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Evaluation of Air Quality Index for Air Quality Data Interpretation in Delhi, India


Affiliations
1 Faculty of Engineering and Technology, Jamia Millia Islamia, Delhi 110 025, India
2 Department of Biostatistics, St. Johns Medical College, Bengaluru 560 034, India
3 AL-FALAH University, Dhauj, Faridabad, Haryana 121 004, India
 

Metro cities across the world use air quality index (AQI) as a tool for local air quality management. The basic purpose of the AQI system is to interpret the air quality status based on potential human health impacts. In the air quality indexing system, ranges of air pollutant concentration are characterized into different categories of air quality on the basis of health implication criteria. Standardized public health advisories are used for different categories of air quality for general public awareness. AQI values at the regional level are normally reported in the media to enhance public access and awareness. In the present study, air quality of Delhi, India has been interpreted, and seasonal and spatial deviation of air quality mapped to enable health risk communication. We also highlight the linkage of air quality with daily nontrauma mortality rate. A significant correlation of air quality with daily non-trauma death rate was observed. The female population was found to be more vulnerable to poor air quality in comparison to the males. Among the different age groups, maximum vulnerability was observed for the population aged 65 years and above. Average air quality status of Delhi was observed at a level which can cause breathing uneasiness to those with respiratory comorbidities, as well as for children and aged people. Direct linkages of different air pollutants with associated health impact estimates have been worked out by several researchers in the past. The present study evaluates the effect estimates on daily non-trauma mortality values with AQI levels. The findings of this study are consistent with earlier reports and provide additional evidence for health impact linked to poor air quality.

Keywords

Air Quality, Metro Cities, Public Awareness, Respiratory Health.
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  • World Health Organization, WHO air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide: global update 2005: summary of risk assessment. No. WHO/SDE/PHE/OEH/06.02, WHO, Geneva, 2006.
  • Chen, R., Kan, H., Chen, B., Huang, W., Bai, Z., Song, G. and Pan, G., Association of particulate air pollution with daily mortality: The China air pollution and health effects study. Am. J. Epidemiol., 2012, 175(11), 1173–1181.
  • Mostofsky, E. et al., Modeling the association between particle constituents of air pollution and health outcomes. Am. J. Epidemiol., 2012, 176(4), 317–326.
  • Murray, C. J. and Lopez, A. D., Measuring the global burden of disease. N. Engl. J. Med., 2013, 369(5), 448–457.
  • Smith, K. R. et al., Millions dead: how do we know and what does it mean? Methods used in the comparative risk assessment of household air pollution. Annu. Rev. Public Health, 2014, 35, 185–206.
  • WHO, Burden of disease from ambient air pollution for 2012. World Health Organization, Geneva, 2014.
  • Gurjar, B. R., Jain, A., Sharma, A., Agarwal, A., Gupta, P., Nagpure, A. S. and Lelieveld, J., Human health risks in megacities due to air pollution. Atmosp. Environ., 2010, 44(36), 4606–4613.
  • Balakrishnan, K., Ganguli, B., Ghosh, S., Sankar, S., Thanasekaraan, V., Rayudu, V. N. and Caussy, H., Part 1. Short-term effects of air pollution on mortality: results from a time-series analysis in Chennai, India. Research report, Health Effects Institute, Boston, USA, 2011, 157, pp. 7–44.
  • Rajarathnam, U., Sehgal, M., Nairy, S., Patnayak, R. C., Chhabra, S. K. and Ragavan, K. V., Part 2. Time-series study on air pollution and mortality in Delhi. Research report, Health Effects Institute, 2011, 157, pp. 47–74.
  • Dholakia, H. H., Bhadra, D. and Garg, A., Short term association between ambient air pollution and mortality and modification by temperature in five Indian cities. Atmos. Environ., 2014, 99, 168– 174.
  • Maji, S., Ahmed, S., Siddiqui, W. A. and Ghosh, S., Short term effects of criteria air pollutants on daily mortality in Delhi, India. Atmos. Environ., 2017, 150, 210–219.
  • Maji, S., Ghosh, S. and Ahmed, S., Association of air quality with respiratory and cardiovascular morbidity rate in Delhi, India. Int. J. Environ. Health Res., 2018, 28(5), 471–490.
  • Global Burden of Disease MAPs Working Group, Burden of disease attributable to major air pollution sources in India. Special report 21, 2018.
  • Government of Delhi, Annual report on registration of births and deaths in Delhi, Directorate of Economics and Statistics, New Delhi, 2010 (various issues).
  • Marlier, M. E., Jina, A. S., Kinney, P. L. and DeFries, R. S., Extreme air pollution in global megacities. Curr. Clim. Change Rep., 2016, 2(1), 15–27.
  • Environmental Protection Agency, Technical assistance document for the reporting of daily air quality – air quality index (AQI). Environmental Protection Agency, Office of Air Quality Planning and Standards, North Carolina, USA, 2013.
  • Central Pollution Control Board, National air quality index. Control of urban pollution series CUPS/82/2014-15, 2014; http://cpcb.nic.in/FINAL-REPORT_AQI.pdf.
  • Gurjar, B. R., Ravindra, K. and Nagpure, A. S., Air pollution trends over Indian megacities and their local-to-global implications. Atmos. Environ., 2016, 142, 475–495.
  • Central Pollution Control Board, National ambient air quality monitoring series NAAQMS/35/2011-2012; 2012; www.cpcb.nic.in 20. Maji, S., Ahmed, S. and Siddiqui, W. A., Air quality assessment and its relation to potential health impacts in Delhi, India. Curr. Sci., 2015, 109(5), 902–909.
  • Government of Delhi, Delhi Statistical Handbook, Directorate of Economics and Statistics, New Delhi, 2001–2010.
  • General, Registrar. (2011), Census Commissioner, India. Census of India, 2000.
  • Cleveland, W. S. and Loader, C., Smoothing by local regression: principles and methods. In Statistical Theory and Computational Aspects of Smoothing, Physica-Verlag HD, New Jersey, UK, 1996, pp. 10–49.
  • James, G., Witten, D., Hastie, T. and Tibshirani, R., Linear model selection and regularization. In An Introduction to Statistical Learning, Springer, New York, USA, 2013, pp. 203–264.
  • Liu, T. et al., Seasonal impact of regional outdoor biomass burning on air pollution in three Indian cities: Delhi, Bengaluru, and Pune. Atmos. Environ., 2018, 172, 83–92.

