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How AI is Helping Solve Climate Change Climate

Climate change is one of the biggest concerns the world is facing, and the problem continues to grow throughout the years. For the last few decades, the world has been experiencing shrinking ice sheets, glacial retreat, sea level rising, ocean acidification, and many more effects due to human activity and the emission of carbon dioxide into the atmosphere. According to scientists at NASA's Goddard Institute for Space Studies, a temperature analysis revealed that “the average global temperature on Earth has increased by a little more than 1° Celsius (2° Fahrenheit) since 1880.” Although one degree hotter does not sound significant, it takes a lot of heat and energy to warm the whole world and its atmosphere. In the past, “a one-to two-degree drop was all it took to plunge the Earth into the Little Ice Age.” Evidence shows that the main cause of this global problem is human activity.

Artificial Intelligence has played a significant role in climate change. While climate change has become a more urgent issue, technology around us has evolved significantly. Humans continue to develop new technological advancements and some, in fact, have played an integral role in solving climate change. From intersecting data science with climate science, scientists have been able to collect more precise data that will ultimately help officials develop informed climate policies and allow governments to take the necessary actions for change. These factors have helped improve climate change because they provide the accurate data needed to educate the public on the danger levels, and inspire the public to implement change into their daily lives. 

SilviaTerra, a precision forestry company, developed an innovative tree-counting strategy to determine the size and species of forests through satellite images. With Microsoft Azure, a cloud computing service, SilviaTerra combines field data with the satellite images to create detailed forest maps that allow them to evaluate the detailed features of trees in an area such as the height, species, and density. This AI-based solution maps every forest in the United States and has improved the management of large ecosystems by allowing landowners and officials to assess risks and health more sufficiently. This is important because forests are vital in helping solve climate change as they affect the amount of carbon dioxide in the atmosphere. With more growing forests, the carbon dioxide will decrease as it is absorbed by the leaves, wood, and soil. If the forests are burned, the carbon dioxide and other air pollutants stored will be released back into the air and can cause health hazards. 

IBM’s Green Horizon Initiative pushes for a greener environment by advocating for cleaner air quality and the use of renewable energy. In their strive towards cleaner air, IBM created an AI-powered system that provides accurate pollution and weather forecasts in hopes that others will lean towards a more sustainable future. The system combines the power from technology to collect data from thousands of sources including weather stations, satellite images, and traffic cameras to analyze and predict the areas that will be impacted by pollution. Because of the advanced algorithms, the system can also adjust based on the topography of the area and the seasonal conditions. These AI-based tools will be crucial in reducing air pollution and have already greatly impacted areas in China where air pollution, in the past, had been a record high. For instance, an air quality management system was developed where data collected early on allowed officials to enforce laws and regulations, and through cognitive modeling, the system created better models that adapted to different conditions like temperature and wind speed. Additionally, IBM Hybrid Renewable Energy Forecasting (HyREF) Solution takes the weather predictions and uses Big Data analytics to forecast the energy available to be redirected and stored, ensuring that less energy is wasted. China is the primary consumer of coal, and the system helped push the nation to integrate more renewable and alternative energy into its national grid. Using more renewable energy sources replaces the use of fossil fuels that releases carbon dioxide into the atmosphere, and will significantly reduce global warming emissions. 

Besides better data collection, AI has become a game-changer for other environmental issues and wildlife as well. For example, the Protection Assistant for Wildlife Security uses an algorithm to analyze past criminal history with poachers to predict areas where poaching could occur in the future. By adding caution towards areas of potential poaching, it not only saves the animals, but also helps climate change as well. Forests are important in reducing toxins in the air, but with species becoming extinct, the biodiversity decreases and forests become more vulnerable to climate change. Additionally, in agriculture, farmers face the problem of tractors destroying nutrients in the soil where crops grow. Thus, farmers tend to use nitrogen-based fertilizers that generate nitrous oxide, a greenhouse gas that warms the atmosphere 300 times more than carbon dioxide. AI and robots have helped farmers decrease the use of these fertilizers by managing these crops and using algorithms to determine the right time to plant certain crops. Computer vision through drones has also helped capture images of the large field for farmers to identify any problems or areas of improvement earlier and faster. 

In regards to energy, many companies have incorporated AI and machine learning into tools that help improve sustainability and efficiency. Google was able to reduce its use of energy by forty percent through machine learning by analyzing when users would most likely use platforms that utilize a lot of data to predict when cooling was needed most. Wind companies have implemented AI into the turbines’ propellers to adjust according to wind speed and direction, while also producing more electricity per rotation. 

Ultimately, AI and new technology has allowed for a better understanding of targeted areas and has helped improve climate predictions. They have been essential in the process of solving climate change, and hopefully one day, climate change will no longer be one of the biggest issues the world faces. 



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