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International Journal of Environment Science and Technology
Center for Environment and Energy Research and Studies (CEERS)
ISSN: 1735-1472 EISSN: 1735-1472
Vol. 12, No. 4, 2015, pp. 1331-1342
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Bioline Code: st15123
Full paper language: English
Document type: Research Article
Document available free of charge
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International Journal of Environment Science and Technology, Vol. 12, No. 4, 2015, pp. 1331-1342
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Optimal design of air quality monitoring network around an oil refinery plant: a holistic approach
Benis, Kh. Zoroufchi & Fatehifar, E.
Abstract
In this study, a multi-objective method for
allocating the number and configuration of an air quality
monitoring network based on non-dominated sorting
genetic algorithm II has been presented. The multiple cell
approach based on the solution of an Eulerian Model built
on K-theory was used to predict the dispersion of emitted
pollutants (SO2, CO, NOx) from different emission sources.
The multi-objective optimization method proposed in this
study utilized two objectives: (1) maximum coverage area
with respect to continuity of covered area and minimum
overlap among coverage areas and (2) detection of violations
over ambient standards. The concept of sphere of
influence was used to determine the spatial area coverage
of the monitoring station, and a weighing function was
employed to measure the capability of a designed network
to detect violations of air quality standards. The results
show that three stations are suitable for the study region
with coverage efficiency of 80 %. Analyzing the effect of cutoff correlation coefficient rc shows that, when the rc
increases, although the coverage area decreases, the covered
region will be well represented and overlap region will
decrease.
Keywords
Air quality; Genetic algorithm; Multi-objective; Multi-pollutant; Optimization
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