The above plot shows 50 places with the highest so2 levels in descending order.Now let us plot the 50 locations with least so2 concentrations :We can see that the so2 level is least in Kottayam which is situated in Kerala, which is expected as we saw from the bar plot of so2 vs state that Kerala was one of those states having least so2 concentrations.It is clear from the figure that West Bengal has the maximum level of no2, whereas Nagaland has the least.The above plot shows 50 places with the highest no2 level.We see from the above plot that Rudrapur(Uttarakhand) is the least polluted city in terms of no2, followed by Alappuzha(Kerala) and Kohima(Nagaland).From the above plot, we see that Delhi has the highest concentration of rspm, which again is not surprising as it can be read from any news article related to pollution in India over the past few years.On the other hand, we have Sikkim with the least concentration of rspm, followed by Mizoram and Puducherry.Let us delve in deeper and see the concentrations of rspm location-wise :As seen from the above plot, we have Kashipur(Uttarakhand) which has the highest level of rspm, followed by Ghaziabad(UP) and Allahabad(UP). it has increased.The emission of the nitrogen dioxide pollutant has gone up significantly in the South Asia region, including India, during the 2005–2014 period, severely affecting air quality in the process, NASA satellite maps show.Heatmaps are such a vital tool for data analysis that it makes everything so easy to analyze. There can be multiple risk factors for a given disease which corroborate or amplify one another when both are present. Without controlling for ethnicity, we find that long-term exposure to fine particulate matter (PMHowever, when controlling for ethnicity, air pollution exposure has no statistically significant impact on COVID-19 deaths.As air pollution is just one of many factors that could be driving disproportionate outcomes for minority ethnic groups, the increased risk of dying from COVID-19 (found when ethnicity is not controlled for) is likely to be an overestimate of the true effect.In this study, we have only been able to examine air quality and COVID-19 deaths at the population level, based on the availability of existing data. In South Asia, it is ranked as the sixth most dangerous killer.Being a data analysis and data science enthusiast, I decided to analyze the air quality data of my own country to find some underlying principles or patterns which might give me an insight into how severe the problem is and I must say the results were worth sharing. So, here I am writing this article to share my approach and what I analyzed from the data and to also make people aware of the enormous problem our country is facing.The following data analysis is carried out in python, and the code can be downloaded from the Github repository: This data is a cleaner version of the Historical Daily Ambient Air Quality Data released by the Ministry of Environment and Forests and Central Pollution Control Board of India under the National Data Sharing and Accessibility Policy (NDSAP).The internet is filled with the harmful effects of the above pollutants, and hence it makes them an essential factor to be analyzed and considered when discussing air pollution.From the above figure, we see that we have 435742 entries in our dataset.It seems that we have a lot of null values in some columns.Let us stop for a bit and check how much helpful the features are.So, to summarize we will delete the following features from our dataset :Now it looks much better and cleaner. This is quite obvious as one is more concerned about the places where people live.We can see that we are left with 396157 values, so we have not removed a very high number of values. Air pollution is one of the world’s largest health and environmental problems. In low-income countries it tops the list. Today air pollution has been one of the significant problems to deal with for any nation. Make learning your daily ritual. By the week ending 12 June (cut-off date for this analysis), this had fallen to 18%.As the virus spread across the country and deaths became more evenly distributed, the correlation between air pollution exposure and COVID-19 mortality decreased.Our analysis includes 46,471 deaths involving COVID-19 among usual residents of England between 7 March 2020 and 12 June 2020, registered by 22 June 2020.We considered exposure to ozone, fine particulate matter (known as PMWhile death rates have generally been higher in polluted areas, this on its own does not establish pollution exposure as a cause of COVID-19 deaths.To isolate the impact of air pollution, we developed a statistical model controlling for factors such as levels of deprivation, population density, public health (such as smoking rates) and pre-existing health conditions.
In 2017, it was responsible for an estimated 5 million deaths globally. Most of the top locations belong to UP, which accounts for UP being the second most polluted state in terms of rspm.Now let us look at the locations with least concentrations of rspm :We see from the above plot that the least level of rspm is in Pathanamthitta(Kerala), followed by Nongstoin(Meghalaya) and Champhai(Mizoram).
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