1.4. Mapping and Visualization of Pollutant Concentration

The application when we do this we define a grid of measurement coordinates also called as receptors. What we are doing is we are trying to measure concentration exposure which means there is a receptor there, so instead of receptor what we are doing is we are putting the coordinates x, y and z on the left hand side of the Gaussian dispersion model that is the receptor which means it’s a coordinate.

In environmental science, mapping refers to how we visualize the location and concentration of pollutants in a specific area. To do this effectively, we create a grid of points in the environment where we want to measure pollution levels. Each point in this grid is called a 'receptor,' and represents a specific location with coordinates (x, y, z). Using the Gaussian dispersion model, we can calculate pollutant concentrations at these points, helping researchers understand the distribution and impact of pollution.

Think of receptors as spots on a chessboard, where each square represents a location you want to check for pollution. Just like a player would look at various squares to make a move, researchers look at these receptors to see where pollution levels are high or low in the environment.

If you are interested in doing a large number of sources, I am looking at a top view of a map there is a source here, we call it a source 1, the source1 has plume. Source 2 somewhere nearby assuming that wind is in this direction source 2 also has plume, source 3 also has a plumeit may have different q1, q2 what we are assuming in dispersion model is let us say if I want to measure the concentration at this point from location x, y and z, now there is a contribution from source 1 for this S1.

When mapping pollution from multiple sources, we assume each source emits pollutants in a specific pattern, which we refer to as a 'plume.' The concentration of pollutants at any point depends on how many sources are nearby and their emission rates. For example, if we have three different sources (like factories) emitting pollutants, we can calculate the total concentration at a specific receptor by adding the contributions from each factory's plume. This allows us to understand not just the impact of a single source but the combined effect of several sources in an area.

Imagine sitting in a park surrounded by three different barbecue parties. Each party has smoke drifting in your direction. The total amount of smoke you experience is the combination of what each party is contributing. Similarly, researchers measure how much each pollution source adds to the overall pollution level at a receptor point.

So the way we do it is by mapping it. So this is a very good way to doing it, say for example; this is a map of Chennai and this is a garbage dump in South Chennai. This is the source, I am assuming this is my one source. So if I plot, if I measure a large set of coordinates all around this. I am assuming that the wind is coming from this direction. If my wind is in this direction, I am defining that as my x axis and then I am measuring it in a wide set of coordinates.

Once we gather pollution concentration data from various receptors around a source, we can visualize this information through contour maps. For instance, if we have a garbage dump as our pollution source and we measure the concentration of pollutants at various locations surrounding it, we can plot these points on a map. If we connect points with equal pollution levels, we create lines called isopleths that represent different levels of concentration, resulting in a contour map. This effectively shows how pollution spreads from the source depending on wind direction and other factors.

Think of contour mapping like drawing a map for a hiking trail. Different elevations create contour lines on a map that indicate how steep or flat a trail is. Similarly, pollution maps show how concentrated pollutants are at different areas surrounding a source, with higher concentrations represented by tighter contour lines.

What this application gives you is; let us say that 50 milligrams per meter cube is the ambient exposure level you cannot anything above 50 is supposed to be not safe. So then you can say that I will mark these regions in this radius to be seriously affected.

Contour maps are not just for observing pollution; they are crucial for emergency response planning. For example, if the safe limit for a pollutant is 50 milligrams per cubic meter, any area on our map showing concentrations above this level indicates a high-risk zone. Authorities can use this information to mark out affected regions for immediate action, helping to safeguard the health of the population nearby. This can involve alerting residents, providing safety equipment, or planning evacuation routes.

Consider a weather map forecasting a storm. Areas marked in red indicate severe weather warnings, giving residents time to prepare or evacuate. In the same way, pollution contour maps warn of hazardous areas, enabling swift action to protect public health.

The second type of application in sense how you can use this information is to plan this sighting of industry. This is a very, very common thing in the reason people used to do this very heuristically.

Investors and urban planners use pollution mapping data to decide where to build new industries. This process, known as 'siting,' involves placing industrial plants far from residential areas to minimize health risks from emissions. By understanding prevailing winds and pollution dispersion patterns, planners can position industries in a way that prevents their emissions from affecting nearby communities, ensuring a healthier environment.

Imagine choosing a location for a restaurant. You'd want to avoid placing it right next to a crowded school or residential neighborhood where passing cars might create noise and pollution. Planners do the same with industrial sites, using data to ensure that factories are located further away from areas where people live and work.

--