The phrase "air quality modelling" is correct and usable in written English.
You can use it when discussing the assessment or simulation of air quality in a specific area or context, often in environmental science or urban planning.
Example: "The researchers conducted air quality modelling to predict the impact of traffic emissions on local pollution levels."
Alternatives: "air quality assessment" or "air quality simulation".
Because the urban impact is not measurable, the SHERPA modelling approach, based on a full air quality modelling system, is used in this work to assess the validity of these assumptions for some European cities. Results indicate that for PM2.5, these two assumptions are far from being fulfilled for many large or medium city sizes.
The SHERPA (Screening for High Emission Reduction Potentials on Air quality) modelling tool was developed in this context.
Validation of the two codes with this realistic urban geometry shows the capabilities and shortcomings of RANS CFD modelling for regulatory purposes in urban air quality modelling.
This paper describes the design of an integrated transportation and air quality modelling framework capable of simulating traffic emissions and air pollution at a refined spatio-temporal scale.
The Traffic Emission Modelling and Mapping Suite (TEMMS) is a program designed to provide detailed estimates of vehicle emissions on urban road networks, and so act as a precursor to urban air quality modelling.
For long-range modelling, the MSRED was built to generate a ready-to-use initial conditions file to be input to the CMAQ model, as it represents the state-of-the-art in regional and chemical transport air quality modelling.
Increased focus has been directed at fine-scale modeling for improving the ability of air quality modeling systems to capture local phenomena.
The objective of this work is to present a novel approach to design a source receptor relationship for air quality modeling.
Meteorological conditions such as thermal inversions can prevent surface air from rising, trapping pollutants near the surface, which makes accurate forecasts of such events crucial for air quality modeling.
We also elected to use air monitor data to avoid the uncertainty associated with air quality modeling assumptions such as emissions inventories and chemical mixing (U.S. EPA 2008b).
The first step is sometimes accomplished through emissions scenarios and information regarding how emissions translate into pollutant concentrations, such as with air quality modeling systems.
