Study on Temperature Variation Pattern Based on Data Analytics

摘要

The anthropogenic activities of the past 150 years have led to an increasing concentration of trace gases and particulate matter in the atmosphere. Major pollutants in the study are ozone, oxides of carbon, oxides of nitrogen, methane, non-metal hydrocarbons, suspended particulate matter (PM2.5 and PM10) and black carbon. Air quality monitoring station data helps in the estimation of emission inventories of these pollutants which in turn acts as the input data for a climate model. Effective decisions should be made with precision and for better analytical results; a new way to deal with the problem should have opted and visualization for the result can be done in the form of charts and graphs to assimilate the measurements. This paper assesses the ambient air quality status in Delhi and gives a new approach to Data Analytics called Pollution Level Forecasting.