Problem Example

Data science can be used for many things, such as solving environmental challenges, acknowledging climate change, and helping support sustainable development. Let’s take a look at a concrete example of how this is being done.

As you are likely aware, one of the major factors driving climate change is increased CO2 emissions. These CO2 emissions come from many sources, a major one of them being fossil fuel consumption. It therefore, makes sense to limit the use of fossil fuels, to decrease CO2 emissions across the board and limit the damage this does to the environment. Laws, rules, and incentives need to be developed and updated with the objective of reducing negative climate effects.

But how can we control and limit something that comes from so many different sources all over the world?

This is where data science comes in. Data science gives us the tools to track and analyse data in novel and powerful ways.

One such example is the UN Regulation No 2019/631 which requires every UN Member State to, with the help of AI and data science, record information for each new passenger car. Every year, this information is submitted to the Commission. This data contains details such as manufacturer name, specific emissions of CO2, vehicle mass, wheelbase, track width, engine capacity and power.

There are regular quality checks that help ascertain the accuracy and quality of the dataset before it is published and manufacturers are given the chance to review the data and report possible errors before the final data is published.

The data collected from this can help us find out just how bad the problem is, track developments over time, and make necessary changes and efforts to direct behaviours and car usage toward more sustainable alternatives. Manufacturers are informed about their CO2 performances and incentives are offered for reducing emissions, which drives the development of companies and technology in a direction that is more sustainable and less damaging to the climate.

Normally, there would be no realistic way to collect and process such immense amounts of data required for this to happen, but now the possibility is there to access this information, increase our understanding, and improve our practices thanks to data science. With the help of data science techniques, we are able to collect massive amounts of data (big data), conduct efficient analysis and visualize the results in a way that supports concrete actions.

CO2 emissions from vehicles is only one of many examples where data science lets us leverage the power of technology to figure out how we can improve the climate and prevent negative climate effects.

You will learn more about these kind of examples in the last week of this course (i.e., Week four)

You can find more information and access the detailed and visualized data charts on the European Environment Agency’s website here: https://www.eea.europa.eu/data-and-maps/data/co2-cars-emission-22