Search for more about air quality
Search for more about air quality
Air quality consultants use a model to get air quality forecasting results in the area surrounding the new plant, and this data is included in the environmental impact assessment.
This EIA normally consists of three cases for most new industrial developments.
One could expect a research document of this sort to start with a review of historical air quality observations in the region. This data is used in a model run to define the background pollution and establish the ambient air quality data. Then the sources to be added with the new plant have their emissions parameterized and we conduct a second model run with the new ones included.
The third case, which may be called the Planned Development Case Assessment, includes all emissions counted in the second case plus any other proposed projects within the air pollution modeling domain. A fourth case that would please researchers examining the study, but is rarely required, would be a case which includes the project emissions alone, as this would make impact comparisons even more meaningful.
The results of these air pollution modeling cases can be interpreted in a few ways. One is to compare the predicted absolute air quality concentrations with the relevant ambient air quality standards. Another interpretation method is to compare each case result with the preceding one and calculate the increments in the maximum predicted concentration as a percentage change.
This air pollution modeling step most commonly looks at estimating and identifying stationary sources of:
...emissions as industrial developments generally result in an increase to releases of these elements.
Emission source characterization uses data pertaining to the exhaust stack from which the substances are released. It will include the stack diameter and height as well as its position with relation to nearby buildings, whose length, height and width also need to be specified. In addition, this step includes determining the emission flow parameters of velocity and temperature for each source. To get the air quality impact analysis started, the mass emission rate for each substance considered must be specified, typically in grams per second, in order for the air pollution modeling to make any sense.
Some contaminants come from fugitive emissions - numerous simultaneous small leaks which cannot be modelled individually. VOC, CO and Hydrogen Sulphide (H₂S) often fall on this list.
Terrain elevations are needed for a refined air pollution modeling study. Elevation data is readily available from shuttle data (SRTM) or digital elevation model (DEM) data. The horizontal resolution of 100 m or better (i.e., less) in which this data is available is quite good for air dispersion modelling.
Vegetation cover and land use information, once encoded into the correct formats, supplies the model with representative surface characterization parameters. Depending on the model selected, this data may include leaf area index (known as LAI), albedo and surface roughness. The inputs affect modelled dispersion and deposition, and they usually change with the seasons.
data Also known as Met-Data. CALPUFF has become a standard advanced air quality model used in detailed assessments, and its adjunct model, CALMET, predicts spatially and temporally dependent temperature, wind and turbulence fields. If the CALMET input selected is in the form of output from a mesoscale meteorological model known as MM5, the data should contain the needed wind and temperature profile information for CALPUFF to use.
This approach can be used to integrate the model data with observed meteorological data from within the region examined. It works well when used to prepare five years of high-resolution weather data for use in CALPUFF.
It is a popular model for determining changes in ambient air quality, and this information is used for air quality impact assessments.
This air quality modelling software is widely available, although a user needs to go through a steep learning curve prior to using it for any reliable model execution. Fortunately, model documentation and source code are both easy to obtain.
Check src.com, the website belonging to the distributor and the developer of this and other air quality dispersion models, Joe Scire. Each year, more regulatory bodies and jurisdictions accept, and perhaps even require, CALPUFF modelling in applications for new developments that have the potential to affect air quality.
A major project, one requiring an environmental impact assessment, could justify having air quality modelling to cover a variety of horizontal extents and densities. Typically we define a Regional Study Area (RSA), square or squarish, spanning 100 to 400 km across, with a resolution of one or two kilometres. Inside that would be a Local Study Area (LSA),
normally square, with a density of 1 km out to a distance of 50 km or so. Within that would be several smaller square grids with resolutions of 500 m, 250 m, 50 m and even 20 m, each large enough to accommodate several hundred or even a few thousand grid points.
CALPUFF model run-time can be a concern with these projects, and the run-time is roughly proportional to the number of grid points selected for the air pollution study. A faster alternative would to be use another model such as AERMOD.
The total number of grid points for an EIA could easily fall in the 15,000 to 20,000 range, including dozens or hundreds of special receptors. Also, a list of special air pollution modeling receptors includes a variety of points of interest such as towns, hospitals, campgrounds, wildlife reserves and other places of particular concern.
The model predicts concentrations, in mass per unit volume, for all of the receptors specified. We can program it to provide expected one-hour, 24-hour or annual concentations, or any other averaging period we choose. Modellers prepare contours of maximum (or some specified percentile) concentration for each receptor superimposed over a map of the area under examination.
Results for the special receptors mentioned above, commonly known as sensitive receptors, often appear in tabular format so they can be examined and compared individually. Using a map to show maximum predicted concentrations shows, in two dimensions, the spatial variability that can occur - how things like hills and prevailing wind directions can alter the resulting concentrations in an air pollution modeling project.
If done correctly, the model output can allow decision makers to choose the conditions under which a proposed new development shall operate. This would allow industrial development, good for the economy, to occur without endangering the natural surroundings or public health. Then we have a win-win for everyone involved.
If you have an industrial site that requires dispersion modelling, have a look at what the air dispersion modeling consultants at Calvin Consulting Group Ltd. (Calgary, Alberta) can do.
Please contact the air pollution and regulatory compliance consultants at Calvin Consulting for further assistance. Ask for Barry at 403-547-7557.
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