Making bio feedstocks sustainable for the future
Ron Beck , senior director at AspenTech , discusses the role of digitalisation in making bio feedstocks viableç
The carbon footprint of supply chains is subject to increasing visibility and scrutiny . At the same time , bio feedstocks ( the use of biomass such as wood , corn stover , sugar cane and palm oil , and organic waste , such as used cooking oil , as chemical feedstocks ) have been highlighted as a path to greater greening of consumer and industrial products .
On the surface , biofeedstock integration seems to be a winwin . There are a few challenges however , and all of them have a major supply chain visibility and optimisation component :
• Discovering the most effective chemical pathway to convert particular biomaterials into chemicals of equal or better functionally than their hydrocarbon-based equivalents
• Accomplishing that in the most energy and materials efficient manner
• Accelerating the adoption of testscale technologies into industrialscale production
• Tracking bio content , both to certify it to consumers and investors , and to prove its lifecycle benefit over today ’ s products
Drive for bio
Europe , Southeast Asia and Africa have taken the lead in championing bio feedstocks as a means of curbing the carbon intensity of hydrocarbon and chemicals production and bringing broader social benefits . The biofuels industry could employ 1,000-2,000 workers per 1,000-2,000 hectares of bio feedstock production in areas that are not productive today , such as parts of Africa with high unemployment and a low standard of living .
Recently , ENI signed an agreement with the government of Angola to develop an agro-biofuel sector . This also involves two key energy players in Angola , Sonangol and ANPG , and a supply chain that will span Africa and Italy . The sustainability benefits include incremental employment and income for Angolans and a greener product mix for ENI , incorporating agro-bio feedstocks in its refining and chemical processes .
However , many companies hesitate to use bio feedstock on a large scale , due to the availability of cheap fossil fuels and also the challenges associated with optimising the use and mixing of bio feedstocks in existing processes , as well as managing end product quality .
Businesses will need to navigate the variability of biofeedstock compositions drawn from diverse agricultural sources , while concerns linger over the performance of blended bio feedstocks alongside hydrocarbon counterparts , and the operational integrity and excellence of process units that are now repurposed to support mixed feedstocks .
Role of digital
In light of these challenges and the growing complexity of bio feedstocks , the need for digital systems to build better processes has become ever more pressing . Creating and scaling new processes requires a significant amount of experimental work to check the feasibility , economics , yield and viability of a new process .
Digital technologies can reduce the number of necessary experiments or assist in designing more targeted experimental schemes . When it comes to scaling up , digitalisation can be used to evaluate economics and offer design solutions to improve process efficiency .
One of the most effective uses of digitalisation in the context of bio feedstocks is for advanced hybrid models , which integrate first principlesbased process simulation models ( built on decades of chemical engineering domain expertise ) with analytics and AI algorithms .
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