Why are LEZs important for smart cities?
Rapid urbanization and increased traffic lead to alarming levels of air pollution. Cities face the challenge of reducing pollutant gas emissions and promoting sustainable mobility. Low-emission zones (LEZs) effectively improve air quality, protect public health and promote a greener lifestyle in urban environments.
IImplementing an EPZ can be a costly and complex process. You aim to ensure that the LEZ positively impacts air quality and citizens' quality of life. LIbelium's Sustainability Impact Assessment (SIA) solution allows cities to predict the impact of the LEZ on overall air quality (not just in the application zone) using pollution dispersion modelling. You can see the effect on air quality throughout the city and make informed decisions before investing resources in implementing the LEZ. Thanks to the ability to predict the results of the LEZ, you can be sure that the implementation will be effective, ensuring that the LEZ does not produce adverse effects in other areas. In addition, the SIA solution also helps address citizens' concerns and resistance. By predicting the impact of the LEZ, you can confidently answer citizens' questions and clearly understand how the new system will work.
The actual situation of the city (obtained from sensors) is displayed on the platform; indicators such as reduced CO2 or reduced number of private trips are shown as part of the results.Se muestra la situación real de la ciudad (obtenida de los sensores) en la plataforma; como parte de los resultados se muestran indicadores como por ejemplo CO2 reducido o número de viajes privados reducidos.
Thanks to the traffic and pollutant dispersion models, we can detect areas where traffic significantly impacts the city's air quality.Gracias a los modelos de tráfico y dispersión de los contaminantes podemos detectar aquellas áreas en las que el tráfico tiene un mayor impacto en la calidad del aire global de la ciudad.
Accurate traffic models can be used to study the impact of the measures, including traffic redistribution.
If public transport data is included, one result of our solution is an indicator of the use of public transport by citizens, with the possibility of modelling changes in public transport and studying which scenarios encourage public transportation vs private vehicles.Si se incluyen datos de transporte público, un resultado de nuestra solución es un indicador del uso del transporte público por parte de los ciudadanos, con la posibilidad de modelar cambios en el mismo y estudiar qué escenarios fomentan más el uso del transporte público vs vehículo privado.
We have successfully developed the LEZs in multiple European cities and participated in European projects, such as AI4Cities in Paris, Helsinki, Amsterdam, Stavanger and Tallinn, or the IMAGINEXT project in Cartagena (Spain) and Lindau (Germany).
Mobility data, traffic cameras, air quality and noise devices, historical data, and external data sources; detailed information on the use case, depending on the municipality's needs. Whether it is a large or small project, we have been developing IoT projects for more than 16 years.
Creation of the traffic model and training of the dispersion models to finally arrive at the recommended deployment of the solution.
We simulate the scenarios of interest for the city; at this point, you already have the tool available to make your simulations autonomously or guided by our experts in Artificial Intelligence.
Based on the studies carried out with the tool, we decide which measures are the most appropriate. From Libelium, we offer you this complete study so that you do not have to worry about anything. From this study, we obtain the results in impact measurement reports, validate the different options and use tools for the simulation/validation of tactical urbanism strategies.
With the implemented measures, we finally validate the prediction of the tool to check and audit the real benefits and impact of the LEZ in your city.
Satisfaction of European regulations and Next Generation funds of public investment in actions towards sustainability and resilience. More than 10 Spanish cities benefiting from Next Generation funds have successfully designed their LEZs with Libelium's Sustainable Impact Assessment (SIA) solution for LEZs.
Thanks to Libelium's solution, our success story in Cartagena has implemented a LEZ without any negative impact or significant reduction in mobility services for its citizens.
“In a city like Cartagena, it is essential that all technological advances in urban mobility are always carried out most efficiently and sustainably possible while at the same time seeking the highest possible return. It makes no sense to implement technology that later becomes obsolete or to measure parameters that are disconnected from each other. It is essential to measure the entire ecosystem, to go step by step and for each investment to build a long-term project. The rulers pass through the office, but their projects must permanently contribute to the citizens' well-being”
The only model in the market that merges traffic models with pollution propagation models. Awarded by EIT Urban Mobility in the ImagiNext Grant in cooperation with CARNET (Volkswagen Group and Universitat Politécnica de Catalunya), Fraunhofer and the leading mobility modelling company (PTV Group), who have joined forces with Libelium for pollution and sustainability modelling.
High capacity of mobility data generation for cities without historical data from pre-trained models with more than 20,000 hours of traffic data (and growing) coming from European cities of different sizes and behaviours.
Compatible with other urban initiatives through open standards for digital transformation such as ETSI NGSI-LD, GAIA-X, and FIWARE and validated by the European Union as a Connecting Europe Facilities service.
Fully available SaaS service with High ENS certification and support for National Interoperability Scheme best practices, Smart Data Models and semantic annotation.
Proven reduction of the design time of LEZs from 12 to 3 months, with the ability to extrapolate and compare mobility models between different cities, including European capitals such as Paris, Helsinki or Madrid.
While urbanisation and populations in urban areas increase, decarbonising cities becomes a harder challenge. In this context, as an unprecedented amount of urban traffic pollutants are generated in cities, IMAGINEXT validates a Software as a Service (SaaS) solution that utilises artificial intelligence (AI) to learn how special mobility strategies and sustainable transport measures impact air quality.
IMAGINEXT SaaS is being validated in two cities so that the AI can start receiving information and learning based on the size and density of each city. IMAGINEXT aims to accelerate market opportunities for mobility decision-makers with the potential of implementing sustainable transport solutions that are known to be effective in improving city air quality based on evidenced cases incorporated in the SaaS and extrapolated to bespoke uses through AI.
To help effectively implement Low Emission Zones (LEZs) and decarbonisation strategies in cities.
To provide a tool to help mobility decision-makers implement necessary strategies to meet European environment targets with evidence-based data.
A SaaS solution that monitors mobility pollutant indicators and traffic conditions in real-time against specific measures and strategies and predicts their impact using AI models.
Data related to traffic emissions are modelled through a different software: PTV Vissim. This allows, through vehicle flow data in the network, to calculate by means of statistical models the number of vehicles and their distribution over a time interval, in addition to having an internal model that translates this data directly into emissions of the main pollutants.
The operation of this tool is mainly based on an air pollution propagation model called MUNICH (Model of Urban Network of Intersecting Canyons and Highways), which is in charge of simulating air quality with a high resolution in medium-sized areas.
CB05 (Carbon Bond 05) mechanism of chemical reactions, including oxidations of VOCs, nitrogenous compounds and sulfides, and the role of sunlight through photolysis.
A device management platform that enables complete end-to-end management of your IoT project. Store, visualize and analyze the data received. Send data to the main cloud platforms on the market.
Libelium's Artificial Intelligence (AI Services) team is able to develop customized services for municipalities, linked to the following areas:
● Low Emission Zones (LEZ) modeling and creation
● Crowd monitoring
● Pollen levels
● Heat maps
From here, we recommend that you set up a meeting with our Smart Cities experts at the link below. What do we need to know from you?