The Role of Data Analytics in Combating Ocean Plastic

The Role of Data Analytics in Combating Ocean Plastic

Now that AI can help address business problems and machine learning can predict storm surges affecting coastal communities, it’s no surprise that more and more sectors of the economy are turning to data analytics. With the insightful information we get from data, we can face problems we had very little idea of how to approach before — including ocean plastic pollution.

As of now, the world’s ecosystems are suffering significant harm due to the unprecedented and expanding amount of plastic pollution. However, while all aspects of nature are affected, the ocean and its inhabitants suffer the most. Over 8 tons of plastic are thrown into the sea each year; by 2025, that amount is predicted to increase.

Where does data analytics fit into all of this? Read on below to find out how it can help with combating ocean plastic.

In recent years, we’ve seen rapid development in big data and machine learning-related technologies, creating new avenues for assessing and monitoring Earth’s resources. Additionally, these better tools and methods enable researchers to collaborate more effectively to share and analyze crucial environmental data.

Environmental scientists and groups can collect, clean, and analyze current data on plastic pollution using data analysis and data visualization technologies to better understand the causes, impacts, and magnitude of the problem.

With the help of data-backed marketing, the general public can also be given the information and visual materials they need to comprehend the severity of the problem, prompting them to act in any way they can. Taking this a step further, digital marketing analytics can help measure climate change-related marketing campaigns to accurately pinpoint what can be adjusted, making the campaigns even more effective.

All the waste in our oceans ends up amassing in trash gyres, most commonly known as ocean rubbish dumps. Right now, the “Great Pacific Garbage Patch,” which is thought to be more than twice the size of Texas, is the dump that receives the most attention. Unfortunately, though, this is not an isolated incident in any sense.

There are several ocean dumps of comparable size, and they are expanding at a startling rate. But with the help of data science, there are ways to address this significant problem. For example, ocean trash can be easily seen and tracked thanks to satellite imaging, which helps us understand the full scope of the catastrophe.

Though data science helps us understand the existing impact of plastic waste and forecast its future development, there are still things we don’t know. This makes appropriately recording data about plastic pollution a little tricky, given how it’s still growing and our limited understanding of its long-term effects.

Despite this, scientists can now better understand natural systems and ocean pollution patterns to optimize interventions due to AI algorithms and improved computing power. In addition, the democratization of AI and data science tools has made it possible for new environmental players to contribute important new insights to the field.

Take The Ocean Cleanup initiative as an example. The organization conducts extensive scientific research and data collection on oceanic plastic pollution, including two North Pacific Gyre trips. They then publicize the information and insights they have gathered through multiple scientific papers.

Because of their efforts, they have not only raised awareness but also successfully placed cleanup systems in ocean gyres to collect marine debris as the system is propelled by wind and current.

Big data can help large organizations identify the areas where waste is being produced so that they can develop solutions for waste reduction. This is especially helpful now as more conscious consumers ask for cleaner and more eco-friendly products.

Data reveals many things companies may otherwise overlook, such as valuable opportunities to reduce, reuse, and repurpose resources they might otherwise waste. For example, reusing not only helps decrease waste dumped into the ocean but can also save corporations money by lowering the number of new materials they will need to buy and replace discarded ones.

Companies can even go as far as thoroughly examining their waste management processes, including the kind, quantity, and disposal methods of plastic waste. Data analytics can then help them make decisions that will reduce their overall waste output, carry out an effective reusing convention, and take other eco-accommodating and financially sensible steps and measures.

Complex environmental and societal problems like ocean plastic waste cannot be miraculously solved by innovation and technology. However, by democratizing data science and encouraging everyone to use data analytics for good, these innovative solutions can empower individuals and organizations to make a difference for our oceans and the Earth.

For more news and insights on data science, AI, machine learning, and more beyond just combating ocean plastic, check out

Bash Sarmiento is a writer and an educator from Manila. He writes laconic pieces in the education, lifestyle, and health realms. His academic background and extensive experience in teaching, textbook evaluation, business management, and traveling are translated in his works.

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