Abstract
Abstract. This paper presents the design and the results of a novel approach to predict air pollutants in urban environments. The objective is to create an artificial intelligence (AI)-based system to support planning actors in taking effective and adequate short-term measures against unfavourable air quality situations. In general, air quality in European cities has improved over the past decades. Nevertheless, reductions of the air pollutants particulate matter (PM), nitrogen dioxide (NO2) and ground-level ozone (O3), in particular, are essential to ensure the quality of life and a healthy life in cities. To forecast these air pollutants for the next 48 hours, a sequence-to-sequence encoder-decoder model with a recurrent neural network (RNN) was implemented. The model was trained with historic in situ air pollutant measurements, traffic and meteorological data. An evaluation of the prediction results against historical data shows high accordance with in situ measurements and implicate the system’s applicability and its great potential for high quality forecasts of air pollutants in urban environments by including real time weather forecast data.
Highlights
Air pollution is still one of the main public health issues in cities worldwide
Biodiversity as well as functioning terrestrial and aquatic ecosystems are threatened by air pollutants
Using artificial intelligence this study proposes a different approach to simulate and forecast air quality at spot-based measurement stations as well as at city level
Summary
Air pollution is still one of the main public health issues in cities worldwide. It affects human health, and the environment. The Directive 2008/50/EC on ambient air quality and cleaner air for Europe, which was enacted in 2018, defines limiting and target values for each air pollutant. NO2 concentrations should not exceed the hourly limit value of 200 μg/m3 for more than 18 hours per year, in addition the annual mean is limited to 40 μg/m3. The directive does not define limiting values for groundlevel ozone. It only states a long-term objective of a maximum daily 8-hour mean of 120 μg/m3 Spot-based measuring stations detect and observe the air quality in Europe. Those measuring stations are mainly located in hotspot areas, such as roads and intersections with a high traffic volume (cf Petry et al, 2020)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
