| dc.description.abstract | The global demand for renewable energy sources has intensified and, the second-generation
ethanol has emerged as a promising alternative to traditional fossil fuels. This study presents a
comprehensive sustainability assessment of second-generation ethanol production, focusing on
environmental, economic, and social dimensions. The evaluation incorporates a life cycle
perspective to analyse the entire production process, from feedstock cultivation to fuel
distribution. The environmental assessment considers key factors such as greenhouse gas
emissions, land use change, water consumption, and other relevant indicators. By employing
advanced modelling techniques and up-to-date data, the study aims to provide a nuanced
understanding of the environmental impact of second-generation ethanol compared to
conventional ethanol and other biofuels. In addition to environmental considerations, the
economic analysis explores the financial viability and competitiveness of second-generation
ethanol production. Factors such as production costs, market dynamics, and policy incentives
are examined to determine the economic feasibility and potential for widespread adoption.
Social aspects are crucial in assessing the overall sustainability of second-generation ethanol.
The study examines the impacts on local communities, employment opportunities, and
potential conflicts with food production. The analysis also addresses the broader societal
implications, including issues of equity, accessibility, and social acceptance. The findings of
this sustainability assessment aim to inform policymakers, industry stakeholders, and the
public about the strengths and challenges associated with second-generation ethanol. By
identifying areas for improvement and potential trade-offs, the study contributes to the
development of a more sustainable and socially responsible bioenergy sector.
As the global energy landscape evolves, understanding the holistic sustainability of second generation
ethanol becomes imperative for making informed decisions and achieving a more
sustainable energy future. The chapter starts with the global statistics of greenhouse gas
emission from the fossil fuel and biofuel. The advantages of biofuel over the fossil fuel are the
major reason to switch for the biofuel technology and the advantages have been described in a
comprehensive manner. As India is rich in agricultural resources, an agricultural waste to
ethanol pathway is possible for future transport. Ethanol blending has been implemented in
India; but currently it is limited to 10 percent in petrol; but the ethanol is a first generation
based which directly comes from plant-based feedstock. The first-generation ethanol might
arise the issue of food versus fuel as India has the global hunger index of 111 out of 125. The
idea is inspired from the circular economy (CE) framework here. Like the CE we have tried to
close the loop through our study. Hence farm area to farm area analogy has been presented
which can be termed as cradle-to-cradle technology. CE promotes the diversification of supply
chains by reducing dependence on a linear flow of resources. This can enhance resilience
against supply chain disruptions and price fluctuations.
A descriptive case study is performed for the analysis of the agricultural waste suitable for the
generation of ethanol, viability of the upstream of the supply chain, feasibility of the
thermochemical and biochemical conversion and finally closing the loop. A detailed study
shows the efficacy of the proposed ethanol supply chain with the help of sustainability
indicators.
The economic indicator encapsulates revenue generated, IRR (Internal rate of return) and NPV
(net present value), whereas the environmental indicator includes emissions, and the social
indicator includes number of jobs created.
The mathematical modelling has helped in assessment of the sustainability indicators. The
amalgamation of heuristic based algorithm and circular economy framework is one of the
innovative works done to prove the sustainability. The heuristic algorithm is based on the
cognitive behaviour of birds who search for optimal location of food. It is a new methodology
where the machine learning is used to predict the total revenue, emissions and number of jobs
generated for the next 5 years. A constrained based non-linear optimisation is the main part of
the algorithm which is known as particle swarm optimisation algorithm. Few constraints are
connected to the mass and energy balance of the supply chain. The mass and energy balance
are performed to analyse the total influx and outflux from the farm area and the collection
centre. The circular economy framework has enabled to visualise the role of many components
starting from farmers to policymakers in the loop. The defined 9R framework is radical in the
way it has been implemented to prove the cradle-to-cradle thinking. It connects each
component of the defined ethanol supply chain with the sustainability indicators intact. The
aim of the work is to establish a path leading research to enable waste to energy concept. In
this model the research work is based in the state of Karnataka, India. The work can be
extrapolated to any geographical area on the globe. | en_US |
