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Computing Pollution
Computers are being used in applications that gauge the pollution in the air and water and other areas of the earth environment. These applications are useful in determining the source of the pollution and in assisting in informing researchers what might be done to reduce such pollution.
Air Pollution Emission
One such application in computing pollution is described in the work of Emad, Sayed, and Kassem (nd)[footnoteRef:1] who report that smoke is one common source of air pollution. Specifically stated is that the "rising process of smoke depends on atmospheric ambient, meteorological conditions, emission parameters, such as the atmospheric stratification, initial emission momentum and temperature, wind direction and speed as well as turbulent behaviors, and so on." (Emad, Sayed, and Kassem, nd, p.1) The smoke dilution process and scope are of great interest to environmentalists since regional air quality is affected critically by dispersion of pollutants. Reported as a key tool in screenings of vehicular exhaust emissions (VEESs) is that of 'line source emission modeling' as it assists in the management and control of such emissions in the urban environment. (Emad, Sayed, and Kassem, nd, paraphrased) [1: Emad, AA., Sayed, M.E., and Kassem K.O. (nd) Computer Simulation for Dispersion of Air Pollution Released from a Line Source According to Gaussian Model. Canadian Journal on Computing in Mathematics, Natural Sciences, Engineering & Medicine Vol. 1, No. 3, April 2010. Online available at: http://ampublisher.com/April%202010/CMNSEM-1004-013.pdf. ]
II. IPython Parallel Computing
The work of Hemann and Granger (nd) entitled "Parallel Computing with IPython: An Application to Air Pollution Modeling" reports that IPython has two main components which are those of:
(1) an enhanced interactive Python shell; and (2) a framework for interactive parallel computing.[footnoteRef:2] [2: Hemann, J. And Granger,...
(nd ) Parallel Computing with IPython: An Application to Air Pollution Modeling. Available online at: http://conference.scipy.org/scipy2010/slides/josh_hemann_airpollution_acrobat.pdf]
IPython is used for air pollution modeling. It is stated that receptor models make the provision of scientific support "…for current ambient air quality standards and for implementation of those standards by identifying and quantifying contributions for source appointment." (U.S. Environmental Protection Agency cited in: Hemann and Granger, nd, p.17) The ability to measure air quality data sets has resulted in the improvement of the same due to the ability to measure air quality and to stratify particle size during sampling. (U.S. Environmental Protection Agency, cited in: Hemann and Granger, nd, paraphrased)
III. Watershed Pollution
Another report entitled "High Performance Computing Application to Address Non-Point Source Pollution at a Watershed Level" reports a tool that is used for evaluating the performance of 'Best Management Practices' that serve to "provide optimal solutions for maximum pollution reduction and minimum increase in net costs'. (Maringanti and Chaubey, nd, p.1)[footnoteRef:3] One specific tool utilized is the soil and water assessment tool (SWAT) which is used for: [3: Maringanti, Chetan and Chaubey, Indrajeet (nd ) High Performance Computing Application to Address Non-Point Source Pollution at a Watershed Level. Agricultural and Biological Engineering. Purdue University. Online available at: https://engineering.purdue.edu/ecohydrology/Chetan/ASABE2009.pdf]
(1) hydrologic and water quality modeling;
(2) to simulate stream flow;
(3) agricultural management practices;
(4) dynamic land use; and (5) climate change. (Maringanti and Chaubey, nd, p.1)[footnoteRef:4] [4: Ibid]
IV. Microscopic Robots and Water Pollution
It was recently reported by the University of Southern California School of Engineering that it has received funds in the amount of $1.5 million in the form of a research grant which will be used to create "swarms of microscopic robots to monitor potentially dangerous microorganisms in the ocean." (Daily University Science News, 2002)[footnoteRef:5] Due to urban runoff combined with sewage spills and blooms of harmful algae off heavily polluted coastal areas"…
References
Emad, AA., Sayed, M.E., and Kassem K.O. (nd) Computer Simulation for Dispersion of Air Pollution Released from a Line Source According to Gaussian Model. Canadian Journal on Computing in Mathematics, Natural Sciences, Engineering & Medicine Vol. 1, No. 3, April 2010. Online available at: http://ampublisher.com/April%202010/CMNSEM-1004-013.pdf.
Hemann, J. And Granger, B. (nd ) Parallel Computing with IPython: An Application to Air Pollution Modeling. Available online at: http://conference.scipy.org/scipy2010/slides/josh_hemann_airpollution_acrobat.pdf
Maringanti, Chetan and Chaubey, Indrajeet (nd ) High Performance Computing Application to Address Non-Point Source Pollution at a Watershed Level. Agricultural and Biological Engineering. Purdue University. Online available at: https://engineering.purdue.edu/ecohydrology/Chetan/ASABE2009.pdf
Swarms of Tiny Robots to Monitor Water Pollution (2002) Daily University Science News. UNISCI online available at: http://www.unisci.com/stories/20021/0114026.htm
Hooker, Ben, Gaver, William W., Steed, A. And Bowers, J. (2007) The Pollution e-Sing. Online available at: http://www.benhooker.com/escience/escience.pdf
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