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Modeling Air Pollution In Dong Nai Province, Vietnam

https://doi.org/10.24057/2071-9388-2019-44

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Abstract

Data analysis shows that dust and CO have a very high concentration, causing air pollution. Meanwhile, SOand NO2 concentrations are lower than the permitted levels. The method inverse distance weighting (IDW) has been proved to be effective in modeling atmospheric pollution space in the study area. The results indicated that the air was contaminated. Pollution levels increase gradually in the following areas: Residential areas <Waste treatment areas <Industrial parks. The integrated pollution map shows that there have been signs of ecological insecurity in the dry season, so there should be measures to control the source of emissions into the environment.

About the Authors

T. Hung Nguyen
Vietnamese National University of Forestry
Viet Nam
Xuan Mai Town, Chuong My District, 1000, Ha Noi


Irina I. Kosinova
Voronezh State University
Russian Federation
1 Universitetskaya pl., 394018, Voronezh


T. L. Anh Đang
Vietnamese National University of Forestry
Viet Nam
Xuan Mai Town, Chuong My District, 1000, Ha Noi


References

1. Awkash K., Rashmi S., Anil K.D. and Rakesh K. (2016). Air Quality Assessment Using Interpolation Technique. Environment Asia, 9(2), 140-149.

2. Bellander T., Berglind N., Gustavsson P., Jonson T., Nyberg, F. and Pershagen G. (2001). Using geographical information systems to assess individual historical exposure to air pollution from traffic and house heating in Stockholm. Environmental Health Perspectives, 109, 633-639.

3. Candiani G., Carnevale C., Finzi G., Pisoni E. and Volta M. (2013). Comparison of reanalysis techniques: applying optimal interpolation and Ensemble Kalman Filtering to improve air quality monitoring at mesoscale. Science of the Total Environment, 458-460, 7-14.

4. Clench-Aas J., Bartonova A., Gronskei K. E. and Walker S. (1999). Air pollution exposure monitoring and estimation. Part IV. Urban exposure in children. Journal of Environmental Monitoring, 1, 333-336.

5. Dilip K.J., Sabesan M. and Kirubagaran R. (2011). Evaluation of Interpolation Technique for Air Quality Parameters in Port Blair, India. Universal Journal of Environmental Research and Technology, 1,(3), 301-310.

6. Gualtieri G. and Tartaglia M. (1998). Predicting urban traffic air pollution: A GIS framework. Transportation Research Part D, 3, 329-336. Janssen S., Dumont G., Fierens F. and Mensink C. (2008). Spatial interpolation of air pollution measurements using CORINE land cover data. Atmospheric Environment, 42(20), 4884-903.

7. Jerrett M., Burnett R.T., Kanaroglou S., Eyles J., Brook J.R. and Giovis C. (2001). A GIS environmental justice analysis of particulate air pollution in Hamilton, Canada. Environment and Planning, A, 33, 955-973.

8. Jerrett M., Arain A., Kanaroglou P., Beckerman B., Potoglou D. and Sahsuvaroglu T. (2005). A review and evaluation of intraurban air pollution exposure models.Journal of Exposure Analysis and Environmental Epidemiology, 15, 185-204.

9. Kumar A., Gupta I., Brandt J., Kumar R., Dikshit A.K. and Patil R.S. (2016). Air quality mapping using GIS and economic evaluation of health impact for Mumbai city, India. Journal of the Air and Waste Management Association, 66(5), 470-81.

10. Krause P., Boyle D.P. and Base F. (2005). Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, (5), 89-97.

11. Li J. and Heap A.D. (2008). A Review of Spatial Interpolation Methods for Environmental Scientists, Geosience Australia. Geoscience Australia Record 2008/23, 137.

12. Michelozzi P., Forastiere F., Fusco D., Perucci C.A., Ostro B., Ancona C. and Pallotti G. (1998). Air Pollution and Daily Mortality in Rome, Italy. Occupational and Environmental Medicine, 55 (9), 605-10, DOI:10.1136/oem.55.9.605. JSTOR 27730990. PMC 1757645. PMID 9861182.

