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GLOBAL DIMMING: HOW TACKLING AIR QUALITY EXACERBATES GLOBAL WARMING


Global dimming refers to the observed reduction in sunlight reaching Earth’s surface, primarily due to atmospheric pollutants like sulfate aerosols.


These particles, resulting from industrial activities, refl ect and absorb solar radiation, leading to a cooling effect that has, to some extent, masked the full impact of greenhouse gas- induced warming.


As efforts to improve air quality reduce these pollutants, we face a paradox: the diminished cooling effect reveals the true extent of global warming, potentially accelerating climate change.


What is global dimming?


From the 1950s to the 1980s, scientists observed a decline in solar irradiance at Earth’s surface, a phenomenon termed “global dimming.” This trend was largely attributed to increased industrial activity that released signifi cant amounts of aerosols into the atmosphere.


These aerosols scatter and absorb sunlight, leading to a net cooling effect. Additionally, they infl uence cloud formation, increasing cloud refl ectivity and further reducing the amount of solar energy reaching the surface.


However, since the 1980s, efforts to reduce air pollution have led to a decrease in aerosol emissions, resulting in a phenomenon known as “global brightening.”


While benefi cial for public health and ecosystems, this reduction unearths a paradox: the cooling effect of aerosols has been masking the full extent of global warming. As aerosol levels decrease, the suppressed warming is unleashed, potentially leading to a more rapid increase in global temperatures.


A paradox of climate action


Efforts to mitigate air pollution have led to a reduction in aerosol emissions, resulting in a phenomenon known as “global brightening.” While benefi cial for public health and ecosystems, this reduction unearths a paradox: the cooling


effect of aerosols has been masking the full extent of global warming. As aerosol levels decrease, the suppressed warming is unleashed, potentially leading to a more rapid increase in global temperatures.


Reducing aerosol emissions is essential for improving air quality and public health. However, without simultaneous and aggressive reductions in greenhouse gas emissions, the decrease in aerosols could lead to an abrupt and severe acceleration of global warming. This scenario underscores the urgency of comprehensive climate strategies that address both air quality and greenhouse gas emissions.


Measuring vertical aerosol dispersion in Switzerland. CC BY-SA 4.0: Julie Schmale.


In a painful irony, improving global air quality through regulation and decarbonising could actually raise average surface temperatures by counteracting a phenomenon called ‘global dimming’.


This, from the latest Assessment Report from the Intergovernmental Panel on Climate Change, lays out the numbers of this paradox:


‘It is likely that well-mixed GHGs contributed a warming of 1.0°C to 2.0°C, other human drivers (principally aerosols) contributed a cooling of 0.0°C to 0.8°C’1


Does global brightening necessitate geoengineering?


In response to this challenge, some scientists have proposed solar geoengineering techniques, such as stratospheric aerosol injection (SAI), to artifi cially enhance Earth’s refl ectivity and counteract warming.


SAI involves releasing refl ective particles into the stratosphere to mimic the cooling effects of volcanic eruptions. While theoretically effective, this approach carries signifi cant risks, including disruptions to global weather patterns, impacts on agriculture, and the ethical dilemma of intentionally modifying the climate.


Moreover, reliance on geoengineering does not address the root cause of climate change—greenhouse gas emissions—and could lead to unforeseen consequences if not carefully managed.


The phenomenon of global dimming highlights the complex interplay between air pollution and climate change. As we strive to improve air quality through the reduction of aerosol emissions, it is imperative to simultaneously implement robust strategies to reduce greenhouse gas emissions.


Failing to do so could result in the unintended consequence of accelerated global warming, exacerbating the very challenges we aim to mitigate. This paradox serves as a stark reminder of the need for comprehensive and integrated approaches to climate policy.


1


Summary for Policymakers. Sixth Assessment of the Intergovernmental Panel on Climate Change. 2022.


Affordable AI-powered air pollution sensors could transform air quality monitoring


A new study from Kingston University suggests that affordable, AI-driven air pollution sensors could revolutionize the way we monitor air quality, offering more accurate and accessible data about pollution levels in local areas.


The research, published in Sensors journal by MDPI, investigates how integrating artifi cial intelligence with compact, cost- effective electrochemical sensors could improve the precision of air quality monitoring. These portable devices—roughly the size of a mobile phone—provide real-time, on-the-ground air quality measurements that can be taken anywhere.


Current air quality monitoring systems are costly, immobile, and too sparse to give accurate readings of the air quality in specifi c locations. As a result, data from the nearest stationary station may not refl ect the conditions people experience in their immediate environment. Air pollution is responsible for seven million deaths globally each year, according to the World Health Organization, with children particularly vulnerable due to their developing lungs, weaker immune systems, and higher breathing rates.


The project began with internal funding from Kingston University, followed by support from Innovate UK and the UK Shared Prosperity Fund. The university worked in collaboration with Technocomm Consulting Ltd, a network communications and sensor specialist, to develop the affordable air pollution sensor, EnviroSense.


Kingston’s team examined how environmental factors and the presence of various gases impacted the sensors’ accuracy. To do this, they co-located the AI-powered sensors with those at the high-precision Weybourne Atmospheric Observatory on the North Norfolk coast, a site known for its varied pollution levels,


driven by winds from heavily polluted areas such as London and the Midlands.


Between May and August 2024, the research team collected data from both the portable sensors and the larger, stationary monitoring station. They focused on measuring levels of carbon monoxide (CO), carbon dioxide (CO2


), and ozone (O3 ) every


30 minutes, while also tracking weather conditions to better understand the relationships between different pollutants and environmental factors.


This data was fed into AI models, which reduced inaccuracies by up to 46%, showing how machine learning could turn relatively simple, inexpensive sensors into powerful tools for air quality monitoring. The study demonstrated that these AI-enhanced sensors could deliver highly accurate air quality information that could help communities take action for cleaner air.


Professor Jean-Christophe Nebel, Director of Kingston University’s Knowledge Exchange and Research Institute for Cyber, Engineering, and Digital Technologies, highlighted the broader impact of the study. “This research shows that portable AI-powered sensors can deliver data accurate enough to make a real difference. It could inform public policy, lead to local emergency responses, and ultimately improve health outcomes,” he said. “Our vision is for these sensors to be deployed on buses or waste collection vehicles in every neighbourhood, providing residents with real-time, localized air quality data.”


Dr. Farzana Rahman, senior lecturer and principal investigator in Data Science, emphasized the importance of the study in tackling a pressing public health issue. “These AI-powered sensors have revolutionized air quality monitoring, making it more accurate and accessible than ever before. This


collaboration sets the stage for future breakthroughs and impactful partnerships,” she said.


Bijan Mohandes, Managing Director of Technocomm Consulting Ltd, credited the success of the project to the close collaboration between the university and his company. “The constant communication and teamwork were essential in delivering the project on schedule,” he said. “This research shows that machine learning and AI have a key role to play in improving the accuracy of electrochemical sensors.”


Further research is underway, in partnership with Rey Juan Carlos University in Madrid and a university in Kuala Lumpur, Malaysia, to deploy these affordable sensors in different climates. The data gathered will help test the sensors’ and AI models’ effectiveness in varied environmental conditions.


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