INTELIGÊNCIA ARTIFICIAL APLICADA À GOVERNANÇA AMBIENTAL: PROPOSTAS PARA O CONTROLE DA POLUIÇÃO POR MICROPLÁSTICOS NO BRASIL

Abstract

Microplastic pollution stands as one of the most challenging and emerging environmental threats today due to its ubiquity, persistence, and the still poorly understood effects on human health and ecosystems. In Brazil, the lack of specific public policies, institutional fragmentation, and scarcity of systematized data hinder the effectiveness of mitigation efforts. In response, this thesis proposes the enhancement of Brazilian public policies aimed at combating microplastic pollution through the application of artificial intelligence (AI)-based methodologies, with a focus on data-driven environmental governance. The research is aligned with the "Pollution Control Technologies" line of the Graduate Program in Environmental Technologies at UFMS and adopts an interdisciplinary approach integrating environmental science, data science, environmental law, and public policy. The thesis is structured into four main chapters. The first presents an overview of the presence of microplastics in Brazilian ecosystems, identifying research gaps and future challenges. The second chapter offers a critical analysis of national public policies, comparing them with international practices and proposing AI-assisted recommendations. The third chapter describes the design, development, and validation of the GEPLA platform – Plastic Pollution Governance with AI, an intelligent decision-support system that integrates data mining, probabilistic modeling, and policy simulation. The fourth chapter proposes a Standardized Guideline for Microplastic Investigation in Brazil, based on international protocols and adapted to the national context, aiming to ensure comparability, reproducibility, and applicability of the data produced. The main contributions of this work include: (i) a comprehensive and critical review of microplastic pollution in Brazil; (ii) an innovative AI-based environmental governance framework; and (iii) technical and institutional inputs to support the development of effective and sustainable public policies. By integrating knowledge and tools from multiple disciplines, the study demonstrates the potential of artificial intelligence as a strategic ally in addressing complex and diffuse environmental issues.