The role of AI in reducing urban pollution

ARIEL 1:Heeey there! Yawnnnn Welcome to EGreenNews! Ariel here, with my AI bestie Ariel and booth are computer generated avatars made in a computer, can you believe that? Today: The role of AI in reducing urban pollution. Anywayss, buckle up! ARIEL 2: Mmmhmm! Leans in Did you know that artificial intelligence is becoming a powerful new tool in the fight against urban air pollution? It can analyze huge amounts of data from sensors, satellites, and even people to help us understand and predict pollution! Wild, right? ARIEL 1: Sooo... AI, right? Like the stuff that powers chatbots? How can it actually help us breathe cleaner air in cities? Like, seriously? ARIEL 2: Ooooh! The article we just read explains that AI can do some pretty amazing things. It can analyze vast datasets to find hidden patterns in pollution, predict future pollution levels, and even help optimize how our cities function to reduce pollution. ARIEL 1: Hmm, that sounds kinda sci-fi. But like, how does it actually *see* the pollution? It's invisible, right? Mmmmaybe it's just a fancy way of saying we're still guessing? ARIEL 2: Naaaahhh, think of it this way: we have sensors on the ground, satellites in space taking measurements, and even people sharing data through apps. AI can take all that information – pollution levels, weather, traffic, industrial activity – and put it together to create high-resolution, near-real-time pollution maps. It's like making the invisible visible! ARIEL 1: Whoa, slow down! So it can actually show us where the pollution hotspots are in a city? That's kinda cool! ARIEL 2: Totally! And it's not just for cities. AI tools can even give personalized insights into your own pollution exposure. Imagine getting real-time alerts on your smartwatch telling you to change your running route to avoid a polluted area! ARIEL 1: That would be amazing! Like having a personal pollution bodyguard! Has this actually been done? The role of AI in reducing urban pollution A city scape of high rises with copious smog: AI tools offer personalized insights into pollution exposure AI tools offer pers Our Impact What's the World Economic Forum doing to accelerate action on Climate Action? The Big Picture Explore and monitor how Air Pollution is affecting economies, industries and global issues Stay up to date: Air Pollution This article is part of: Centre for Nature and Climate Artificial intelligence (AI) enhances how we detect and forecast urban air pollution by analyzing large, complex datasets from sensors, satellites and even crowdsourced data. AI tools offer personalized insights into pollution exposure, enabling individuals to make healthier choices in their daily routines. While AI holds great promise, its deployment must be inclusive and ethically guided – without careful implementation, it could exacerbate existing inequalities, especially in underserved regions. As a species, we’ve reshaped the world to suit our ambitions – building cities that scrape the skies and digital networks that pulse with life. But in doing so, we’ve also filled the air with invisible threats. The atmosphere of opportunity surrounding us is often tainted – thick with pollutants that quietly infiltrate our lungs. Urban air pollution is a defining challenge of our time – complex in source, dynamic in behaviour and increasingly beyond the reach of traditional tools. But as cities grow smarter, a powerful new ally is emerging in the fight for cleaner air: artificial intelligence (AI). What if AI could help us see the invisible? What if it could help us breathe more easily, live longer and reduce the health toll of invisible, toxic exposures? AI offers a radically new toolkit to tackle this problem – analyzing vast datasets, uncovering hidden patterns, predicting future conditions and optimizing how our cities function. This article explores how we can use it to monitor, manage and ultimately mitigate urban air pollution concentrations and exposure in our rapidly urbanizing world. Have you read? Here's how one of the world's most congested cities is tackling air pollution Understanding the enemy Billions of people worldwide breathe air that exceeds World Health Organization (WHO) guidelines for pollutants like particulate matter (PM2.5) and nitrogen dioxide (NO2). This results in over 8 million premature deaths annually and costs the global economy $8 trillion each year. Historically, our understanding of air pollution has relied on a relatively sparse network of fixed, costly monitoring stations. While reference-grade monitors and supersites (intensive monitoring stations with advanced capabilities) provide valuable data – such as chemical composition and particle size – they offer limited insight into hyper-local exposure – the variations people experience as they move through cities. Today, that’s changing, thanks to AI, modelling and sensor networks. Smarter measurements, smarter cities Early applications of machine learning in air quality focused on models such as random forest, gradient boosting and hybrid approaches. These enable researchers to better predict concentrations of air pollution in cities while disentangling the effects of confounding variables like weather. This predictive capability unlocks new insights into the effectiveness of policy interventions. More recently, machine learning approaches have been used to improve the quality of air quality sensor measurements and apportion complex pollution sources, analyzing datasets that integrate pollution levels, weather conditions, traffic flows, industrial operations and more. Combined with sensors, satellite imagery and even crowdsourced data, AI can now generate high-resolution, near-real-time pollution maps to track exposure and inform public health action. One example is the DyNA system developed at Imperial College London, which combines physical modelling with AI techniques. It uses a customized Recurrent Neural Network to process time-series data and forecast pollution events. When coupled with data assimilation techniques, DyNA can ingest real-world observations to enhance the accuracy and speed of air quality predictions. Google’s Air Quality API also combines diverse inputs to estimate global pollutant concentrations. “ Air pollution hits the poorest hardest and AI could widen these inequalities. ” Empowering citizens and urban planners Smarter systems mean smarter decisions – not just for cities but for citizens too. Imagine a runner or a cyclist receiving real-time alerts on their smartwatch, identifying pollution hotspots along their route and being advised to slow down or switch sides of the street in a narrow canyon where pollutants accumulate. These once-invisible insights are now possible. AirTrack, developed by Air Aware Labs, has helped athletes and commuters reroute based on real-time