organic waste provides the heat required for pyrolysis through controlled combustion of a portion of the feedstock, eliminating the need for external energy inputs and making the process energy-self-sufficient while maximizing carbon sequestration efficiency.
Solution Approach 2:
The patent recovers energy from the biogenic materials during pyrolysis by capturing and utilizing the syngas and heat generated in the process. This energy recovery offsets the energy consumption of the pyrolysis reaction, reducing net energy requirements while producing valuable byproducts (biochar, syngas, bio-oil) that can be utilized or sold.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Efficiently reduces biogenic material decomposition into GHGs by separating and processing MSW into biochar and syngas, thereby sequestering carbon and producing valuable byproducts.
Implementation Method 1
A set of images of an input stream of heterogeneous materials is received from one or more image sensors
Implementation Method 2
The pixel values within the region are analyzed using machine learning to characterize the region into a biogenic-related classification
Implementation Method 3
A sorting device is instructed to perform a sorting operation to remove the material that has been identified as biogenic material from the stream
Implementation Method 4
pyrolysis to convert them into biochar and syngas
Data Source
AI summary
Obtaining biogenic material from a stream of heterogeneous materials is disclosed, including: receiving an input stream of heterogeneous material; separating a sub-stream of at least biogenic material from the input stream of heterogeneous material using a screen; removing a set of non-biogenic material from the sub-stream of at least biogenic material based at least in part on density separation; and drying the sub-stream of at least biogenic material after removal of the set of non-biogenic material, wherein the sub-stream of at least biogenic material after removal of the set of non-biogenic material comprises biogenic material that is suitable to produce biochar.