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environmental implications of artificial intelligence applications in the production of chemical products

Chemical products play an important role in our society. From cars and medicines to toys and clothes, they can be found in a wide variety of daily necessities. But the production of these substances can have adverse effects on the environment, including emissions of greenhouse gases into the atmosphere.

Fortunately, however, the chemical manufacturing industry has a new tool that can help reduce its environmental footprint: artificial intelligence.

Artificial intelligence (AI) is a branch of computer science, which focuses on manufacturing machines and processing programs. It can perform tasks that usually require human cognitive ability, such as learning and solving problems. Although this sounds like science fiction, AI has promoted many programs and services that make our lives easier and more efficient. This includes voice assistants like Apple’s Siri, Google’s assistant, Amazon’s Alexa and Microsoft’s Cortana.

In the past decade or so, the chemical industry has adopted or developed artificial intelligence to improve operational efficiency, reduce costs and improve customer satisfaction. Now more and more companies are using these technologies to reduce greenhouse gas emissions and improve energy efficiency in the production process, according to Dr. Yuan Yao, assistant professor of sustainable forest biomaterials science and Engineering Department of NC State University natural resources.

The results show that the chemical industry accounts for about 10% of the total global energy consumption and 7% of the total greenhouse gas emissions. According to the U.S. Environmental Protection Agency, the chemical industry has produced more than 800 million tons of greenhouse gas emissions since 2011.

Greenhouse gases (carbon dioxide, methane, nitrous oxide, etc.) trap solar radiation in the earth’s atmosphere, warming the earth enough to sustain life. However, since the industrial revolution at the end of the 18th century and the beginning of the 19th century, the concentration of these gases emitted into the atmosphere has become higher and higher, leading to the rise of global surface temperature and climate change.

Yao Yao said that artificial intelligence showed great potential in reducing chemical energy consumption and environmental footprint. For example, Borealis, the world’s eighth largest producer of polyethylene and polypropylene, has deployed an artificial intelligence program to set dynamic targets for plant energy consumption and improve plant energy use, thereby reducing emissions and costs.

Unfortunately, despite the growing awareness and exploration of AI in the chemical industry, quantifying the benefits and impacts of these emerging technologies is challenging due to the lack of reliable performance data.

Yao Jian said that it is also difficult for many enterprises to match the appropriate evaluation methods and performance indicators with the different and complex applications of artificial intelligence in the chemical industry. This could hinder policymakers and early adopters, whose investments are crucial to accelerating the deployment of AI.

Professor Yao’s research focuses on developing systematic, scientific and rigorous methods to support engineering and policy decisions for sustainable industrial development. He is leading a study to address these methodological and data gaps.

The research, funded by the Alfred P. Sloan Foundation, aims to develop an indicator based framework to guide decision makers in selecting appropriate assessment methods and performance indicators to quantify the energy and environmental impacts of AI applications in the production of chemical products. Collaborators include the Institute of environmental law, the University of California, Berkeley and Yale University.

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