Environmental twins could save us the day after tomorrow

Peter Fawcett Peter Fawcett
Principal, Environment and Planning
1 August 2023
6 min read

The 2004 blockbuster The Day After Tomorrow is a disaster movie that depicts the catastrophic consequences of global warming. While it presents an exaggerated and dramatised depiction of an impending global disaster, it also highlights how predictive modelling can be used to understand, anticipate, and respond to environmental changes – something that is extremely useful with the climate challenge we're facing today.

The film's protagonist, Professor Jack Hall is a palaeoclimatologist who, through computer simulations, predicted the onset of a new ice age triggered by human-induced climate change – but nobody believed him. With the amount of data that we generate every second, would the same happen today? We certainly hope not.

Today, there is a proliferation of monitoring systems collecting and generating vast amounts of data about our natural environment every single day. These include meteorological stations, satellites, and weather balloons, which collect data on temperature, precipitation, wind, humidity, and atmospheric pressure. 

We also have environmental sensors which measure air and water quality, soil conditions, and noise levels, as well as remote sensing instruments, which capture data about land cover, vegetation health, sea surface temperatures, and ocean currents. 

That is A LOT of data…but what are we using it for? Are we just all bark and no bite?

The sound of silence

As we welcome our eight-billionth person in the planet, the imperative to better understand and predict the environment – and act on what we know – is beyond critical. 

Environmentalists and scientists have warned of the risk of inaction since the publication of Rachel Carson's ground-breaking book, Silent Spring in 1962 that contributed to the establishment of the US Environmental Protection Agency and was instrumental to the development of contemporary environmental regulations and integrated pest management practices.

Of course, over the subsequent decades, agriculture, extractive industries, manufacturing, energy generation, infrastructure, and consumerism have continued to grow at pace. However, while the total absolute global wealth in 2022 reached US$516 trillion, only a small fraction of this is invested in alignment with environmental, social, and governance (ESG) principles. 

With virtually all global financial capital focused on maximising profit, it is no surprise environmental degradation persists at an alarming rate.

According to the UN-backed paper Action Plan for a Sustainable Planet in the Digital Age, digital solutions, including artificial intelligence (AI), big data, and the Internet of Things (IoT) have a great potential to address global challenges such as climate action, biodiversity conservation, circular economy, and poverty eradication, as well as drive evidence-based decision making for sustainable development.

Although to unlock this potential, collaboration between governments, private sector organisations, academia, and global institutions is needed to promote knowledge sharing, capacity building, policy coherence, regulatory frameworks, and technology transfer.

The challenge we face is not how to collect or generate and analyse environmental data – we already do and our ability to measure, record, catalogue, interpret, and predict almost any aspect of the natural world is improving exponentially with the aid of the Internet of Everything and AI. 

The real question is are we really making a difference through it? And if we aren't, the big question is: how?


Digital twins – a virtual or digital representation of a physical object or system – are not new to the building and construction sector. As one of our blogs has mentioned before: "The essence of digital twins is connectedness and big data". Businesses routinely use world-class solutions and software to create digital twins of the built environment, simulate real-world behaviour, and optimise the performance of physical assets.

In the not-too-distant future, as sophisticated models for predicting environmental change become smarter, more connected, and are refined and augmented by artificial intelligence, we will possibly be able to create 'digital twins' of the earth itself, or portions of it. Imagine what we could learn from having an 'environmental twin.' All of society would benefit, and we would come closer to achieving the UN's SDG goals through multistakeholder collaboration and cooperation. 

Things versus Everything

The IoT refers to the network of physical devices, vehicles, appliances, and other objects embedded with sensors, software, and connectivity capabilities that enable them to collect and exchange data without human intervention for the purpose of monitoring, automation, and analysis.

The Internet of Everything is a broader concept that extends beyond just connecting physical devices through the internet to also include the integration of people, processes, and data to create a more comprehensive and interconnected system that enables enhanced communication, collaboration, and decision-making.

Imagine our environmental twin powered by the Internet of Everything…

All stakeholders would have a comprehensive understanding of the current state of the environment, formed through analysis of complex data sets. Everyone would benefit from understanding how an environment is likely to respond to development or change. 

With greater awareness of the vulnerabilities in our environments and the potential impacts we might cause, we could implement interventions such as more sustainable land management practices, design more resilient infrastructure, or better protect vulnerable ecosystems. By simulating likely outcomes, environmental twins would permit decision makers to assess the effectiveness of proposed interventions before implementation.

Imagine a construction site where every aspect of the environment is continuously monitored with IoT devices, which feed data back to intelligent systems that can instantly advise on appropriate actions to meet compliance requirements or to drive nature-positive outcomes. 

Environmental twins could replace environmental management plans as we know them. 

Imagine a development precinct which has an environmental twin controlling the waste, wastewater, storm water, air quality, and soil inputs and outputs. It could enable a truly circular economy and make sustainable development a reality. 

Imagine if climate models could adapt quickly to environmental changes to provide updated simulations of potential consequences on ecosystems, land and water. Environmental twins could improve our understanding of complex climate change feedback mechanisms. Similar implementations and their benefits could be imagined at a state, national or even global scale. 

The effective use of environmental data would make a difference. 

A brave new world

Environmental twins have the potential to promote knowledge sharing, capacity building, policy and regulatory coherence, and technology transfer. Moreover, their insights would aid sustainable development and a more effective response to tackle climate change. 

However, technology alone will not solve our global environmental challenges. Nor is technology globally inclusive or without its negative impacts. The International Telecommunication Union estimates only 66 per cent of the world's population currently has access to the internet. One-third of the world's population is without an internet of anything. 

Electronic waste generated worldwide is estimated to exceed 74 million metric tonnes by 2030. Currently, less than 20 per cent of this e-waste is properly collected, treated, and recycled. Often, it is illegally dumped in countries such as Thailand, Vietnam, and the Philippines.

Ultimately, it will be up to leaders, organisations, and communities to lead change – to make proper use of integrated environmental data, maximise it, analyse it, and act. Unlike the leaders in the movie who dismissed Jack's theories, we must learn how to listen to what the data tells us and react before it's too late – or the day after tomorrow may not come.


Peter Fawcett
Written by
Peter Fawcett

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