Increased average annual prevalence of upper respiratory tract infection (UTRI) in the central Indian population residing near the coal-fired thermal power plants

Author:

Barik Puspita,Naoghare Pravin,Sivanesan Saravanadevi,Kannan Krishnamurthi,Middey Anirban

Abstract

AbstractPeople are vulnerable to health risks due to particulate matter generated through the coal combustion processes. The air pollution due to the thermal power plant is a primary concern among all sources of pollution. The air pollution due to the coal-fired thermal power plant is a primary concern among all the different sources of pollution. The air quality (suspended particulate matter; SPM) modeling in the study area of central India was carried out using CALAUFF model. In addition, real-time air monitoring of particulate matter PM1, PM2.5 and PM10 was carried out in the study area. Real-time air quality monitoring data showed higher concentration of particulate matter (PM1 and PM2.5) at different locations in the study area, exceeding the regulatory limits set by NAAQS (National Ambient Air Quality Standards) and WHO (World Health Organization). Considering the most probable health impacts due to coal-fired thermal power plant, diseases such as chronic upper respiratory tract infections (URTI), and asthma were focused in this study. Hospital admission data were collected for respiratory disorders from six different public health centers (PHCs) located in the study area for the years 2012 and 2013. Average annual prevalence (AAP) of asthma at Dhapewada, Patansaongi, Chicholi, Satak, Droli and Kanhan PHCs was observed to be 0.581, 0.218, 0.201, 0.155, 0.377 and 0.198%, respectively, whereas AAP of UTRI at Dhapewada, Patansaongi, Chicholi, Satak, Droli and Kanhan PHCs was 24.961, 40.693, 0.769, 12.775, 28.605 and 14.898%, respectively. Thus, we conclude that the study population residing nearby the coal-fired thermal power plants may have an increased risk to upper respiratory tract infections (URTI) than asthma.

Funder

Department of Science and Technology

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Physics and Astronomy,General Engineering,General Environmental Science,General Materials Science,General Chemical Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Eff-AQI: An Efficient CNN-Based Model for Air Pollution Estimation: A Study Case in India;Proceedings of the 2023 ACM Conference on Information Technology for Social Good;2023-09-06

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