PROPOSTA DE PLANO DE GERENCIAMENTO DE RESÍDUOS SÓLIDOS PARA UMA INSTITUIÇÃO DE ENSINO TÉCNICO E SUPERIOR DO SUL DE MINAS GERAIS
Description
This dataset comprises the doctoral dissertation (tese de doutorado) underlying the research article "From waste characterisation to circular recovery: a transferable management framework for Brazilian Federal Institute campuses" submitted to the Journal of Cleaner Production. Research hypothesis and objectives Brazilian Federal Institutes of Education, Science and Technology (Institutos Federais — IFs) constitute a network of 661 campuses serving over one million daily users across Brazil, yet they are entirely absent from the solid waste management literature. This study hypothesises that gravimetric characterisation of waste streams, combined with a structured SWOT diagnosis and valorisation pathway analysis, can identify the structural drivers of low recyclable capture rates and provide an evidence base for PNRS-compliant Solid Waste Management Plan (SWMP) development at IF campuses. Data collection Primary data were collected at IFSULDEMINAS Campus Passos, Minas Gerais, Brazil, through a three-stage gravimetric characterisation protocol adapted from ABNT NBR 10.007/2004. Field campaigns were conducted in December 2023 (Stage 1 — pilot) and July 2024 (Stages 2 and 3 — reference dataset). Waste was manually sorted, weighed using calibrated scales, and classified into organic waste, recyclables, health-service waste, and rejects. Restaurant food waste was quantified separately using pre- and post-service weighing. Campus population was 1,420 daily users. Key findings Total weekly waste generation was 338.8 kg (per capita: 0.048 kg person⁻¹ day⁻¹). Organic waste dominated at 47.68%, followed by rejects (38.52%) and recyclables (13.81%). The elevated reject fraction was attributed to structural single-bin collection infrastructure rather than exclusively to user behaviour. Three priority interventions were identified: three-stream source segregation (potential fourfold increase in recyclable capture), on-campus composting of 175 kg week⁻¹, and reverse logistics for hazardous streams. Avoidable food waste was quantified at 1,956 kg year⁻¹, directly relevant to SDG 12.3. How to interpret and use this data The dissertation contains the complete field methodology, raw gravimetric data tables, SWOT analysis matrices, valorisation pathway matrix, and the integrated six-stage decision-support framework. The framework is directly transferable to the 661 IF campuses across Brazil and to analogous higher education institutions in developing countries. Researchers, campus managers and policymakers may use this dataset to benchmark waste generation rates, replicate the characterisation methodology, or adapt the proposed framework to their institutional context.
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