Modeling Air Pollution and Temperature Components to Identify Their Effects on India‟s Capital using Python
Sandeep Mathur1, Satvik Sharma2
1Sandeep Mathur*, Amity Institute of Information Technology Amity University, Uttar Pradesh.
2Satvik Sharma, Amity Institute of Information Technology Amity University, Uttar Pradesh.
Manuscript received on December 12, 2019. | Revised Manuscript received on December 24, 2019. | Manuscript published on January 10, 2020. | PP: 711-715 | Volume-9 Issue-3, January 2020. | Retrieval Number: B6213129219/2020©BEIESP | DOI: 10.35940/ijitee.B6213.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Data Analytics, Air Pollution, Metrological factors, Python, CPCB
Scope of the Article: Data Analytics