How AI is changing the way we track greenhouse gases

The fight against climate change is real. It is important to know just how much greenhouse gas is being pumped into the atmosphere. This is where life cycle assessment comes in. It is a way to measure the environmental impact of a product from start to finish. From the moment raw materials are dug up to when the product is thrown away. This process is not easy. It is hard to track emissions that a company does not control directly. Experts use something called emission factors. These are estimates of greenhouse gas emissions for a specific activity. They help figure out the indirect impacts. But here is the thing. Picking the right emission factors is a pain. It takes a lot of time and can be full of mistakes. Plus, it needs someone who knows what they are doing. There is a new way to do this. It uses artificial intelligence. This AI can look at data and suggest the best emission factors. It can even explain why it picked them. The AI can work in two ways. It can give a list of suggestions for an expert to pick from. Or it can just pick the best one on its own. Tests show that this AI is pretty good at its job. When it works alone, it picks the right emission factor 86. 9% of the time. And when it gives a list, the right answer is in the top 10 suggestions 93. 1% of the time. This is a big deal. It means companies can track their greenhouse gas emissions more accurately and quickly. This helps them work towards their sustainability goals. It also helps industries move towards net-zero emissions. But, it is important to remember that this AI is a tool. It should not replace human experts. Instead, it should help them do their jobs better. It is also important to think about the data that the AI uses. If the data is not good, the suggestions will not be good either. So, it is crucial to have high-quality data. This way, the AI can make the best suggestions possible.