Air pollution is one of the biggest environmental challenges facing modern cities, and Liverpool is no exception. Urbanisation, an increase in the number of vehicles, and industrial activity have created a need to implement modern technologies for monitoring and improving air quality. The use of artificial intelligence (AI) and IoT technologies has become an important tool in tackling this problem, making it possible not only to detect rising pollution levels in a timely manner but also to actively work towards reducing them. Find out more at liverpoolname.com.
Air Pollution Monitoring in Liverpool
Liverpool is actively engaged in monitoring its air quality using a variety of systems. The city operates seven automatic monitoring stations, six of which are managed by the City Council and measure Nitrogen Dioxide (NO2) levels in real-time. Another station is owned by DEFRA and is part of the national Automatic Urban and Rural Network (AURN), which also measures other pollutants, including Particulate Matter (PM). In addition to this, Liverpool City Council uses passive diffusion tubes to monitor NO2 at 120 sites across the city, providing a detailed picture of roadside pollution.
To better understand the distribution of pollution, Liverpool also employs air quality modelling, which takes into account the impact of traffic and weather conditions. Studies into the sources of pollution have shown that road traffic, particularly cars, is the main contributor. Consequently, managing traffic is a key task in reducing pollution levels.
Using Artificial Intelligence to Improve Air Quality
To further enhance its air quality management, Liverpool has turned to modern technologies. As a case study, they looked to a project in another county where an AI-based system for predicting NO2 pollution was successfully implemented. Using real-time data from sensors, the system could predict pollution levels an hour before they peaked, allowing pre-emptive measures to be taken to reduce the concentration of pollutants.
Artificial intelligence, when integrated with traffic management systems, allows the flow of transport to be regulated at critical points in the city, preventing pollution levels from rising near residential areas and schools. This type of project has shown positive results, particularly in reducing peak NO2 concentrations without significantly impacting journey times for drivers.
Despite the positive results from implementing AI for pollution monitoring, there is a need for further development and refinement of these technologies. Specifically, the network of monitoring stations needs to be expanded and the forecasting systems improved to cover more areas at high risk of pollution. As shown by the experience gained from the ADEPT SMART Places Live Labs programme, expanding the use of AI for traffic management can significantly improve air quality in other cities. Further funding and investment in the development of such technologies will also have a positive impact on living conditions in urban areas.
Conclusion
Ensuring clean air in urban environments requires the integration of traditional monitoring methods with modern, AI-based technologies. Liverpool’s experience shows that such engineering solutions can significantly improve air quality, especially in areas with heavy road traffic. The continued expansion of these technologies will help to reduce the negative impact of pollution on residents’ health and make the environmental situation in our cities less critical.