Dispersion of Carbon Monoxide Pollutant and The Effect of Health (Case Study on Frontage Road Surabaya by Gaussian Line Source Equation Model)
Abstract
Air pollution was being a very important problem and danger for human life. This was related to diseases that arise due to motor vehicle emissions, especially carbon monoxide. Simulation of air dispersion models is the one way to study about air quality that is needed in this regard. This study aims to determine the distribution of carbon monoxide pollutants in Ahmad Yani's frontage and to anticipate the dangers of these pollutants to the health of the people living around the research location. This research discussed about the mathematical model of the dispersion of CO that emitted from cars that passed through the frontage road on the Ahmad Yani Street, Surabaya. The method used is direct observation in the field and numerical simulation using a mathematical model, Gaussian Line Source Equation Model (GLSEM). GLSEM had prepared based on the mechanism of transport of pollutants in dispersion, diffusion and advection. With GLSEM we calculated CO gas concentration values for certain heights downwind. We validated the model by comparing numerical results and measurements of CO concentration. We used the R2 test and we got an R2 close to one. We simulated GLSEM by used Fortran programming language and visualized it with Surfer. The results of the visualization in June showed that the pattern of CO gas dispersion was influenced by the direction and speed of the wind. The results obtained are that the distribution of CO pollutants in the Ahmad Yani frontage is horizontal/downwind. CO concentrations at night are higher than during the daytime. From the CO dispersion pattern, we had known that there were dangerous of air around the frontage for people health. We conclude that around the frontage road of the Ahmad Yani highway there is sufficient open air space so that the danger of CO pollutants being emitted can be minimized so that the health of the community, namely pedestrians, motorcycle drivers and the community around the location can be protected.
Keywords
Full Text:
PDFReferences
Butland, B. K., Atkinson, R. W., Crichton, S., Barratt, B., Beevers, S., Spiridou, A., … Wolfe, C. D. (2017). Air pollution and the incidence of ischaemic and haemorrhagic stroke in the South London stroke register: A case-cross-over analysis. Journal of Epidemiology and Community Health. https://doi.org/10.1136/jech-2016-208025
Coudon, T., Hourani, H., Nguyen, C., Faure, E., Mancini, F. R., Fervers, B., & Salizzoni, P. (2018). Assessment of long-term exposure to airborne dioxin and cadmium concentrations in the Lyon metropolitan area (France). Environment International.
https://doi.org/10.1016/j.envint.2017.11.027
Dash, A. K., Sahu, S. K., Pradhan, A., Dash, S. K., & Kolli, R. N. (2017). Air dispersion model to study the point source air pollution and its impact on ambient air quality. Asian Journal of Chemistry. https://doi.org/10.14233/ajchem.2017.20477
Emanuel, PLE. (2017). SIMULASI MODEL DISPERSI POLUTAN KARBON MONOKSIDA DI JALAN LAYANG ( Studi Kasus Line Source Di Jalan Layang Waru, Sidoarjo). 7(1), 1–6. https://doi.org/https://doi.org/10.36456/buanamatematika.v7i1:.637
Gallagher, J., & Lago, C. (2019). How parked cars affect pollutant dispersion at street level in an urban street canyon? A CFD modelling exercise assessing geometrical detailing and pollutant decay rates. Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2018.10.135
Iodice, P., Langella, G., & Amoresano, A. (2017). A numerical approach to assess air pollution by ship engines in manoeuvring mode and fuel switch conditions. Energy and Environment. https://doi.org/10.1177/0958305X17734050
