A Study on Artificial Intelligence-Driven Solutions for Climate Change Forecasting and Mitigation Strategies

Abstract

Detailed weather predictions, faster discovery of pollution sources, and better planning to reduce harm to the environment Artificial Intelligence, or AI, is quickly changing how climate science works. It helps with more. This paper shares a new study that's ready for a conference. It brings together information from published research, technical reports, and global climate and pollution data to look at how AI is used in predicting climate changes and helping to fix environmental problems. We reviewed a lot of recent studies from 2018 to 2025 and looked at data and results from those studies to find out how well different AI methods work, what techniques are commonly used, and where there are still challenges. We found that (1) models that mix physics with AI usually do a better job at predicting local weather and extreme events than just using statistics; (2) AI tools that look at satellite images are getting better at quickly finding places where methane and carbon dioxide are coming out in large amounts; and (3) AI-based learning and planning tools can help reduce pollution in simulations of energy use in power grids and buildings. However, there are still some big issues, like not enough testing in areas with little data, mixed approaches to measuring uncertainty, and not enough focus on fairness and how decisions are made. We end with a clear plan for analyzing data using secondary sources, suggestions for making these tools work in real life, and a list of research ideas to create fair and dependable AI tools for climate work. All references are provided in APA style, and more about the role of AI in this area is included.