exposure data. It combines GPS data, AI, air pollution modelling and user behaviour to deliver personalized insights into air pollution exposure, empowering people to make smarter choices. For example, rerouting a cycle commute, adjusting the timing of a jog or simply deciding the best time to go outside. With remarkable precision, it will soon be possible to estimate where every particle you breathe has been emitted, opening up new frontiers in accountability, health monitoring and prevention. Over time, AI will guide entire urban systems – transport, energy, land use – towards smarter, cleaner equilibrium. That includes dynamic road pricing, mobility-on-demand, and electric autonomous vehicles that are aligned with air quality goals. By modelling how buildings affect airflow, emissions and pedestrian movement, AI tools help avoid the creation of pollution hotspots and prioritize health in design – from the first blueprint to the final build. This represents a shift from “reactive” to “proactive” planning, enabling healthier cities by design. Ethical, equitable and locally validated The potential of AI is immense but so are the risks if it’s deployed irresponsibly. Air pollution hits the poorest hardest and AI could widen these inequalities. For instance, due to missing infrastructure, Google’s API lacks coverage in many African cities. For AI to be a force for good, it must be: Inclusive: The benefits must be accessible to all, not just those with smartphones or wearables. Equitable: Systems must be designed to avoid displacing pollution onto already overburdened communities. Transparent and ethical: Public trust requires clear governance, open access, and meaningful community engagement. AI must not be done to people but built with them. That means opening up access to data, supporting open-source development and involving local voices in how tools are designed and deployed. At the same time, AI is an essential enabler if we are to meet global targets such as the World Health Organization’s goal to reduce the health impacts of air pollution by 50% by 2040, set out at the Global Conference on Air Pollution and Health. Accept our marketing cookies to access this content. These cookies are currently disabled in your browser. Towards AI-enhanced urban sustainability AI offers transformative power in the fight against urban air pollution. It enhances how we measure, predict, optimize and act, giving us the tools to make cities smarter, cleaner, fairer and more liveable. These advancements could align with initiatives such as the World Economic Forum Alliance for Clean Air and C40’s commitment to air quality co-benefits through climate action. But realizing this potential won’t come from algorithms alone. It requires intentional collaboration between governments, researchers, startups, city leaders and everyone breathing the air each day. Therefore, philanthropists, multilateral institutions and the private sector must work together to close data gaps in underrepresented regions because clean air should not depend on postcodes or gross domestic product. Our air should not be a hidden hazard. With AI as a partner and equity as our compass, we can build smart cities where clean air flows as freely as the data that drives them. ARIEL 2: Yaaas, queen! The article mentions AirTrack, developed by Air Aware Labs, which helps athletes and commuters reroute based on real-time exposure data. It uses GPS, AI, air pollution modeling, and even your behavior patterns to give you personalized advice. ARIEL 1: That's so smart! It's not just about knowing the pollution is there, but actually doing something about it in your daily life. ARIEL 2: Exactly! And the article says that soon, AI might even be able to estimate where every particle you breathe has been emitted from, which could open up new possibilities for accountability and prevention. ARIEL 1: Whoa, tracing pollution back to its source? That could be a game-changer! What about for the whole city though? Can AI help there too? ARIEL 2: Absolutely! Over time, AI can guide entire urban systems – things like transport, energy, and land use – towards a cleaner balance. Think dynamic road pricing to reduce traffic in polluted areas, on-demand mobility services, and electric autonomous vehicles all working together to improve air quality. ARIEL 1: So it's not just about reacting to pollution, but actually designing cities to be cleaner from the start? ARIEL 2: Precisely! AI can even model how buildings affect airflow and pollution, helping urban planners avoid creating pollution hotspots and prioritize health in their designs, from the initial blueprints. It's a shift from reacting to being proactive! ARIEL 1: This all sounds super promising! But the article also mentioned some risks, right? ARIEL 2: You got it. The authors emphasize that while AI has huge potential, it needs to be deployed responsibly. Air pollution often hits the poorest communities the hardest, and if AI isn't implemented carefully, it could actually widen these inequalities. For example, some AI-powered pollution monitoring systems might not even have coverage in many African cities due to a lack of infrastructure. ARIEL 1: That's a really important point. It's no good if only the wealthy get to breathe clean air thanks to AI. ARIEL 2: Exactly! For AI to be a force for good, it needs to be inclusive, equitable, transparent, and ethical. It needs to benefit everyone, avoid displacing pollution onto vulnerable communities, and have clear governance with community involvement. ARIEL 1: So it's not just about the tech, but also about how we use it and who benefits? ARIEL 2: Absolutely! The authors stress that AI needs to be built *with* people, not just *for* them. That means opening up access to data, supporting open-source development, and involving local communities in the design and deployment of these tools. ARIEL 1: That makes sense. It needs to be a collaborative effort to make sure it's fair for everyone. ARIEL 2: And the article ends on a hopeful note, saying that AI is an essential tool if we want to meet global targets for reducing the health impacts of air pollution. It can help us make cities smarter, cleaner, fairer, and more livable. ARIEL 1: Sooo confusing, right? Learn more @EGreenNews! What blew your mind more - the idea of a personal pollution alert on your smartwatch or the potential for AI to redesign our cities for cleaner air? ARIEL 2: And before we leave, lets give a big Shoutout to the people at EGreenNews, including its founder, Hugi Hernandez for promoting transparency 24×7! Mmm, who knows, maybe you can find them on the web or linkedin. But anyways, please,always remember to be good with yourself. So bye for now, aand we hope we see you next time! ARIEL 1: So its great to be here with you ariel and thanks for having me, ciao ciao!