Numbers aren’t good storytellers
Numbers are supposed to make things clearer. But when it comes to climate and environmental issues, they often do the opposite.
We’re told something uses gigawatts of energy, tons of CO₂e, or millions of gallons of water. Technically accurate, yet for most people, completely ungraspable, meaning that they float in abstraction rather than paint the picture they were intended to. So we translate them. We turn emissions into “miles driven in a car” or water use into “Olympic swimming pools.” It feels helpful, but often it leaves us just as lost—because it gives us scale without consequence.
And that’s the problem: when numbers aren’t anchored to something meaningful, they stop informing us and start misleading us. Climate change hasn't always been told in ways that is intuitive or resonates with our daily lives. While the climate statistics aren't wrong, the stories and context behind them are very difficult to tell.
‘Hundreds of football fields’ worth of metaphors
It’s tempting to translate these confusing metrics to everyday activities, in order to make them more digestible. A common ask from clients is to translate tons of CO₂e into daily activities, like miles driven in a car. But while that equivalence offers scale, it tells is us little about consequence. Something being equivalent to driving around the world twice doesn’t really tell us about its impact, nor is it realistic.
The trouble with these kinds of metrics are not only that they don’t describe consequences, but they can be confusing, with many under or overestimating the resources that everyday activities use. For example, there is a lot of debate around AI’s water use, with its data centers consuming enormous amounts of energy and water every day. Whilst we don’t have the exact numbers, using OpenAI’s per query estimates, and at 2.5 billion queries a day, this would mean that ChatGPT has an annual water footprint of 77.6 million gallons. Multiple infographics in the press compare this water usage to bathtubs (120 million in Google's case) or Olympic pools.
But those equivalences fall short. They provide visuals without providing meaning, and without a benchmark. Running the numbers, we found that a year of ChatGPT queries – 1.3 million bathtubs- uses as much water as irrigating all the golf courses in the UK…for less than a month.. And golf, despite its Eden-like image, carries its own heavy costs in biodiversity loss, water consumption, and pesticide use. Yet golf rarely provokes such outrage. Why? Because it looks harmless, low-impact. Because its framing feels idyllic. When data fails to provide a benchmark or a consequence, it can be at best confusing, and at worst, obfuscate big issues.
There are multiple examples of this phenomena
Streaming’s carbon footprint: Usually compared to miles driven, but rarely to other leisure activities with similar costs - like running air conditioning for comfort or attending a live game.
Cryptocurrency mining energy: Often equated to the energy use of ‘small countries’, but seldom to the financial systems it aims to replace such as banks, ATMs, data networks.
Fast fashion’s water use: Commonly expressed in Olympic pools. But given a pair of jeans has the same water impact as eating four hamburgers, it might be more appropriate to compare instead to the foods we consume daily'
Each example shows the same problem: what we use to scaffold facts changes their interpretation. We reach for familiar metaphors instead of meaningful ones, and in doing so, obscure what’s truly at stake.
Toward better impact communication
Numbers don’t speak for themselves. They require framing, and framing decides whether we understand or ignore what’s being said. Here are five ways to better anchor environmental metrics to their real world impact:
1. Choose consequence over equivalence.
Instead of saying that something requires 50,000 bathtubs’ worth of water, describe how that amount of water could sustain a community of X people for a week, or that consistently depleting resources at that rate could put 15 species at serious risk of harm. Real issues require real stories.
2. Don’t be afraid to benchmark.
Whilst benchmarks are imperfect, they increase literacy on the impacts of everyday activities. By comparing something to another action (like the hamburger/denim example), it becomes more tangible than relying solely on the metrics.
3. Make it personal.
Abstract futures don’t move us. Immediate, tangible consequences - health lost, time shortened, landscapes changed - do. As a personal example, the fact that struck me most as an ex-smoker wasn’t the statistics on cancer rates, but hearing that each cigarette smoked shortens your life by about 22 minutes (UK Department of Health). This was immediate, personal, and tangible.
4. Question the frame itself.
Why are environmental harms measured in Olympic pools, while others use football fields? Are some metaphors unconsciously biased towards certain age groups, genders, or cultural backgrounds? Every framing carries meaning.
The bottom line
The numbers themselves are neutral. But the frames we choose shape reality, They determine what we notice, what we dismiss, and what we decide to change.
Framing won’t solve climate change, but in an age where climate-fatigue and scepticism makes it easier to ignore the facts than face them, it becomes more important than ever to position information in a way that feels personally measurable, relevant, and impactful.