Irwin, M., Bradley, H., Duckhouse, M., Hammond, M., & Peckham, M. S. (2018). High spatio-Temporal resolution pollutant measurements of on-board vehicle emissions using ultra-fast response gas analyzers. Atmospheric Measurement Techniques. https://doi.org/10.5194/amt-11-3559-2018
Izzah, N.A., Nasrullah, N., & Sulistyantara, B. (2019). The Effectivity of Roadside Green Belt in Reducing the Concentration of CO Gas Pollutant. Jurnal Ilmu Pertanian Indonesia, 24(4), 337–342. https://doi.org/10.18343/jipi.24.4.337
Jeanjean, A., Buccolieri, R., Eddy, J., Monks, P., & Leigh, R. (2017). Air quality affected by trees in real street canyons: The case of Marylebone neighbourhood in central London. Urban Forestry and Urban Greening. https://doi.org/10.1016/j.ufug.2017.01.009
Kiesewetter, G., Borken-Kleefeld, J., Schöpp, W., Heyes, C., Thunis, P., Bessagnet, B., … Amann, M. (2014). Modelling NO2 concentrations at the street level in the GAINS integrated assessment model: Projections under current legislation. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-14-813-2014
Morakinyo, T. E., Lam, Y. F., & Hao, S. (2016). Evaluating the role of green infrastructures on near-road pollutant dispersion and removal: Modelling and measurement. Journal of Environmental Management. https://doi.org/10.1016/j.jenvman.2016.07.077
Moreira, D. M., & dos Santos, C. A. G. (2019). New approach to handle gas-particle transformation in air pollution modelling using fractional derivatives. Atmospheric Pollution Research. https://doi.org/10.1016/j.apr.2019.05.006
Mylläri, F., Asmi, E., Anttila, T., Saukko, E., Vakkari, V., Pirjola, L., … Rönkkö, T. (2016). New particle formation in the fresh flue-gas plume from a coal-fired power plant: Effect of flue-gas cleaning. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-16-7485-2016
Sarrat, C., Aubry, S., Chaboud, T., & Lac, C. (2017). Modelling airport pollutants dispersion at high resolution. Aerospace. https://doi.org/10.3390/aerospace4030046
Seprianto, S. M., & Sainab, S. (2015). Studi Kadar CO Udara & Kadar COHB Darah Karyawan Mekanik Otomotif Bengkel Perawatan & Perbaikan. Jurnal Bionature, 16(1), 49–53.
Seto, E., Austin, E., Novosselov, I., & Yost, M. (2014). Use of low-cost particle monitors to calibrate traffic-related air pollutant models in urban areas. Proceedings - 7th International Congress on Environmental Modelling and Software: Bold Visions for Environmental Modeling, IEMSs 2014.
Shorshani, M., Bonhomme, C., Petrucci, G., André, M., & Seigneur, C. (2014). Road traffic impact on urban water quality: A step towards integrated traffic, air and stormwater modelling. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-013-2370-x
Tomasi, E., Antonacci, G., Giovannini, L., Zardi, D., & Ragazzi, M. (2015). Atmospheric dispersion modelling with AERMOD for comparative impact assessment of different pollutant emission sources in an alpine valley. WIT Transactions on Ecology and the Environment. https://doi.org/10.2495/AIR150371
Vicente, B., Rafael, S., Rodrigues, V., Relvas, H., Vilaça, M., Teixeira, J., … Borrego, C. (2018). Influence of different complexity levels of road traffic models on air quality modelling at street scale. Air Quality, Atmosphere and Health. https://doi.org/10.1007/s11869-018-0621-1
Zhunussova, M., Jaeger, M., & Adair, D. (2017). Application of CFD modelling to air quality in Kuwait City. Environmental Fluid Mechanics. https://doi.org/10.1007/s10652-016-9497-5
Zong, C., & Zhang, G. (2014). Numerical modelling of airflow and gas dispersion in the pit headspace via slatted floor: Comparison of two modelling approaches. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2014.10.015
DOI: http://dx.doi.org/10.30742/jikw.v11i2.2416
Refbacks
- There are currently no refbacks.
Copyright (c) 2022 Nurachmawati Meindah Sari, R. Azizah
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Jurnal Ilmiah Kedokteran Wijaya Kusuma is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
