Valorization of municipal solid waste (MSW) for energy represents a strategic alternative for developing countries, as it mitigates emissions, reduces pressure on landfills, and diversifies the electricity matrix. This study quantified the potential for electricity generation from MSW in the Jequitinhonha Valley, Minas Gerais, Brazil, using primary gravimetric characterization data, a method rarely employed in tropical areas. The identified composition showed a predominance of the organic fraction (47.6–73.3%), confirming the relevance of biological routes. The results indicated a consolidated potential of 106,640 MWh·year⁻¹, of which 94.7% was from biogas recovery and 5.3% from incineration. Almenara, one of the three locations analyzed, showed the highest potential (48,200 MWh·year⁻¹), followed by Diamantina (34,540 MWh·year⁻¹) and Capelinha (23,900 MWh·year⁻¹). The specific yields ranged from 0.33 to 0.53 MWh·ton⁻¹ MSW and the per capita indicators from 1.01 to 1.49 MWh·cap⁻¹·year⁻¹. The climate mitigation potential reached 1.0 Mt of CO₂eq·year⁻¹. It is concluded that valorization in the Jequitinhonha Valley should prioritize biogas recovery, complemented by the incineration of rejects. The materialization of this potential requires advancements in infrastructure, selective collection, and socio-productive inclusion. This study provides evidence for public policies and contributes to the literature by demonstrating that valorization can boost energy transition and socio-environmental equity in developing tropical regions.

Climate variability and extreme events disproportionately affect rural regions with limited adaptive capacity. In Minas Gerais, Brazil, mesoregions with semi-arid characteristics face severe vulnerabilities, underscoring the importance of detailed regional climate trend analyses. This study analyzed historical air temperature (maximum, minimum, and average) and precipitation from 1990 to 2019 in four mesoregions of Minas Gerais. The goal was to support climate planning and the development of local responses. Daily data from the National Institute of Meteorology (INMET) and a gridded meteorological database were analyzed using Mann–Kendall and Sen’s non-parametric tests, with a 95% confidence level (p-value ≤ 0.05) to identify significant trends. Annual results showed significant increases in maximum temperature in 15 of 24 evaluated areas, with rates from −0.03 to +0.15 °C year⁻¹. For minimum and average temperatures, significant increases were observed in 17 locations. Annual precipitation showed a downward trend in 21 areas. Monthly and seasonal analyses confirmed this pattern of warming and reduced rainfall. These findings indicate an intensification of climate stress in over 80% of the studied locations, potentially impacting agriculture, public health, and ecosystems, requiring specific regional adaptive responses.