Artificial Intelligence and Environmental ChallengesLeskovar, Robert T. (Urednik) artificial intelligencemachine learningenvironmental issuesCO2 emissionsPM2.3 particlesriskfailurerenewable energywind turbinesolar power plantedge AIThis volume examines where artificial intelligence can provide genuine insight into environmental problems, and at what cost. Across eight chapters, contributors apply machine learning, deep learning, econometric modelling, and computational simulation to a range of pressing challenges: forecasting wind and solar energy output, deploying efficient AI on resource-constrained edge devices, quantifying risk in sustainable finance, detecting faults in photovoltaic installations, analysing air quality and CO₂ emissions data, simulating nanoplastic interactions with biological systems, and modelling urban heat transfer. A recurring theme is the critical importance of data quality — sparse, biased, or poorly curated datasets remain a fundamental obstacle to trustworthy modelling. The volume equally emphasises interpretability, recognising that environmental decision-making is ultimately a human and political process. Taken together, the chapters offer an honest, domain-grounded assessment of the current capabilities and limitations of AI as a tool for addressing environmental challenges.University of Maribor, University of Maribor Press20262026-06-18 09:56:07Znanstveno delo98526sl