Difference between revisions of "IS428 AY2018-19T1 Gokarn Malika Nitin"

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I started by bringing in the EEA Data for the years 2013 to 2018. The aim is to visualize the concentration in terms of the average, across a Calendar Heatmap, to understand the outliers, and any potential anomalies. It can be understood that data across all stations is missing for the time period of 1 January 2017 to 28 November 2017.
  
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[[File:OriginalHeatmap.jpg|500px|center]]
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Characterize the past and most recent situation with respect to air quality measures in Sofia City. What does a typical day look like for Sofia city? Do you see any trends of possible interest in this investigation?  What anomalies do you find in the official air quality dataset? How do these affect your analysis of potential problems in the environment? 
 
  
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Your submission for this questions should contain no more than 10 images and 1000 words.
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This HeatMap visualized above shows the potential for a trend during the winter months from November onwards. However, the trend here is shown by the assigned palette which means that proper definition of boundary conditions is required to see a trend which we can make sense of.
  
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Therefore, making use of the legend available with this map [https://www.eea.europa.eu/themes/air/air-quality-index/index#tab-based-on-data] that visualizes the European Air Quality Index for the year 2017. This legend is defined by the European Environment Agency. Therefore, I built binning criteria as shown below:
  
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{| class="wikitable" style="background-color:#FFFFFF;" width="100%"
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|-
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! style="font-weight: bold;background: #581845;color:#FFFFFF;width: 20%;" | Lower Bound (inclusive)
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! style="font-weight: bold;background: #581845;color:#FFFFFF;width: 30%" | Upper Bound (exclusive)
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! style="font-weight: bold;background: #581845;color:#FFFFFF;" | Label
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|-
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| -
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|| 20
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|| Good
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|-
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| 20
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|| 35
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|| Moderate
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|-
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| 35
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|| 50
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||Unhealthy for Sensitive Groups
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|-
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| 50
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|| 100
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|| Unhealthy
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|-
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| 100
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|| -
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|| Hazardous
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|-
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|}
  
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Firstly, we are looking at only EEA Data from 2013 to 2018. By looking at the data as a whole, we identified that all stations have missing values from the period of 1 Jan 2017 to 28 November 2017.
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It is important to note that 50μg/m3 measured daily is the limit for Bulgaria with a 35 exceedances each year [http://ec.europa.eu/environment/air/quality/standards.htm]. Thus it is important that the graph is generated so as to clearly pinpoint the days where the concentration exceeds 50μg/m3. This will clearly differentiate the days that residents of Sofia City are breathing healthy air. Based on the above bins a colour scale can be developed, thereby allowing us to visualize a typical day in Sofia City. The resultant graph is as below:
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''' INSERT THE FIRST GRAPH HERE '''
 
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From this simple plot, we are able to identify that there is a pattern in the increase of the concentration of PM10. This means that there could be an interesting reason for the cause. Thus I decided to explore what is the current standards for PM10 to be considered unhealthy. Sofia City is located in Bulgaria, which is part of EU, thus I referenced to their standards of air quality from this [http://ec.europa.eu/environment/air/quality/standards.htm link]. From [https://www.epa.vic.gov.au/your-environment/air/air-pollution/pm10-particles-in-air this link] we can further categorize the PM Air quality into different categories. Firstly 50μg/m3 measured daily is the limit for Bulgaria with a 35 exceedences each year. Thus we need to generate a graph that can clearly pinpoint on which day the concentration exceeds and when are the days where people in Sofia city can enjoy breathing healthy air.  
 
  
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''' INSERT THE CATEGORIES HERE '''
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[[File:Calendar HeatMap Final.jpg|500px|center]]
  
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I used the above categorization as my Color Scaling to visualize how a typical day in Sofia City looks like.  
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This second categorization allows us to understand that true to the reputation of Bulgaria, Sofia city too has a very high level of concentration of PM10. This is especially so across the year with a dip in the summer months of May, June, and July. More importantly, there are spikes in January and December. The global maxima of all the data is found on 25th December 2013, for which there are cultural reasons explaining the spike in air pollution, as can be found at the following [https://www.novinite.com/articles/135151/Bulgaria+Celebrates+with+Christmas+Eve+Traditions link], wherein it is stated that “Strict tradition demanded that a fire be built in the hearth, with enough wood to burn all night and into Christmas Day, to help with the new birth of the sun.”
  
