Forecasting air pollution load in Delhi using data analysis tools
Abstract
The enormity of air pollution has always been a matter of concern due to rapid development and urbanization over a long period. The increasing level of pollutants in ambient air in 2016-2017 has deteriorated the air quality of Delhi at an alarming rate. This brought us to focus our study on air quality in Delhi region. The prediction of future air quality has been carried out by analyzing the pollutants using data analysis techniques.
In our previous study, we had analyzed the data from 2011-2015. Detailed analysis from 2009-2017 of air pollutants has been proposed in this extended paper along with the critical observation of 2016-2017 air pollutants trend in Delhi. Descriptive analysis and predictive analysis have been used to study the trends of various air pollutants like sulphur dioxide (SO2), nitrogen dioxide (NO2), suspended particulate matter (PM), ozone (O3) carbon monoxide (CO), benzene, and forecast the future trend. We have observed through data analytics techniques that SO2 is likely to increase by 1.24ug/m3, NO2 is likely to increase by 16.77ug/m3, O3 is likely to increase by 6.11 mg/m3, benzene is likely to reduce by 1.33 mg/m3 and NO2 is predicted to reduce by 0.169 mg/m3 in the coming years.
References
[1]
Seinfeld J. H, Pandis S., Atmospheric chemistry and physics, 2nd ed., John Wiley, Hoboken (NJ), 2006.
[2]
Statistical Abstract (2016) Delhi Govt Portal, www.delhi.gov.in.
[3]
Cohen Aaron J, Brauer Michael, Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study, The Lancet 389 (10082) (2017) 1907–1908.
[4]
Rizwan SA, Nongkynrih B, Gupta SK, Air pollution in Delhi: Its Magnitude and effects on health., Indian J Community Med 38 (1) (2013) 4–8.
[5]
Kumar, P, Kumar, S and Joshi, Laxmi. (2014) “Socioeconomic and Environmental Implications of Agricultural Residue Burning, A Case Study of Punjab, India.” Springer Briefs in Environmental Science, DOI 10.1007/978-81-322-5_1.
[6]
Technical report. (2017) “CPCB Guidelines on Environmental management on C & D Wastes (Prepared in compliance of Rule 10 sub-rule 1(a) of C & D Waste Management Rules, 2016).
[7]
Realtime ambient air quality data of Delhi, DPCClink:http://www.dpccairdata.com/dpccairdata/display.
[8]
WHO’s Urban Ambient Air Pollutiondatabase Update 2016 http://www.who.int/phe/health_topics/outdoorair/databases/AAP_database_summary_results_2016_v02.pdf.
[9]
Sindhwani, R. (2012) “Assessment of gaseous and respirable suspended Particulate matter (PM10) emission estimates over megacity Delhi: past trends and future scenario (2000-2020).” 13th Annual CMAS Conference Chapel Hill, NC, USA.
[10]
Gurjar, B.R., Aardenne, J.A. van, Lelieveld, J., Mohan, M. (2004) “Emission estimates and trends (1990-2000) for megacity Delhi and implications.” Atmospheric Environment :5663–5681.
[11]
Sindhwani R., Goyal P., Assessment of traffic-generated gaseous and particulate matter emissions and trends over Delhi (2000-2010)., Atmospheric Pollution Reseach 5 (3) (2014) 438–446.
[12]
Shaddick, G, Thomas, ML, Jobling, A et al. (2016) “Data integration model for air quality: a hierarchical approach to the global estimation of exposures to ambient air pollution.”.
[13]
Ma, Xin, Gong, Wei, Zhu, Zhongmin. (2016) “The study of long-term air pollution characteristic in Wuhan, China.” Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International
[14]
Kisi Ozgur Singh, Kulwinder Soni Kirti, Modeling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models., Air Quality, Atmosphere & Health 10 (7) (2017) 873–883.
[15]
Mishra, D., Goyal, P. (2015) “Development of artificial intelligence based NO2 forecasting models at Taj Mahal, Agra centre for atmospheric sciences”, Atmospheric Pollution Research: 99–106.
[16]
Soh, Ping-Wei, Chen, Kai-Hsiang, Huang, Jen-Wei. (2017) “Spatial-temporal Pattern Analysis and Prediction of Air Quality in Taiwan.” 10th International Conference on Ubi-media Computing and Workshops (Ubi-Media).
[17]
Kumar Anil, Kamal Dikshit, Maji Jyoti, Deshpande Ashok, Disability-adjusted life years and economic cost assessment of the health effects related to PM2.5 and PM10 pollution in Mumbai and Delhi, in India from 1991 to 2015, Environmental Science and Pollution Research 24 (5) (2017) 4709–4730.
[18]
Taneja, Shweta, Sharma, Nidhi, Oberoi, Kettun, Navoria, Yash. (2016) “Predicting Trends in Air Pollution in Delhi using Data Mining.” Information Processing (IICIP), 2016 1st India International Conference, DTU, New Delhi.
[19]
CPCB report on Air pollution in Delhi; An analysis (2016).
[20]
RStudio. (2018) [Online] Available at: https://www.rstudio.com/products/rstudio2/[Accessed 15 Jan. 2018].
[21]
Tableau Software. (2018). Tableau Desktop. [Online] Available at: https://www.tableau.com/products/desktop [Accessed 16 Jan. 2018].
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Published: 27 February 2024
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