First held back in 1974, World Environment Day has become a powerful way for the United Nations to engage with “governments, businesses and citizens in an effort to address pressing environmental issues.” This year, a key theme is #GenerationRestoration and also sees the launch of the UN Decade on Ecosystem Restoration: a global rallying cry for everyone to do their part in healing the planet.
Back in the 70s, the prospect of a looming global environmental crisis was, for most people, simply not among the major issues of the day. Experts and activists aside, few could have imagined the pace at which events would develop and how urgent the need for action would become.
In a similar way, half a century ago, the idea that technology could have a positive impact on protecting the planet was much closer to science fiction than reality. Today, however, the world looks to digital innovation as one of the main strategies to combat climate change, with data science among the industries now playing a vital role on both a macro and micro scale.
Globally, data scientists blend human expertise with technology to assess data and review the impact of problems causing climate change. This insight informs government policy, which then filters across the economy and society to deliver meaningful impact. In the UK, for example, it is now national policy to cut carbon emissions by 78% by 2035, and data science will play a key ongoing role in the further development of policies in the years ahead.
On a day-to-day basis, businesses everywhere will need to make a major contribution if this target is to be reached. The sustainability of every organisation depends on addressing the impact of its operations across the supply chain. Everything from water consumption, pollution and plastic reduction, to carbon emissions, waste and recycling, is part of the equation – and data science modelling is increasingly being used by businesses to assess the likely impact of their actions and the quality of decision-making.
In recent years, the Mango team has worked on sustainability projects to monitor and measure world poverty, reduce water waste and to understand the proportion of electricity generated using low-carbon sources. We remain committed to broadening the availability of data science expertise and technology to make a difference to ensure data science empowers #GenerationRestoration.
Delivery by Mango
Protecting and preserving biodiversity
Mango built and mentored several data science production projects across the ONS including the United Nations funded Sustainability Development Goals, a system to monitor and measure world poverty based on 19 sustainable goals, from ending hunger and poverty to achieving sustainable energy and gender equality to protecting and preserving biodiversity. Data science is a powerful tool which can be used to inform businesses and improve their water consumption as well as having world-wide applications in reaching the UN targets of providing clean, accessible water to all.
Reducing water waste
Mango helped i20 realise their data capabilities but develop a solution that greatly improved the performance of their smart network solutions, leading them into the world of AI and data analytics. This has enabled water companies to shift to conditional based maintenance and reduce the number of water leaks. One client reduced leakage by 15% in the north of their city within 2 weeks of using the solution.
Enabling the adoption of renewable energy
Britain’s first all-digital, renewable energy supplier Pure Planet choose to work with Mango to harness their data to drive data-driven pricing solutions and help to drive service efficiency. Mango added value in terms of broadening the scope and skills of the data science team and in helping them to establish common frameworks and processes to make data science easier with repeatable and scalable models.
Assessing the proportion of low carbon sources of energy
Mango were involved in a project that assessed the proportion of electricity generated using low-carbon sources including solar, wind, hydro or nuclear. All the data and deployment workflows were developed to schedule daily updates of carbon intensity data and re-deploying the app when the data was pushed to main branch.
Data science is used widely in business as an integral part of a businesses to positively impact change in a number of ways https://earth.org/data_visualization/ai-can-it-help-achieve-environmental-sustainable/
Data scientists, looking to add their support to the wider effort to protect the environment, can get more information from the Open Sustainable Technology website which provides a list of all sustainable, open, and actively maintained technology projects worldwide and details of how to get involved.