13. Nguyen Trong Hai. (2018). Report the situation of infection in 2018. Dong Nai Department of Health, 75-86. (in Vietnamese).

14. Ostachuk A., Evelson P., Martin S., Dawidowski L., Yakisich J.S. and Tasat D.R. (2008). Age-related lung cell response to urban Buenos Aires air particle soluble fraction. Environmental Research, 107(2), 170-177, DOI: 10.1016/j.envres.2008.01.007. PMID 18313661.

15. Oke A.O., Sangodoyin A.Y., Ogedengbe K. and Omodele T. (2013). Mapping of river water quality using Inverse Distance Weighted interpolation in OgunOsun river basin, Nigeria. Landscape & Environment, 7(2), 48-62.

16. Pamela F.H. and Grace K.L. (2011). The Use of AERMOD Air Pollution Dispersion Models to Estimate Residential Ambient Concentrations of Elemental Mercury. Water Air Soil Pollut, 219, 377-388, DOI: 10.1007/s11270-010-0714-4.

17. Pieters N., Koppen G., Van Poppel M., De Prins S., Cox B., Dons E., Nelen V., Int Panis L., Plusquin M., Schoeters G. and Nawrot TS. (2015). Blood Pressure and Same-Day Exposure to Air Pollution at School: Associations with Nano-Sized to Coarse PM in Children. Environmental Health Perspectives, 123(7), 737-42, DOI: 10.1289/ehp.1408121. PMC 4492263. PMID 25756964.

18. Raaschou-Nielsen O., Andersen Z.J., Hvidberg M., Jensen S.S., Ketzel M., Sorensen M. and Tjonneland A. (2011). Air pollution from traffic and cancer incidence: a Danish cohort study. Environmental Health, 10, 67, DOI: 10.1186/1476-069X-10-67. PMC 3157417. PMID 21771295.

19. Shuo L., Lei Y., Yannan Y., Huichao L., Jing T., Sijia L., Ning W. and Jiafu J. (2018). Cancer incidence in Beijing, 2014. Chinese journal of cancer research, 30(1), 13-20, DOI: 10.21147/j.issn.1000-9604.2018.01.02.

20. The new york time. (2017). India's Air Pollution Rivals China's as World's Deadliest, [online] Available at: www.nytimes.com/2017/02/14/world/asia/indias-air-pollution-rivals-china-as-worlds-deadliest.html. [Accessed 8 April 2019].

21. Tran Hong Ha. (2013). National Technical Regulation on Ambient Air Quality. Ministry of Natural Resources and Environment, 1-3. (in Vietnamese).

22. Van L.M. (1993). Testing interpolation and filtering techniques in connection with a semi-Lagrangian method. Atmospheric Environment. Part A. General Topics, 27(15), 2351-64.

23. Wong D.W., Yuan L. and Perlin S.A. (2004). Comparison of spatial interpolation methods for the estimation of air quality data. Journal of Exposure Analysis and Environmental Epidemiology 14(5), 404-15, DOI: 10.1038/sj.jea.7500338.

24. World Health Organization. (2018). Ambient (outdoor) air quality and health. [online] Available at: www.who.int/en/news-room/factsheets/detail/ambient-(outdoor)-air-quality-and-health. [Accessed 8 April 2019].

25. World Health Organization. (2016). Ambient air pollution: A global assessment of exposure and burden of disease. [online] Available at: www.who.int/phe/publications/air-pollution-global-assessment/en/ [Accessed 8 April 2019].

26. Yang Z.P., Lu W.X., Long Y.Q. and Liu X.R. (2010). Prediction and precaution of heavy metal pollution trend in urban soils of Changchun City, Urban Environ. Urban Ecol, 23, 1-4.


For citation:


Nguyen T., Kosinova I.I., Đang T. Modeling Air Pollution In Dong Nai Province, Vietnam. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2020;13(2):166-174. https://doi.org/10.24057/2071-9388-2019-44

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ISSN 2071-9388 (Print)
ISSN 2542-1565 (Online)