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''' INSERT THE HEATMAP HERE '''
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[[File:Control Plot.jpg|500px|center]]
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The Calendar Heatmap helps to highlight the overall daily trend of high pollution in terms of PM10. However, in order to better visualize the amount of spike between days, a control plot would be more intuitive in understanding the data. It is noticeable that between 18th and 24th January as well as on Christmas days each year there are spikes. Air pollution is high on Christmas days has already been explained by the cultural significance and traditions above. While there are no significant [https://www.officeholidays.com/countries/bulgaria/index.php public holidays] during the days of interest in January, I wondered whether there was a chronic trend of January 18th to 24th being the coldest days of the year in Bulgaria. It is interesting to note that while I have not found specific data that points to these dates being the coldest of the year, the average temperature recorded for the month of January is -5 degree to 2 degrees Celsius. [https://www.climatestotravel.com/climate/Bulgaria]
  
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By categorizing the concentration, we can identify that actually, Sofia City is facing a high level of concentration of PM10. Surprisingly, other than the spikes in January and December, Sofia City is also facing a high concentration of pollutant across the years except for June.
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Taking this into account, residents of Bulgaria might be more inclined to lighting fires to get through the cold. Additionally, I found that forest fires are not rare in Bulgaria, and this could have some amount of significant contribution to the deteriorating air quality. [https://sofiaglobe.com/2017/08/28/bulgaria-kresna-gorge-forestfires-lead-to-more-evacuations/]
  
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''' INSERT THE Control Plot HERE '''
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The final dashboard would look like the following:
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[[File:Dashboard Task 1.png|500px|center]]
  
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Although Heatmap can highlight the seriousness of pollution Sofia is facing, but using Control Plot, we can use it to identify the underlying pattern and interesting insight from this graph. You can notice that every year during 24th December and between 18th to 24th January, there is a significant rise in the concentration of PM10 in Sofia. Could this be a coincidence or a reason behind this. I look up the [http://www.parliament.bg/en/24 national holidays] of Bulgaria and try to identify to see other Festive Seasons also have a significant rise other than Christmas Season, but in this case there isn't.
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<b> References </b>:
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# Air quality index. (2018, May 04). Retrieved from https://www.eea.europa.eu/themes/air/air-quality-index/index#tab-based-on-data
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# Air Quality Standards. (n.d.). Retrieved from http://ec.europa.eu/environment/air/quality/standards.htm
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# Bulgaria Celebrates with Christmas Eve Traditions. (n.d.). Retrieved from https://www.novinite.com/articles/135151/Bulgaria Celebrates with Christmas Eve Traditions
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#
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# Climate - Bulgaria. (n.d.). Retrieved from https://www.climatestotravel.com/climate/Bulgaria
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# Public Holidays in Bulgaria in 2018. (n.d.). Retrieved from https://www.officeholidays.com/countries/bulgaria/index.php
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# Bulgaria: Kresna Gorge forest fires lead to more evacuations. (2017, August 30). Retrieved from https://sofiaglobe.com/2017/08/28/bulgaria-kresna-gorge-forestfires-lead-to-more-evacuations/
  
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''' INSERT THE Final Dashboard HERE '''
 
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Reference for Task 1:
 
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Your submission for this questions should contain no more than 10 images and 1000 words.
 
 
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Revision as of 07:16, 11 November 2018

Problem and Motivation

Dataset Analysis and Transformation Process

Task 1: Spatio-temporal Analysis of Official Air Quality

Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements

Using appropriate data visualisation, you are required will be asked to answer the following types of questions:

  • Characterize the sensors’ coverage, performance and operation. Are they well distributed over the entire city? Are they all working properly at all times? Can you detect any unexpected behaviours of the sensors by analyzing the readings they capture? Limit your response to no more than 4 images and 600 words.
  • Now turn your attention to the air pollution measurements themselves. Which part of the city shows relatively higher readings than others? Are these differences time-dependent? Limit your response to no more than 6 images and 800 words.

Task 3

Urban air pollution is a complex issue. There are many factors affecting the air quality of a city. Some of the possible causes are:

  • Local energy sources. For example, according to Unmask My City, a global initiative by doctors, nurses, public health practitioners, and allied health professionals dedicated to improving air quality and reducing emissions in our cities, Bulgaria’s main sources of PM10, and fine particle pollution PM2.5 (particles 2.5 microns or smaller) are household burning of fossil fuels or biomass, and transport.
  • Local meteorology such as temperature, pressure, rainfall, humidity, wind etc
  • Local topography
  • Complex interactions between local topography and meteorological characteristics.
  • Transboundary pollution, for example, the haze that intruded into Singapore from our neighbours.

In this third task, you are required to reveal the relationships between the factors mentioned above and the air quality measure detected in Task 1 and Task 2. Limit your response to no more than 5 images and 600 words.

Software

  • Tableau - for visualization of the various tasks
  • Python - for geocoding

References

Retrieved from ‘https://wiki.smu.edu.sg/18191is428g1/index.php?title=IS428_AY2018-19T1_Gokarn_Malika_Nitin&oldid=1889’