Air Quality Modelling

Air Quality Modeling is at the heart of what we do here at our Singapore office in BroadTech Engineering.
It is the use of numerical simulation models to understand and predict the fluid flow behavior of air pollutants in the atmosphere.
Simulation Modelling can be used to run scenarios, to test and validate fluid dynamic theories and give insights environmental air quality impact (AQI) of different factors such as Emission rates, meteorological weather conditions, and development scenarios.
Although there is a wide variety of Air modeling methods and techniques, the ultimate end goal is almost always the same, which is to assess the impact of pollutant impact over a given area using a pre-existing data set.
 
During the Air modeling, there are some inputs make, such as Assumptions, Rules, and Data
 

1. Assumption

An assumption is something that we assume to hold true in all air modeling conditions.
One of the assumption that we make is that the fluid dynamic behavior of the atmosphere is not random, but behaves in a predictable way and that plumes behave in a known way.
 

2. Rules

Some of the rules we use include

3. Input Data

We usually input data such as meteorological and terrain data.
The accuracy and quality of the air simulation model are only as good as the quality of the input data that we feed it.

Advantages of Air Quality Modelling

1. Accurate Theoretical Assessment

Accurately assess a totally hypothetical air dispersion modeling scenario before time and financial resources are committed to a project, such as the construction of a particular industrial plant design
 
Using air simulation model, it is possible to roughly quantify the pollutants emission output from an industrial operation, base on the known information, such as stack height and the industrial process involved in the industrial operation.
These emissions data obtained can be fed into an air quality model, which can spatially simulate the dispersion patterns of emissions around the source.
 

2. Exploration of Emission Scenarios which are Impossible to Test

Although the downside of the theoretical model is that it does not always reflect real-world conditions with total accuracy, it allows for the simulation and exploration of alternative test scenarios which are otherwise impossible to test physically, such as air quality impact of a new road, or manufacturing plant.
 

3. Exploration of Large-Scale or Regional Emission Scenarios

Air quality modeling can also be used to test large-scale emission situations at a regional or global scale whereby the process of actual data collection is too cost prohibitive and impossible.

Application Uses of Air Quality Modelling

Analysis of Air pollution models can help us to answer question such as

 
This can give insights such as
 

1. Emission Concentration of Industrial Processes

Show if whether the pollutant concentrations are too high based on a specific mode of industrial operation
 

2. Emission Concentration in Downstream Residential Areas

Reveal that under specific wind conditions the pollutant concentrations in a downstream residential area are at a hazardous level high. Air quality modeling simulation allows potential emission problem to be highlighted and solved before it even happens in the real world.
 

3. Assess Impact of Specific Industrial Emission on Air Quality

Often due to regulatory requirements for Environmental protection of Air quality, industrial emitters need to demonstrate the extent of the environmental impact from their industrial emission source.
The impact severity of their industrial processes will dictate whether their emissions are permitted.
 

4. Simulation of Alternative Emission Scenario

Air quality model can be used to simulate Specific emissions scenarios base on new modification implemented in an industrial operation can be modeled and simulated to quantify the emission.
Air quality modeling can be used to assess the impact and effectiveness of specific changes such as

Overview