Atmospheric Corrosivity in Electric Power Transmission Towers: Limitations of Traditional Technical Specifications and the Challenges of Climate Changes

Selecting materials for metallic structures such as transmission towers requires careful consideration of environmental dynamics, climate change, atmospheric variations, and human activity, all of which directly affect corrosion behavior. Relying on generic or incomplete data can lead to premature material degradation and increased maintenance costs. This study focuses on a 1,150 km transmission line spanning the Brazilian states of Ceará, Piauí, and Maranhão, where material selection was initially based on theoretical estimates of atmospheric aggressiveness (C3 category). However, frequent maintenance and component replacements indicated underestimated corrosivity. To improve understanding, environmental parameters (humidity, salinity, precipitation, and wind) were monitored, and field corrosion rates were determined using AISI 1020 and galvanized steel samples. Complementary analyses included electrochemical testing, microstructural evaluation, and accelerated aging under industrial and saline conditions. Additionally, an artificial intelligence tool based on feedforward neural networks was developed to enable rapid corrosivity classification through RGB/HSV image analysis, without requiring long-term field exposure or specialized equipment. After one year, the environment was reclassified as C5–Cx (extreme aggressiveness). These results highlight the importance of location-specific assessments over general assumptions and demonstrate how AI-based tools can enhance decision-making and maintenance strategies for more resilient power transmission infrastructure in a changing climate.