ESTIMASI POLA DISPERSI DEBU, SO2 DAN NOX DARI INDUSTRI SEMEN MENGGUNAKAN MODEL GAUSS YANG DIINTEGRASI DENGAN SCREEN3
AbstractIndustrial 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.
Apiratikul, R., 2015. Approximation formula for the prediction of downwind distance that found the maximum ground level concentration of air pollution based on the gaussian model. Jurnal Procedia Social and Behavioral Sciences 197, pp. 1257-1262.
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
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 who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).