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  • Evaluation of Air Quality Index for Air Quality Data Interpretation in Delhi, India

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Authors

Sanjoy Maji
Faculty of Engineering and Technology, Jamia Millia Islamia, Delhi 110 025, India
Sirajuddin Ahmed
Faculty of Engineering and Technology, Jamia Millia Islamia, Delhi 110 025, India
Santu Ghosh
Department of Biostatistics, St. Johns Medical College, Bengaluru 560 034, India
Saurabh Kumar Garg
AL-FALAH University, Dhauj, Faridabad, Haryana 121 004, India

Abstract


Metro cities across the world use air quality index (AQI) as a tool for local air quality management. The basic purpose of the AQI system is to interpret the air quality status based on potential human health impacts. In the air quality indexing system, ranges of air pollutant concentration are characterized into different categories of air quality on the basis of health implication criteria. Standardized public health advisories are used for different categories of air quality for general public awareness. AQI values at the regional level are normally reported in the media to enhance public access and awareness. In the present study, air quality of Delhi, India has been interpreted, and seasonal and spatial deviation of air quality mapped to enable health risk communication. We also highlight the linkage of air quality with daily nontrauma mortality rate. A significant correlation of air quality with daily non-trauma death rate was observed. The female population was found to be more vulnerable to poor air quality in comparison to the males. Among the different age groups, maximum vulnerability was observed for the population aged 65 years and above. Average air quality status of Delhi was observed at a level which can cause breathing uneasiness to those with respiratory comorbidities, as well as for children and aged people. Direct linkages of different air pollutants with associated health impact estimates have been worked out by several researchers in the past. The present study evaluates the effect estimates on daily non-trauma mortality values with AQI levels. The findings of this study are consistent with earlier reports and provide additional evidence for health impact linked to poor air quality.

Keywords


Air Quality, Metro Cities, Public Awareness, Respiratory Health.

References





DOI: https://doi.org/10.18520/cs%2Fv119%2Fi6%2F1019-1026