ESTIMASI POLA DISPERSI DEBU, SO2 DAN NOX DARI INDUSTRI SEMEN MENGGUNAKAN MODEL GAUSS YANG DIINTEGRASI DENGAN SCREEN3
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Accepted
26 February 2018
Published
26 February 2018
Abstract
Industrial activities are sources of air pollution. Pollutants dispersion in air influenced by meteorological condition, such as wind speed, wind direction, air temperarture, air turbulence and atmospheric stability. Air quality monitoring is important in controling the worst condition of pollutants concentration. Air quality monitoring is not easy to do, because it is time consuming, costly and need technology, so that air quality model is developed as an alternative air quality monitoring. This research used gaussian model, a model for predicting pollutant concentrations in downwind area. This model is applied in cement industry, focusing on major pollutants of the cement industry. Sources of pollutants consist of dust, SO2 and NOx. The modeling results showed maximum ground level concentration of dust, SO2 and NOx occur at night (7-10 PM). The maximum ground level concentration of dust, SO2 and NOx at night respectively were 13.16 μg / Nm3, 32.69 μg / Nm3, 100.21 μg / Nm3 (N1 stack) and 14.65 μg / Nm3, 36.65 μg / Nm3, 128.10 μg / Nm3 (N2 stack) based from downwind scenarios at night when atmospheric condition was stable. The distance where the maximum ground level concentration occured has a strong correlation with wind speed (-0.82 ≤ r ≤ -1). Based on gaussian model output, air quality monitoring should be executed at night time (stable atmospheric condition) and located at ground level where maximum concentration occured. Increasing 50m of stack can decrease 57% pollutant concentrations in stable condition.
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Arya, S.P.,1999. Air Pollution Meteorology and Dispersion. Oxford University Press, New York.
Berlyand, M.E., 1991. Prediction and Regulation of Air Pollution. Springer-Science+Business Media, B.V, Netherland.
Eliasson, I., Jonson, P., Holmer, B., 2009. Diurnal and intra-urban particle concentrations in relation to windspeed and stability during the dry season in three African cities. Environ Monit Assess 154, pp. 309-324.
[EPA] Environmental Protection Agency, 1995. Industri Source Complex-3 (ISC3) Dispersion Model, Volume 1 dan 2:User Instruction. US Environmental Protection Agency (EPA) Publication, North Carolina (US).
Gibson, M.D., Kundu, S., Satish, M., 2013. Dispersion model evaluation of PM2.5, NOx and SO2 from point and major line sources in Nova Scotia, Canada using AERMOD Gaussian plume air dispersion model. Jurnal Atmospheric Pollution Research 4, pp.157-167.
Holcim, 2015. Laporan Pembangunan Berkelanjutan 2015. Holcim Indonesia,Jakarta.
Iodice, P., Senartore, A., 2015. Air pollution and air quality statein an Italian National Interest Priority Site. Part 2: the pollutant dispersion. Jurnal Energy Procedia 81, pp. 637-643.
[Kemenperin]Kementerian Perindustrian Republik Indonesia, 2016. Target pertumbuhan industri 5,7 persen. [terhubung berkala]. http://www.kemenperin.go.id/artikel/13740/Tahun-2016,-Target-Pertumbuhan-Industri-5,7-Persen [26 Agustus 2016].
[KLHK] Kementerian Lingkungan Hidup dan Kehutanan, 2014. Indeks Kualitas Lingkungan Hidup Indonesia 2014. KLHK, Jakarta.
Lazaridis, M., 2011. First Principles of Meteorology and Air Pollution. Springer, London.
Pramono, G.H., 2008. Akurasi metode IDW dan Kringing untuk interpolasi sebaran sedimen tersuspensi. Forum Geografi22(1), pp. 97-110.
Rahmawati, F., 2003. Aplikasi model dispersi gauss untuk menduga pencemaran udara di kawasan industri. Tesis.Sekolah Pascasarjana, Institut Pertanian Bogor, Bogor.
Ruhiat, Bey, A., Santosa, I,, Nelwan, L.O., 2008.Penyebaran pencemar udaradi kawasan industri cilegon. Jurnal Agromet Indonesia 22(1), pp. 1-11.
Seinfeld, J.H., Pandis, S.N., 2006. Atmospheric Chemistry and Physics:From Air Polluiton to Climate Change: Second Edition. A Willey-Interscience Publication, Canada.
Shaohui, Z., Worrell, E., Graus, W.C., 2015. Cutting air pollution by improving energy efficiency of China’s cement industry. Jurnal Energy Procedia83, pp. 10-20.
Skelsey, P., Holtslag, A.A.M., Werf, W., 2008. Development and validation of a quasi-Gaussian plumemodel for the transport of botanical spores. Jurnal Agricultural and Forest Meteorology 148, pp. 1383-1394.
Spijkerboer, H.P., Beniers, J.E., Jaspers, D., Schouten, H.J., Goudriaan, J., Rabbinge, R., Werf, W., 2002. Ability of the gaussian plume model to predict and describe spore dispersal over a potato crop. Jurnal Ecological Modelling 155, pp. 1-18.
Turner, D.B., 1994. Workbook of Atmospheric Dispersion Estimates: An Introduction to Dipsersion Modeling: Second Edition. Lewis
Publishers, US.
Turyanti, A., 2016. Pemodelan dispersi PM10 dan SO2 dengan pendekatan dinamika stabilitas atmosfer di lapisan perbatas pada kawasan industri. Disertasi. Sekolah Pascasarjana, Institut Pertanian Bogor, Bogor.
Authors
Puspa DewiN. W. S., JuneT., YaniM. and MujitoM. (2018) “ESTIMASI POLA DISPERSI DEBU, SO2 DAN NOX DARI INDUSTRI SEMEN MENGGUNAKAN MODEL GAUSS YANG DIINTEGRASI DENGAN SCREEN3”, Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management). Bogor, ID, 8(1), pp. 109-119. doi: 10.29244/jpsl.8.1.109-119.
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