Ankush Halba is a Doctoral Fellow in the Department of Hydro and Renewable Energy, Indian Institute of Technology Roorkee (IIT Roorkee), India. With over seven years of experience in renewable and sustainable energy, he started this journey during his M.Tech. at IIT Kharagpur and continues to work at the intersection of biomass-to-energy, waste-to-energy, gasification and co-gasification, GIS-based biomass supply chain design and optimization, life cycle assessment (LCA), techno-economic assessment (TEA), carbon credits, ESG, Aspen Plus process modeling, biodiesel, and IC engines. He has published 9 peer-reviewed research papers as author and co-author in high-impact Q1 journals and conference proceedings, with additional manuscripts currently in preparation. He has a professional following of over 15,000 on LinkedIn. His research focuses on understanding when renewable energy systems are genuinely viable and when they fail due to overlooked technical, logistical, or financial constraints.

In a recent podcast hosted by Net Zero Compare, we discussed insights on the real-world performance of bioenergy systems, the importance of full life cycle thinking, and the financial realities behind renewable energy deployment. Drawing from seven years of hands-on research experience, he addressed how supply chain design, emissions accounting, and techno-economic modeling intersect in practice. As governments tighten Scope 1, 2, and 3 reporting requirements and companies face increasing pressure to decarbonize, these distinctions matter more than ever.

🎥Watch the Full Conversation: The full discussion with Ankush Halba is available below. In this conversation, we explored biomass supply chain emissions, carbon credits, life cycle assessment, techno-economic modeling, GIS-based optimization, ESG, and the practical limits of current renewable energy systems. Watching the full interview provides additional nuance, especially around region-specific constraints and modeling approaches that are difficult to capture fully in written form.

Biomass and Waste-to-Energy Are Not the Same

Bioenergy is often treated as a single category. In practice, biomass-to-energy and waste-to-energy represent distinct technical and environmental pathways.

Biomass refers to recently living organic material such as agricultural residues, forest residues, or animal waste. Waste-to-energy typically refers to the conversion of combustible fractions of municipal or industrial waste into energy.

Key differences include:

• Feedstock variability: Biomass availability is seasonal, while municipal waste varies by location and day-to-day generation patterns.

• Composition and preprocessing: Waste streams require segregation and material recovery before energy conversion.

• Environmental accounting: Avoided landfill emissions may apply in waste-to-energy systems, while biomass systems often focus on replacing fossil fuels or preventing open burning.

Failing to distinguish between these pathways leads to oversimplified policy and financing assumptions.

Life Cycle Assessment and Scope 1, 2, and 3 Emissions

Life Cycle Assessment, or LCA, evaluates environmental impacts across defined system boundaries. Ankush Halba emphasized that misunderstanding system boundaries is one of the most common sources of confusion in bioenergy research and project development.

Typical LCA system boundaries include:

• Cradle-to-gate

• Gate-to-gate

• Cradle-to-grave

• Cradle-to-cradle

If a study only reports gate-to-gate emissions, it excludes upstream supply chain impacts. In bioenergy systems, this omission can be significant.

Ankush noted that supply chain emissions, which often align with Scope 3 emissions in corporate reporting frameworks, can account for 70 to 90 percent of total emissions in some cases. If a plant reduces 100 kilograms of CO2 at the combustion stage but emits 200 kilograms during feedstock transport and preprocessing, the project results in net environmental harm.

For sustainability professionals dealing with Scope 1, 2, and 3 disclosures, this distinction is critical. LCA and corporate emissions accounting must align with actual system boundaries to avoid misleading conclusions and poor investment decisions.

When Bioenergy Makes Sense

Bioenergy systems can be viable under specific conditions:

1. Strong public-private collaboration plays a key role. Ankush described models where governments provide incentives or subsidies, private firms provide technology and operations, and local communities participate in feedstock supply and plant operations.

2. Region-specific design is equally important. Renewable energy deployment must account for geography, infrastructure, and local constraints. In mountainous regions, for example, manual biomass collection may be the only viable option, as Ankush has observed firsthand through his research on pine needle collection in the Indian Himalayan Region.

3. Financial viability improves when plants generate integrated revenue streams, such as electricity sales, byproduct sales, including biochar, and carbon credit revenue. His research has demonstrated that incorporating carbon credits and government subsidies significantly improves project returns.

In developing economies with high capital expenditure constraints, transitional models may be more realistic than full renewable system replacement.

When Bioenergy Fails

Many projects look viable in theoretical models but fail due to overlooked constraints in real-world conditions.

Common failure points include:

• Unreliable feedstock supply chains,

• High transportation distances,

• Biomass degradation during storage,

• Low CUF (capacity utilization factor), and

• Overestimated plant operating days.

Each of these factors individually can significantly alter both the economic and environmental performance of a project.

Ankush highlighted that storage losses alone can reach 16% to 24% of biomass mass over a year. In some supply chain studies he has conducted, up to 40% of biomass was lost due to accessibility constraints, particularly in mountainous and remote terrains such as the Indian Himalayan Region.

These losses directly affect both economic returns and emissions performance and are frequently underestimated or entirely ignored in preliminary feasibility studies. This is why rigorous supply chain assessment must precede any investment decision in bioenergy projects.

GIS Modeling and Supply Chain Optimization

Geographic Information Systems, or GIS, play a critical role in bioenergy deployment planning and decision-making.

Using spatial modeling, researchers can:

• Identify feedstock supply points,

• Optimize transportation routes,

• Assess terrain constraints,

• Determine plant siting, and

• Model intermediate storage options.

When integrated effectively, GIS-based analysis transforms raw geographic data into actionable supply chain decisions.

