Open AccessModeling Air Pollution and Temperature Components to Identify Their Effects on India’s Capital using Python
Author(s) -
Samir D. Mathur,
Shanu Sharma
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b6213.019320
Subject(s) - python (programming language) , contamination , air temperature , environmental science , pollution , air pollution , global warming , climate change , mean radiant temperature , meteorology , computer science , geography , oceanography , chemistry , geology , ecology , organic chemistry , biology , operating system
Various past research works have shown that temperature can alter the effect of ambient fine particles category PM 2.5 which causes the high mortality risk. In surveying air contamination impacts, temperature is generally considered as a confounder. In any case, encompassing temperature can change individuals' physiological reaction to air contamination and might alter the effect of air contamination on wellbeing results. This study investigates the interaction between monthly values of PM2.5 and monthly average temperature values in Delhi, India using data for the period 2010–2018. The computer language Python is used to analysis facts and produce the outcomes which can shape the future research work and policies to overcome both global issues- pollution and Global warming.