What happens to air quality levels when these three factors come together?
According to the World Health Organization the most polluted cities in the world are Zabol (Iran), Gwalior (India), Allahabad (India), Riyadh (Saudi Arabia) and Al Jubail (Saudi Arabia). All these cities have something in common, as they are all affected by three determining air quality sensitive factors:
Sand and dust storms affection that provide a natural-generated contribution to PM10 and PM2.5 concentrations.
Highly populated cities normally lead to a massive use of private motor vehicles that mostly use low refined fossil fuels.
High industrial activity demands of high power-electricity and fossil-fuel demand to cover the operational needs.
Considering these initial conditions, perhaps we could think if there is any technological solution to early-detect severe air quality episodes over complex located urban areas.
Following the previous post Dust: when pollution comes from deserts air quality severe episodes over these urban areas is not only due to emission sources associated to anthropogenic activity. Therefore, the use of modelling tools that reproduce the impact contribution generated by the natural dust generation phenomena is also mandatory.
In addition to this subject, the difficulty to retrieve detailed information related to anthropogenic pollutant emitting sources over the same regions requires of a very complex scientific challenge in order to develop reliable forecasting technology to predict severe air quality future situations.
The combination of different air quality modelling tools linked to a high-resolutionmulti-source emission inventories can provide a feasible response to this complex environmental situation over desertic urban areas.
Air Quality forecasting and management tools for complex urban environments.
Meteosim has recently developed an urban air quality management tool in which different atmospheric models are combined and coupled to perform reliable and high-resolution air quality forecasts. This technology has been developed to help local authorities to detect severe air quality episodes and evaluate potential mitigation strategies, helping to improve the air quality levels management over these urban environments. This innovative technology is also able to provide quick-response modelling capabilities for industrial emergency events related to operational abnormal conditions and helping local authorities to implement emergency response protocols in the necessary time response requirements.
The system is based on a multy-coupled modelling approach using WRF-Chem chemical-meteorological model, CMAQ photochemical model, Meteosim’s AEMM Emission model. CALPUFF and HySPLIT modelling systems are also integrated for local and emergency response approach capabilities.
This technological advance can be easily exported to other large cities with similar complex conditions helping local authorities to improve air quality management over dense-populated urban environments.