Ankush described using GIS to model pine needle collection in mountainous terrain in the Indian Himalayan Region, accounting for walking distances, slope constraints, and accessibility losses. These analyses directly influenced plant placement decisions and emissions calculations, demonstrating how supply chain optimization is not merely a logistical exercise but a core determinant of a project's environmental and financial performance.

Without rigorous supply chain optimization, Scope 3 emissions can easily outweigh operational emission reductions, turning what appears to be a green project into a net emissions contributor.

Techno-Economic Assessment Versus Real Markets

A techno-economic assessment determines whether a project is bankable. However, many models assume idealized conditions that rarely reflect ground realities.

Common modeling errors include:

• Assuming biomass is free,

• Ignoring procurement costs,

• Failing to model inflation and escalation rates,

• Ignoring discount rates, and

• Oversimplifying operational variability.

Each of these assumptions, when left unaddressed, can make an unviable project appear financially attractive on paper.

Ankush emphasized the importance of incorporating real inflation rates, labor cost escalation, and state-level policy differences into financial models.

His research has shown that standard financial indicators such as:

• Net Present Value,

• Internal Rate of Return,

• Discounted Payback Period, and

• Levelized Cost of Electricity.

All of them must be evaluated together under realistic assumptions rather than optimistic projections.

If NPV is positive under realistic assumptions, a project may be financially viable. However, sensitivity analyses often reveal that even small increases in feedstock costs can drastically change project outcomes, underscoring the need for robust scenario planning and conservative baseline assumptions in bioenergy project development.

Carbon Credits, ESG, and Green Financing

Carbon credits represent avoided, reduced, or removed emissions. Their financial impact on a bioenergy project depends on the credit type, verification methodology, and prevailing market price.

Bioenergy or waste-to-energy projects may qualify for credits through:

• Avoided landfill emissions,

• Avoided wildfire emissions,

• Carbon sequestration through biochar, and

• Direct carbon removal technologies.

Ankush's research has demonstrated that integrating carbon credits and government subsidies significantly improved project returns, making otherwise marginal projects financially viable.

ESG reporting frameworks also play an increasing role in bioenergy deployment. Companies under regulatory pressure to reduce emissions intensity are actively seeking investment in bioenergy projects to meet compliance targets, creating new financing opportunities for well-designed projects.

Green financing mechanisms, including lower-interest capital dedicated to renewable projects, further improve feasibility and reduce the cost of capital. However, Ankush cautioned that reliance on carbon credits without robust system boundaries can distort incentives if emissions are merely shifted rather than genuinely reduced. For carbon markets to function effectively in supporting bioenergy, rigorous life cycle thinking and transparent emissions accounting must underpin every credit claim.

Internal Combustion Engines in the Transition Phase

In emerging economies, fully replacing internal combustion engines is not immediately feasible, and any transition strategy must account for this reality.

Halba argued that transition strategies must consider:

• Technology readiness levels,

• Per capita income constraints,

• Infrastructure availability, and

• Electricity generation sources.

These factors collectively determine the pace and viability of any energy transition at the ground level.

A critical but often overlooked point is that if electric vehicles are charged using fossil-based electricity, lifecycle emissions may not improve significantly compared to conventional internal combustion engine vehicles. The source of electricity generation is therefore as important as the technology itself.

Hybrid models may represent a realistic interim solution while renewable generation scales up to meet demand. Ankush's research perspective, grounded in the realities of developing economies and rural energy access, suggests that a phased and context-sensitive approach to transitioning away from internal combustion engines is far more practical and impactful than an abrupt technology shift driven purely by policy mandates.

What Developers Should Get Right First

Before committing capital to biomass or waste-to-energy projects, developers and municipalities must prioritize getting the fundamentals right:

• Conducting full supply chain assessments is the critical first step, as upstream emissions and logistics costs can determine a project's viability before a single piece of equipment is installed. System boundaries must be defined clearly and transparently from the outset, ensuring that LCA and corporate emissions accounting are aligned with actual project conditions.

• Realistic financial assumptions must be modelled from the beginning, incorporating inflation, labor cost escalation, feedstock procurement costs, and state-level policy variations. Feedstock variability and storage losses must also be evaluated rigorously, as these are among the most commonly underestimated risk factors in bioenergy project development.

• Early stakeholder engagement is equally important. Local communities are not just end users, but active participants in feedstock supply chains, and their involvement from the planning stage significantly improves both project acceptance and operational reliability.

• Waste segregation at source is particularly critical in waste-to-energy systems. Without proper segregation, supply chain complexity increases both cost and emissions, undermining the very environmental and financial case that justified the project in the first place.

Bridging the Technology Readiness Gap

One of the most persistent challenges in renewable energy deployment is the technology readiness gap, and bridging it requires deliberate and sustained investment.

Ankush emphasized the importance of investing in mid-stage technologies, particularly those between Technology Readiness Levels 4 and 6. This is the stage where many promising technologies stall, having proven their concept in laboratory settings but lacking the funding and institutional support needed to reach commercial deployment. This phase is often referred to as the valley of death in technology development, and bioenergy technologies are particularly vulnerable to it.

Collaboration between researchers, government agencies, industry, and local communities is essential to bridge this gap. Each stakeholder brings a distinct and necessary contribution, from fundamental research and policy support to capital investment and community-level implementation.

Conclusion

Bioenergy is neither universally green nor inherently flawed. Its sustainability depends on context, supply chain design, financial modeling, and realistic assumptions.

For organizations navigating ESG reporting, Scope 1, 2, and 3 emissions compliance, and decarbonization strategies, the key takeaway is clear. System boundaries matter. Supply chain emissions can dominate total impact. Financial viability depends on real-world costs, not optimistic assumptions.

As regulatory scrutiny increases and capital markets demand credible climate strategies, rigorous life cycle assessment and techno-economic analysis are no longer optional. They are prerequisites for responsible deployment.