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
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.
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
It can be used to evaluate it pollution impact on urban Air quality or check to see if it represents Health hazards to residents in the nearby area.
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
We Help Our Clients Gain Valuable Insights to Optimize and Improve Product Performance, Reliability, and Efficiency.
1. Powerful FEA Simulation Software Tools
2. FEA Consultants with Extensive Research & Professional Experience
3. FEA projects Completed in a Timely and Cost-effective Manner
4. Proven Track Record
6. Full Knowledge Transfer
Types Of ADM Models
There are several different types of air quality models, all used for differing scenarios. The most commonly used models are broadly known as Atmospheric Dispersion Models (ADM).
These mathematical models use assumptions about the way that the atmosphere behaves, to assess the air quality impact of pollutant emissions.
Typically, these types of air quality models are used to model emissions from a single point source, such as a smokestack of an industrial facility.
CALPUFF is a powerful air quality model which uses 3 major inputs, 1. Meteorological model, 2. Dispersion model and 3. Post-processing package.
This air quality model recommended by USEPA can be used at a wide range of scales ranging from a few square kilometers to several hundred kilometers encompassing a large regional area.
It can accurately take into account and handle with other related environmental factors such as
The data output from CALPUFF model can be easily visualized as a ‘grid’ in Geographic Information Systems (GIS) software packages or other similar proprietary software.
In general, the CALPUFF model is used for smaller scale air quality impact assessments (less than 10KM2)
Unlike the CALPUFF model which is a non-steady state air simulation model which can be tuned for changes in environmental conditions, AERMOD assumes a steady state condition, where the model is characterized by continuous emissions and environmental factors.
AERMOD is USEPA approved and suitable for larger regional air modeling projects.
CALINE4 is an ADM specifically designed for assessing air quality impacts at roadways or intersections. The module uses a range of traffic and fleet characteristics, and a diffusion equation to assess the impacts of a road on a small scale.
Often this model is used to predict impacts of changing traffic volumes, signal phasing or adding additional lanes to a roadway.
VEPM is a similar model are in use around the world. developed in New Zealand, uses real, lab-based emissions data to predict emissions from a roadway, and can even predict emissions out to 2040.
5. Land Use Regression (LUR)
Land Use Regression (LUR) models can model and predict air quality in particular location by drawing a theoretical correlation between the land use and air quality
Such models can involve the deployment of passive air sampler instruments distributed strategically across an area of interest. Base on the data collected, a correlation between pollutant concentration and other possible factors can be developed. This includes factors such as vehicle traffic movements, street size or building height.
This approach allows entire metropolitan cities, such as to be modeled
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Clients will be provided with a fully tailored report which outlines the Methodology, in-depth analysis and recommendations.
This insight allows our customers to optimize performance and make informed engineering decisions in a scientific, proven manner.
Discover what Air Quality Modelling can do for your company today by calling us today at +6581822236 for a no obligation discussion of your needs.
Our knowledgeable and friendly consultants will be happy to assist and understand more about your project needs and requirements.
Alternatively, for quote request, simply email us your detailed technical specifications & requirements to email@example.com