Mitigating emissions from mining, agriculture, and livestock farming: A sustainability assessment in a developing country

Abstract

Purpose: To evaluate and classify the environmental and operational efficiency of Brazilian states, identifying best practices in sustainable development regarding the environmental impact of mining, agriculture, and livestock farming. Originality/value: This study’s relevance and originality revolve around analyzing real and updated data from 23 Brazilian states plus the Federal District, considering two national databases to assess sustainability performance. We also included relevant variables in our empirical model in terms of sustainability and economic impact. Design/methodology/approach: Data envelopment analysis (DEA) methodology was employed to analyze secondary data from 2018 to 2022 originating from satellite images of the Brazilian Annual Land Use and Cover Mapping Project (MapBiomas) and the Greenhouse Gas Emissions and Removals Estimation System (Sistema de Estimativa de Emissões e Remoções de Gases de Efeito Estufa [SEEG]). Each Brazilian state was considered a decision-making unit (DMU). We take as input variables the land use in mining, agriculture, and livestock sectors, while data on carbon dioxide (CO2) and methane (CH4) emissions were considered outputs. Results: The resulting ranking highlights the most efficient states in integrating economic activities with environmental sustainability. Amapá, Distrito Federal, and Rio Grande do Norte presented consistent efficiency, while Mato Grosso and Goiás emerged as the less efficient states in the Brazilian scenario, highlighting livestock farming as one of the main contributors to CH4 emissions. Contribution/implication: Our empirical findings can help policymakers and urban planners by supporting data-driven decision-making and investment strategies aimed at fostering sustainable, intelligent, and resilient cities and regions, especially in emerging economies.