Indoor and Ambient Air Pollution in Chennai, India during COVID-19 Lockdown: An Affordable Sensors Study

Abstract

The Tamil Nadu Air Pollution and Health Effects study (TAPHE-2) aims to evaluate the relationship between air pollution and birth outcome in a rural-urban cohort of 300 pregnant women. Due to COVID-19 related lockdowns, some TAPHE-2 activities were delayed; however, continuous indoor and outdoor air quality data were collected in and around Chennai, India. We report here the impact of graded COVID-19 lockdown on indoor particulate matter (PM2.5 and PM10) levels based on calibrated data from affordable real-time PM sensors called atmos™ and ambient PM levels from publicly available regulatory monitors. The study period was between 11 March and 30 June 2020 (i.e., 100 days of continuous monitoring), which coincided with four phases of a nationwide graded lockdown. Field calibration coefficients for the atmos PM were derived by collocating them with reference-grade PM monitors. The normalized root mean square error (NRMSE) of the atmos hourly PM2.5 (PM10) improved from 41% to 15% (33% to 18%) after applying the field calibration coefficients. Lockdowns resulted in significant reductions in indoor and ambient PM levels, with the highest reduction observed during lockdown phase 2 (L2) and phase 3 (L3). Reductions as high as 70%, 91%, and 62% were observed in ambient PM2.5, indoor PM2.5, and indoor PM10 relative to pre-lockdown levels (PL), respectively. The indoor PM2.5/PM10 ratio decreased during the lockdown, suggesting a decline in the fine mode dominance in PM10. The indoor-to-outdoor (I/O) ratios in PM2.5 marginally increased during L1, L2, and L3 phases compared to that of PL levels, suggesting an uneven reduction in indoor and ambient PM2.5 levels during the lockdown.

Inter- versus Intracity Variations in the Performance and Calibration of Low-Cost PM2.5 Sensors: A Multicity Assessment in India

“…In addition, the SD card in Atmos stores data as a backup. More details on Atmos and the Plantower PMS7003 can be found elsewhere. , …”

Site and Season Specific Calibrations Improve Low-cost Sensor Performance: Long-term Field Evaluation of PurpleAir Sensors in Urban and Rural India

“…Recently there is increased interest in understanding LCS performance in the Global South to fill major monitoring gaps (Bai et al, 2020;Jha et al, 2021;Malyan et al, 2023;McFarlane et al, 2021;Puttaswamy et al, 2022;Sreekanth et al, 2022;Zheng et al, 2018Zheng et al, , 2019. In North India, Zheng et al (2018) deployed Plantower models in Kanpur, Uttar Pradesh, for 90 days and found multilinear regression improved Plantower performance, albeit with significant error for hourly data.…”

“…In North India, Zheng et al (2018) deployed Plantower models in Kanpur, Uttar Pradesh, for 90 days and found multilinear regression improved Plantower performance, albeit with significant error for hourly data. In South India, Puttaswamy et al (2022) calibrated Plantower units for 68-days in Chennai and found a multilinear regression approach reduced uncertainty to within 15% and 18% for PM 2.5 and PM 10 respectively. LCS studies in India report the importance of climate and emissions variability on aerosol characteristics and advise future deployments to test calibration algorithms across longer timelines (Malyan et al, 2023;Puttaswamy et al, 2022;Sreekanth et al, 2022;Zheng et al, 2018Zheng et al, , 2019.…”

Changes in healthy effects and economic burden of PM2.5 in Beijing after COVID-19

“…During the COVID-19 pandemic, the number of vehicles on highways in the Metropolitan Region of São Paulo (MRSP), Brazil, decreased by 50% compared to 2019, and air quality improved significantly (Perez-Martinez et al 2022). During the outbreak lockdown, both indoor and ambient PM levels in Chennai, India, were significantly reduced (Puttaswamy et al 2022). Changes in anthropogenic emissions in Hubei Province, China, during the COVID-19 outbreak resulted in a decrease in PM 2.5 concentration levels of about 33.3% compared to the same period in 2019, while changes in meteorological conditions increased PM 2.5 concentrations by about 8.8% (Liu et al 2022).…”