Extreme heat in recent years in the developed countries, including North
America and Europe, has been associated with an appreciable rise in mortality in these
countries. But little information is available about developing regions in South Asia. In the
context of the increasingly visible consequences of air pollution and climate change, there is
a need for reliable projections of the expected changes, the probability of their occurrence
and their likely impact on health. The present study uses statistical models to estimate
seasonal variations and project trends in temperature, air quality and heat-related mortalities,
which are issues of concern for a) India's population, especially b) those from the working
and older age groups.
This study took the data available on the website (data.gov.in) of
Government of India. Temperature data was categorized according to the season: premonsoon,
post-monsoon, winter and monsoon/summer. Air quality data for the period
January 2020 - May 2020 was obtained from the website (https: //app.cpcbccr.com) of
Central Pollution Control Board. This data included PM10, PM2.5, NO2 and SO2 values.
According to the World Air Quality Report 2019, Ghaziabad and Delhi are the most polluted
cities in India. Kolkata and Hyderabad are among India's ten most populated cities. This
study compares the lockdown effect on air quality in Ghaziabad, Delhi, Kolkata, Hyderabad
and Cochin. Cochin was included to understand pollution trends in Kerala, which is less
polluted than other states (World's most Contaminated Cities in the year 2020 - PM2.5
Position Air Graphic, n.d.). Linear, Inverse, Logarithmic, Quadratic, Power Compound,
Cubic, Logistic, S, Exponential and Growth, statistical models were applied to temperature
data to obtain the most appropriate model for the prediction of maximum and minimum
temperature. The study also directed analysis of all-cause mortalities associated with the 2010
May heat wave in Ahmadabad (Gujarat) to govern whether thrilling heat leads to surplus
death.
