Analysis shows app-based models improve economic viability in residual biomass recovery, highlighting the need for external support.
Background: Rural fires, worsened by climate factors such as drought, biomass buildup, and ignition sources, threaten sustainability. Recovering residual biomass (RB) presents a promising way to lower fire risk by reducing fuel loads and generating renewable energy; however, logistical costs in the RB supply chain—due to poor stakeholder coordination—limit its feasibility. App-based models can help solve these issues by improving information sharing, but their economic viability remains largely unexplored. This study suggests that such models work well when large amounts of biomass are involved and moisture content is low. Still, they might need external incentives for widespread use and fire risk reduction. Methods: The study modeled recovery scenarios by comparing costs (harvesting, retrieval, transport, and pre-processing) with biomass market value, using expert inputs and sensitivity analysis on variables like fuel prices and wages. Results: The economic feasibility is possible for large volumes (e.g., 10-ton loads) with low moisture (<30%), allowing transportation distances up to 459 km; however, small-scale or high-moisture situations often are not viable without support. Conclusions: App-based models need external support, like subsidies, to overcome owner and RB challenges, ensuring effective fire mitigation and sustainability benefits.
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Bastos et al. (2025) studied this question.
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