Estimation of health impact using AirQ+ model attributed to surface ozone in sub-regions of Surat city, India

Abstract

Introduction: Deteriorated air quality in nation like India contributes to the health burden. The AirQ+ is used to estimate short-term and long-term health impact attributable to surface Ozone (O3) in Surat city. Average hourly ozone concentration data and other criteria pollutants retrieved from January 2018 to December 2019 from two monitoring stations (Limbayat and Varachha).
 Materials and methods: In this study, the Respiratory Mortality (RM), Cardiovascular Mortality (CM), Total Mortality (TM), Hospital Admissions with Cardiovascular Disease (HACVD), and Hospital Admissions with Respiratory Disease (HARD), as well as Respiratory Mortality-Long-Term (LT-RM) were quantified. Baseline Incidence (BI) data were obtained from literature and Relative Risk (RR) values were referred from World Health Organization (WHO). An annual Sum of Maximum 8 h Ozone means over 35 ppb (SOMO35), 70 µg/m3, used as a predictor of potential long-term health effects.
 Results: More ozone concentration were observed in winter and pre-monsoon than concentration formed in southwest monsoon and post-monsoon seasons.The average of O3 concentration for Limbayat are 71.61 (±0.39) µg/m3 and 29.76 (±1.86) µg/m3 and for Varachha are 61.17 9 (±6.15) µg/m3, 11.32 (±1.35) µg/m3 during 2018 and 2019, respectively and the obtained cumulative number of cases of death are estimated 136, 45, 172 and 18 persons respectively. Total hospital admission due to cardiovascular and respiratory diseases are found 435, 134, 552 and 58 at Limbayat and Varachha during 2018 and 2019. LT- RM is attributed to ozone concentration having the most significant value, 6.8% and 4.62% at Limbayat and Varachha in 2018.
 Conclusion: More hospital admissions are found than mortality rates using AirQ+ tool. It can be used to estimate public health in context of mortality and morbidity rates which helps to develop air quality management programs and policy makers to reduce the impact of air pollution on health.

Increased tropospheric ozone levels as a public health issue during COVID-19 lockdown and estimation the related pulmonary diseases

“…The number of MRD due to O 3 exposure in Ahvaz (Iran) with population higher than 1.3 million was 6.17 for people with ages ≥30 year-old ( Karimi et al, 2019 ). In Surat (India), 24 HA-CVD, 1 MRD, and 4 LT-MRD per 10 5 people were attributed to O 3 exposure in 2018 ( Jariwala and Kapadia, 2022 ).…”

“…To estimate the population exposure to O 3 levels, at first standard Z-scores were identified in time series. The concentration-response (C-R) is a developed model from different meta-analyses and systematic reviews of health effects due to exposure to different air pollutants in the world ( Amoatey et al, 2020 ; Jariwala and Kapadia, 2022 ; Naghan et al, 2022 ). For that, we need three parameters including the number of people at-risk (N) in a city, the baseline incidence (BI), and the relative risk (RR) values.…”

“… Health outcomes BI a RR b per 5 ppb (95% CI c ) Ref. Hospital admission-CVD 436 1.009 (1.005–1.0127) ( De Marco et al, 2022 ), ( Héroux et al, 2015 ) Respiratory mortality (age≥30) 44–53 1.014 (1.005–1.024) ( De Marco et al, 2022 ), Héroux et al (2015) Long-term respiratory mortality 66 1.013 (1.005–1.024) Jariwala and Kapadia (2022) a Baseline incidence. b Relative risk.…”

“…This method was used in Ahvaz for estimating related respiratory diseases mortality by O 3 exposure in the period 2012–2018 ( Naghan et al, 2022 ). Similar O 3 risk assessments were conducted based on concentration-response (C-R) function model in Texas ( Zu et al, 2017 ), Surat City ( Jariwala and Kapadia, 2022 ), Tabriz ( Barzeghar et al, 2019 ), Canada ( Zhao et al, 2021 ), Ahvaz (Amoatey et al, 2019), Mexico city and New York ( Gurjar et al, 2010 ), Tehran ( Hadei et al, 2017a ), and Catalonia ( Rovira et al, 2020 ).…”